Frontline knowledge, attitudes, and practices on climate change and its link to zoonotic diseases: a mixed-methods study of healthcare workers in Ada East, Ghana

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Yilma, Kirstin P. West, Hannah E. Sauve, Kristin K. Sznajder, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8282544/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 04 Mar, 2026 Read the published version in Discover Public Health → Version 1 posted 9 You are reading this latest preprint version Abstract Introduction Climate change alters patterns of infectious diseases and increases the risk of zoonotic spillover in vulnerable areas. This study examines how frontline healthcare workers (FHWs) in Ghana’s Ada East District understand and perceive the relationship between climate change and zoonotic disease transmission. Methods We conducted a concurrent mixed-methods study in the Ada East District, Ghana. A cross-sectional survey of FHWs evaluated knowledge, attitudes, and practices (KAP) regarding climate change and its link to zoonotic diseases. KAP scores were classified using Bloom’s cutoffs; adjusted logistic regression models identified predictors of good KAP. A purposively selected focus group (n = 9) explored perceived links between climate change and zoonotic disease, lived experiences, and institutional barriers. Results Most participants demonstrated good knowledge (≥60% correct; 83.2%) and attitudes (≥60% positive attitudes; 86.8%), but fewer reported good climate-mitigation practices (≥60% of good practices; 62.4%). Clinical staff other than nurses and midwives were associated with higher odds of good knowledge (adjOR = 4.52, 95% CI 1.12–22.76), while those trained on the human monkeypox virus were associated with lower odds of good knowledge (adjOR = 0.24, 95% CI 0.08–0.64). For practices, working in a district/regional hospital was associated with lower odds (adjOR = 0.18, 95% CI 0.05–0.61), as was training delivered by Ministry/Government authorities (adjOR = 0.44, 95% CI 0.21–0.91) and training on human monkeypox virus (adjOR = 0.39, 95% CI 0.17–0.90). Providers associated land-use change and bushmeat hunting with zoonotic spillover risk. They noted that spiritual beliefs, self-medication, and fear of income loss delayed care-seeking for suspected cases. Institutional preparedness was perceived as reactive. Participants called for climate-resilient infrastructure, integrated early-warning systems, and One Health training. Conclusion FHWs in Ghana’s Ada East District are knowledgeable and motivated to address climate-sensitive zoonotic risks. Yet, structural and sociocultural barriers limit the translation of frontline commitment into system-wide resilience. Strengthening climate-health education, investing in facility-level preparedness, and integrating FHW insights into surveillance could enable a shift from reactive outbreak response to proactive, community-based preparedness. Climate change Zoonotic diseases Knowledge attitudes and practices (KAP) Frontline healthcare workers One Health West Africa Figures Figure 1 Introduction Human-induced climate change, defined as long-term alterations in local, regional, and global weather patterns driven primarily by anthropogenic greenhouse gas emissions and land-use changes, has emerged as a key modifier of infectious disease dynamics [ 1 – 7 ]. Such climate stressors are intensifying the emergence and re-emergence of zoonotic diseases by altering environmental conditions that influence pathogen transmission [ 2 , 3 , 8 – 14 ]. In recent decades, zoonotic outbreaks have increased in both frequency and geographic range, a trend expected to worsen as climate pressures escalate [ 9 , 10 , 15 , 16 ]. Over 60% of emerging infectious disease events since 1940 have been zoonotic, with most traced to wildlife reservoirs [ 9 , 17 ]. These climate-related hazards are already intensifying global health risks [ 13 , 18 , 19 ]. While global evidence links climate stressors to zoonotic emergence, limited research explores how these mechanisms operate in specific regional contexts such as West Africa. Climate variability amplifies zoonotic spillover risk through disrupted ecosystems and host-pathogen dynamics [ 20 – 24 ]. Species migration, vector expansion, and habitat overlap increase cross-species viral exchange [ 25 – 33 ]. These changes increase the likelihood of new pathogen transmission cycles, especially in biodiversity-rich, rapidly urbanizing regions as in West Africa. These global patterns in climate change and disease vectors are acutely relevant to Ghana, which is home to 221 species of amphibians and reptiles, 728 bird species, and 225 mammal species [ 34 , 35 ]. Wetlands in Accra provide stopover habitats for migratory species, further contributing to the region’s potential reservoir of zoonotic pathogens [ 36 ]. Urban ecosystems like Accra’s wetlands host migratory birds and bat colonies, while bushmeat consumption and livestock encroachment into wildlife habitats intensify human–animal interfaces [ 36 – 63 ]. Clearly, much of Ghana’s population relies directly on these ecosystems for their livelihoods [ 36 , 38 , 39 , 45 , 46 , 64 ]. Few studies explore how environmental and livelihood changes affect zoonotic disease risks in Ghana, despite its ecological and social vulnerabilities. Frontline healthcare workers (FHWs)—including community nurses, clinicians, and public health officers—are pivotal to early outbreak detection and climate-resilient health systems in vulnerable regions such as Accra [ 65 – 68 ]. Embedded within their communities, they are trusted communicators who bridge clinical and community knowledge, translating climate–health messages into practical action[ 65 , 66 , 69 – 72 ]. However, the effectiveness of FHWs in this role depends on adequate awareness, knowledge, and training related to the climate–zoonoses nexus. The Intergovernmental Panel on Climate Change (IPCC) warns that the severity of climate-related health risks will hinge on how effectively health systems and their staff can anticipate and manage emerging threats [ 73 ]. Yet gaps remain between high-level climate–health policy and local implementation [ 66 – 68 , 72 ]. In Ghana, limited climate-specific training and constrained resources remain significant barriers to operationalizing climate–health strategies [ 74 ]. Without insight into how FHWs perceive and manage these interconnected challenges, it is difficult to tailor solutions that enhance zoonotic outbreak prevention, preparedness, and resilience at the community level in an era of climate change. To address these gaps, this study employed a mixed-methods approach to examine how FHWs in Ghana’s Ada East District understand and perceive the relationship between climate change and zoonotic disease transmission. This study (i) quantitatively assessed FHWs’ knowledge, attitudes, and practices (KAP) related to the climate-zoonoses nexus, gauging both their understanding and the extent to which this knowledge informs their practices; (ii) identified predictors of higher KAP, such as sociodemographics, professional experience, and prior training; and (iii) qualitatively contextualized survey findings through a focus group discussion, exploring FHWs’ perspectives on climate–zoonosis dynamics, barriers to climate adaptation in healthcare settings, and recommendations for strengthening zoonotic preparedness in a changing climate. Materials and method Study design and population This study employed a concurrent exploratory mixed-methods design, integrating quantitative cross-sectional survey data with a qualitative, semi-structured focus group discussion. Data collection took place from January 30th to February 7th, 2025, in the Ada East District of Ghana’s Greater Accra Region. Eighteen healthcare facilities were purposively sampled in collaboration with the University of Ghana (Figure 1). These included district hospitals, local health centers, and Community-Based Health Planning and Services compounds, chosen to reflect the diversity of the regional healthcare delivery system. We describe both the quantitative and qualitative procedures in the following section. Eligible participants included FHWs employed at the selected facilities who met the following inclusion criteria: (1) age ≥18 years; (2) actively involved in direct patient care at the facility for ≥3 months; (3) ≥6 months post-completion of formal clinical training; (4) proficient in English—the official language of healthcare delivery in Ghana; and (5) able to provide written informed consent. Individuals were excluded if they were not engaged in patient care, were unavailable during data collection, or declined to participate. Eligibility was confirmed at the time of enrollment by trained research personnel. The required sample size was calculated using a single-population proportion formula, as outlined in a prior manuscript [75]. Due to the absence of existing data specific to the Ada East District, we assumed a 6% prevalence of poor KAP, a 3% margin of error, and a 95% confidence level. This yielded a minimum sample size of 241 participants. To accommodate potential nonresponse and ensure sample diversity, we targeted 250 participants. Quantitative part Participant recruitment Survey recruitment was conducted on-site at each selected healthcare facility. In total, 250 subjects fulfilled inclusion criteria to this study, and thus, were included in the study. Recruitment at each facility continued until no additional eligible participants remained. Local data collectors coordinated with facility administrators to identify optimal recruitment windows that minimized disruption to clinical activities across day and night shifts. During these time windows, trained research assistants approached eligible staff in common areas to introduce the study and distribute informational leaflets. Interested individuals were escorted to a private area where the study was explained and questions were addressed. Survey pilot testing The survey instrument underwent pilot testing with 10 FHWs at a nearby hospital to assess question clarity, survey flow, and technical usability of tablet devices for data collection. Based on feedback, we refined the instrument by incorporating a standardized definition of climate change at the start of the attitude’s module. We clarified select climate mitigation practices to eliminate any ambiguity among participants. Ten research assistants were recruited and completed a two-day training in Good Clinical Practice, study-specific protocols, informed consent procedures, survey administration techniques, and hands-on instruction using the Research Electronic Data Capture (REDCap) platform. Surveys were administered using REDCap-enabled tablets via structured, interviewer-led sessions conducted in private areas of each facility. Research assistants read each survey question (in English) aloud to the participant and entered the participant’s responses into the REDCap-enabled tablet in real time. Each session lasted approximately 45 to 60 minutes. No personal identifiers were collected with the survey data, unless participants were willing to participate in the follow-up focus discussion groups. Those provided a first name and phone number, which were recorded in a separate, password-protected file accessible only to the principal investigator. Survey Measures A structured questionnaire was developed to assess FHWs’ KAP regarding climate change, its health impacts, and its links to zoonotic diseases such as EVD. Several items were adapted from previously validated KAP surveys and other peer-reviewed information sources on the topics of climate change, its health impacts, and the link to zoonotic diseases [76–80]. The tool included four main sections : sociodemographic and professional background, knowledge, attitudes, and practices related to climate change and health. Sociodemographic and Professional Characteristics Respondents reported age, sex, education, occupational role, facility type, total years of healthcare experience, and years managing infectious diseases. They also indicated prior formal training on infectious diseases (topics covered, training providers), and their frequency and preferred sources of information about climate change and zoonotic diseases (radio, television, internet, social media, or mobile applications). Knowledge of Climate Change and its Health Impacts Knowledge was assessed using 37 items (true/false and multiple-response) across three domains: Climate change (16 items): understanding of definitions, anthropogenic causes (industrial activity, deforestation, greenhouse gas emissions), and environmental effects (temperature rise, altered rainfall, floods, droughts). Health impacts (12 items): awareness of climate-related diseases (heat stress, vector- and water-borne diseases, malnutrition, respiratory and mental health conditions) and recognition of vulnerable groups. Climate–zoonoses link (9 items): knowledge of how climatic shifts alter pathogen ecology, host migration, and disease emergence. Each correct answer scored 1 point , incorrect/unsure scored 0 , yielding a total score of 0–37, expressed as a percentage. Scores ≥60% (≥23 points) were classified as good knowledge , both overall and by domain. Attitudes Toward Climate Change Mitigation and Health Seven Likert-scale statements (1 = strongly disagree to 4 = strongly agree) assessed attitudes toward: Support for climate change mitigation actions, Stakeholder responsibility (government, individuals, private sector, donors), Health sector’s environmental role, and Beliefs about human capacity to influence climate outcomes. For analysis, responses were dichotomized: “agree/strongly agree” = favorable (1); “disagree/strongly disagree” = unfavorable (0). The negatively worded item (“Climate change is an act of God and cannot be controlled”) was reverse-coded. Total attitude scores ranged from 0–7 , with ≥4 indicating positive attitudes . Climate Change Mitigation Practices Participants were asked about 13 practice items , divided into: Individual-level behaviors (8 items): actions such as energy and water conservation, recycling, clean cookstove use, and low-carbon transport. Institutional-level behaviors (5 items): facility-based practices such as reducing medical waste, switching off unused equipment, and promoting sustainability in meetings. “Yes/No” items were scored 1 for “Yes”; frequency items (“often/always”) were also scored 1. The composite practice score ranged 0–13 , with higher scores reflecting better climate mitigation practices . Sub-scores for individual and institutional practices were analyzed separately. Statistical analysis All analyses were conducted in RStudio v4.3.1. Descriptive statistics were used to summarize participant characteristics. Continuous variables were presented as means and standard deviations (SD), and categorical variables as frequencies and percentages. Composite KAP scores were calculated by summing responses, converting total scores to percentages, and classifying participants according to Bloom’s taxonomy, as used in prior KAP research [81, 82]. That is, scores >60% were labeled “Good” or “Positive,” while scores ≤60% were considered “Poor” or “Negative.” Geospatial data visualizing facility locations and participant distributions across Ada East were generated using ArcGIS Online v3.2. Logistic regression was used to identify covariates associated with “Good” knowledge, “Positive” attitudes, and “Good” practices. Covariates included sociodemographic factors (e.g., sex, age), occupational characteristics (e.g., facility type, clinical role, years of experience), training history (e.g., training source, content), and information access (e.g., source type, frequency). Univariate models yielded crude odds ratios (ORs) with 95% Cis. These were followed by a fully adjusted multivariable logistic regression —adjusting for all theoretically relevant variables shown in Table 1— which yielded adjusted odds ratios (AORs) with 95% CIs. Covariates with < 5% prevalence or near-zero variance were excluded from modeling. Participants with missing covariate data were omitted list-wise in subsequent regression analyses. Statistical significance was set at α = 0.05, using two-sided Wald chi-square tests. Qualitative Part Focus Group Discussion A semi-structured focus group discussion guide was developed to explore FHWs’ KAP regarding zoonotic diseases—particularly Ebola Virus Disease—and their perceived links with climate change. The guide covered two domains: Zoonotic disease knowledge and preparedness – beliefs, misconceptions, and management practices. Climate change and health – awareness, perceived impacts, and mitigation or adaptation strategies. Questions were open-ended, with targeted probes to encourage discussion and clarify survey findings. Training for Focus Group Discussion To capture a broad range of frontline perspectives, we employed a maximum-variation purposive sampling approach during the same five-day period as the survey. Survey responses were reviewed in real time to identify interested FHWs and ensure diversity across occupational roles, facility types, sex, experience levels, and training backgrounds. Sampling continued until the target of 7 to 10 participants was reached. Participants in the focus group discussion were either newly recruited from the 18 study sites or selected from among survey respondents. Ultimately, we enrolled nine FHWs (2 men, 7 women), purposively selected to deliberately yield a diverse sample for the focus group discussion on climate change and zoonotic disease. Focus Group Discussion Data Collection The focus group discussion was conducted in a private room at Ada East District Hospital to ensure comfort and confidentiality. The session was facilitated in English and Dangme by a trained moderator, supported by a note-taker. Participants were assigned numeric identifiers (P1–P9) for anonymity. The moderator reviewed the study purpose, ground rules, and obtained verbal group consent for recording. The session lasted ~100 minutes , with member-checking used throughout to confirm interpretations. Audio was transcribed verbatim and translated into English when needed by the bilingual moderator and note-taker. All data were de-identified and securely stored by the principal investigator. Qualitative Data Analysis A thematic analysis guided by grounded theory principles was used. Three researchers (one senior, two trained assistants) independently reviewed the transcript and developed a hybrid codebook , combining deductive codes from the guide and inductive codes emerging from the data. Line-by-line coding was performed with constant comparison to ensure consistency. The team met to reconcile differences and refine the codebook. Themes were formed by clustering related codes and were supported by representative quotations and counterexamples to capture variation in perspectives. Research Ethics The study received ethical approval from both the Ghana Health Service Ethical Review Committee (protocol GHS‑ERC 024/08/24) and the Pennsylvania State University Institutional Review Board (STUDY00025492). Written authorization to conduct the study was also obtained from the administrative leadership of all eighteen participating health facilities. Then, all survey data were collected anonymously, with no direct identifiers included in the analytic dataset. Participation was voluntary, and individuals were assured that declining or withdrawing from the study would have no impact on their employment or benefits. Written informed consent was obtained from all participants before enrollment. All participants were provided 160 Ghanian Cedi (13.39 USD) upon completion of the survey. Only individuals who expressed interest in the focus group discussion voluntarily provided their name and phone number for recontact. This identifying information was stored in a separate, encrypted, password-protected file accessible only to the principal investigator and was not linked to survey responses. Participants in the focus group discussion signed a separate consent form specific to the qualitative component. Upon completion of the focus group discussion, all participants were provided with 160 Ghanaian cedis (13.39 USD). Results Study demographics A total of 250 FHWs (73.2% women) in Ada East completed the survey (Table 1). The mean age was 32.8 years (SD = 6.4). Most participants were stationed at either district or regional hospitals (46.4%) or health centers (44.8%), while 8.8% worked in Community-based Health Planning and Services compounds. Nurses comprised the largest cadre (61.2%). Respondents averaged 6.0 years (SD = 5.6) of professional experience. Nearly all reported active involvement in direct clinical care and preventive services. The most frequently covered diseases included COVID-19, monkeypox, rabies, and Ebola virus disease. Digital platforms were the predominant source of professional information, accessed by 96.4% for zoonoses and 95.2% for climate-related health topics. Conventional media such as television and radio remained common, while public channels were cited less often. The majority of FHWs reported engaging with climate change information only occasionally or not at all. Table 1: Sociodemographic, professional, training, and information-access characteristics of study participants (N=250), frontline healthcare workers (FHWs). Characteristic N (%) Age (in years) 20 - 29 84 (33.6) 30 - 34 83 (33.2) 35-37 83 (32.2) Sex - Women 183 (73.2) Education Level SSS/SHS/Technical 11 (4.4) Higher education 239 (95.6) Healthcare Facility Type CHPS Compound 22 (8.8) District/Regional Hospital 116 (46.4) Health Center 112 (44.8) Occupational Category Nurse 153 (61.2) Midwives 45 (18.0) Other Clinical Staff 41 (16.4) Administrative and Support Staff 11 (4.4) Activities Performed in Job Role Provision of clinical services 245 (98.0) Clinical support group 93 (37.2) Preventative health services 229 (91.6) Other 1 (0.4) Years of Experience in Current Job > 5 years 94 (37.6) ≤ 5 years 156 (62.4) Diagnoses and Treats Patients with Infectious Diseases ** 156 (63.4) Received Infectious Diseases Training * 175 (70.3) Who Provided Infectious Diseases Training Experts from the Respondents’ Health Facility 121 (48.4) Experts from the Ministry and the Government Health Authorities 104 (41.6) Experts from International NGOs 27 (10.8) Academic or School-Based Training 8 (3.2) No Training Received / Other 75 (30.0) What Infectious Diseases Training Provide COVID-19 149 (59.6) Ebola virus disease 64 (25.6) Marburg virus disease 24 (9.6) Human monkeypox virus 74 (29.6) Rabies 72 (28.8) Anthrax 14 (5.6) Cholera 45 (18.0) Tuberculosis 14 (5.6) Other 13 (5.2) Current Source of Zoonotic Disease Information Electronic media 241 (96.4) Conventional media 155 (62.0) Public media 94 (37.6) Current Source of Climate Change Information Electronic media 238 (95.2) Conventional media 163 (65.2) Public media 93 (33.2) Frequency of Engagement with Climate Change Information Always or often 26 (10.4) Sometimes, rarely, or never 224 (89.6) Notes: Missing variables: *n=1 and **n=4; multi-response items (e.g., training topics and information sources) are not mutually exclusive and may exceed 100%. Abbreviations: CHPS = Community-based Health Planning and Services; SSS/SHS = senior secondary school / technical school (e.g., secondary); NGO = non-governmental organizatio Knowledge of climate change and its health impacts Most FHWs (83.2%) met the ≥60% threshold for “Good” climate change and health knowledge (Supplementary Table 1). Participants correctly identified major biophysical indicators of climate change, including changes in temperature and rainfall (89.2%), increased frequency of droughts and floods (94.0%), and rising sea levels and coastal erosion (74.4%). Key drivers such as deforestation (96.0%), industrial emissions (90.8%), atmospheric pollution from open waste burning (96.4%), and carbon dioxide emissions (86.0%) were widely recognized. However, fewer respondents linked agriculture (56.0%) and methane from livestock (40.8%) to climate change. In the health impacts domain, most FHWs associated climate change with heat-related (91.6%) and air-quality-related illnesses (94.4%). Recognition of indirect impacts was lower: malnutrition (54.8%), mental health conditions (28.0%), and social conflict (26.0%). Awareness of vulnerable populations was also limited, with fewer than half identifying children (46.4%), older adults (44.4%), or women (11.6%) as especially susceptible to climate-related health risks. Nearly all respondents (96.4%) agreed that climate change increases infectious disease outbreaks, and 98.8% linked it to illness in both humans and livestock. Most participants understood that rising temperatures and shifting rainfall patterns expand vector habitats (93.2%), and many anticipated increased EVD outbreak risk (81.6%) and emergence in new locations (83.2%). Attitudes toward climate change Most respondents expressed strong pro-mitigation attitudes, with 86.8% (n = 217) meeting the ≥60% threshold for a “Positive” climate change attitude (Supplementary Table 2). Support for climate change mitigation was nearly universal; 94.4% agreed it is essential for controlling emerging and re-emerging zoonoses. Most respondents assigned primary responsibility to the Ministry of Health (84.8%) and private citizens (79.6%). Fewer attributed responsibility to international actors such as industrialized nations (57.6%) and donors or NGOs (59.6%). A majority (72.8%) acknowledged that healthcare systems contribute to climate change. Fatalistic beliefs were uncommon—only 17.2% agreed that climate-related disasters are unavoidable “acts of God.” Practices regarding climate change mitigation Overall engagement in climate change mitigation practices was moderate, with 62.4% (n = 156) classified as having “Good” climate change mitigation practices (Supplementary Table 3). Individual-level practices were more commonly adopted than institutional ones. Nearly 80% (79.6%) met the threshold for “Good” individual practices (mean = 6.39, SD = 1.02). Routine behaviors included switching off lights and appliances (92.0%), using energy-efficient bulbs (85.2%), and adopting low-energy devices (82.0%). Water conservation (76.4%) and clean cookstove use (89.2%) were also widely reported. Fewer respondents reported harvesting rainwater (50.0%), practicing waste sorting (45.6%), or using low-carbon transport (59.2%). Institutional-level practices were limited. Only 11.2% (n = 28) achieved “Good” institutional practice scores. While most reported turning off unused digital (64.4%) and clinical equipment (61.6%), a minority reported minimizing single-use plastics (15.2%) or integrating climate mitigation into staff meetings or training (4.4%). Factors associated with climate-change knowledge, attitudes, and practices Most frontline healthcare workers demonstrated good knowledge and positive attitudes toward climate change and health across sociodemographic, professional, and training categories. Slight variations were observed by age, facility type, and prior infectious-disease training, but overall awareness and attitudes remained consistently high across all groups (Table 2). Table 2. Proportions of good climate change and health knowledge among frontline healthcare workers (N = 250). Predictor Level Knowledge (n, %) Attitudes (n, %) Attitudes (n, %) Poor Good Poor Good Negative Positive Sociodemographic Characteristics Age (in years) 20-29 11 (13.1) 73 (86.9) 11 (13.1) 73 (86.9) 35 (41.7) 49 (58.3) 30-34 15 (18.1) 68 (81.9) 11 (13.1) 72 (86.7) 32 (38.6) 51 (61.4) 35-57 16 (19.3) 67 (80.7) 11 (13.1) 72 (86.7) 27 (32.5) 56 (67.5) Sex Man 12 (17.9) 55 (82.1) 6 (9.0) 61 (91.0) 24 (35.8) 43 (64.2) Woman 30 (16.4) 153 (83.6) 27 (14.8) 156 (85.2) 70 (38.3) 113 (61.7) Professional Characteristics Healthcare Facility Type CHPS Compound 2 (9.1) 20 (90.9) 2 (9.1) 20 (90.9) 5 (22.7) 17 (77.3) District/Regional Hospital 21 (18.1) 95 (81.9) 18 (15.5) 98 (84.5) 56 (48.3) 60 (51.7) Health Center 19 (17.0) 93 (83.0) 13 (11.6) 99 (88.4) 33 (29.5) 79 (70.5) Occupational Category Nurse 29 (18.3) 125 (81.7) 19 (12.4) 134 (87.6) 56 (36.6) 97 (63.4) Midwives 9 (20.0) 36 (80.0) 8 (17.8) 37 (82.2) 19 (42.2) 26 (57.8) Other Clinical Staff 4 (9.8) 37 (90.2) 4 (9.8) 37 (90.2) 15 (36.6) 26 (63.4) Experience in Current Role > 5 years 20 (21.3) 74 (78.7) 11 (11.7) 83 (88.3) 34 (36.2) 60 (63.8) ≤ 5 years 22 (14.1) 134 (85.9) 22 (14.1) 134 (85.9) 60 (38.5) 96 (61.5) Diagnoses/Treats Patients w/ IDs Yes 26 (16.7) 130 (83.3) 19 (12.2) 137 (87.8) 55 (35.3) 101 (64.7) No 15 (16.7) 75 (83.3) 14 (15.6) 76 (84.4) 35 (38.9) 55 (61.1) Training Characteristics Received ID Training Yes 31 (17.7) 144 (82.3) 21 (12.0) 154 (88.0) 64 (36.6) 111 (63.4) No 11 (14.9) 63 (85.1) 12 (16.2) 62 (83.8) 29 (39.2) 45 (60.8) Experts Who Delivered ID Training No - Respondents’ Health Facility 14 (10.9) 115 (89.1) 12 (9.3) 117 (90.7) 44 (34.2) 85 (65.9) Yes - Respondents’ Health Facility 28 (23.1) 93 (76.9) 21 (17.4) 100 (82.6) 50 (41.3) 71 (58.7) No - Ministry/Government Health Authorities 28 (19.2) 118 (80.8) 26 (17.8) 120 (82.2) 54 (37.0) 92 (63.0) Yes - Ministry/Government Health Authorities 14 (13.5) 90 (86.5) 7 (6.7) 97 (93.3) 40 (38.5) 64 (61.5) No - International NGOs 38 (17.0) 185 (83.0) 31 (13.9) 192 (86.1) 88 (39.5) 135 (60.5) Yes - International NGOs 4 (14.8) 23 (85.2) 2 (7.4) 25 (92.6) 6 (22.2) 21 (77.8) What ID Training Was Delivered No - COVID-19 11 (10.9) 90 (89.1) 12 (11.9) 89 (88.1) 42 (41.6) 59 (58.4) Yes - COVID-19 31 (20.8) 118 (79.2) 21 (14.1) 128 (85.9) 52 (34.9) 97 (65.1) No - Ebola virus disease 26 (14.0) 160 (86.0) 23 (12.4) 163 (87.6) 74 (39.8) 112 (60.2) Yes - Ebola virus disease 16 (25.0) 48 (75.0) 10 (15.6) 54 (84.4) 20 (31.2) 44 (68.8) No - Human monkeypox virus 20 (11.4) 156 (88.6) 20 (11.4) 156 (88.6) 62 (35.2) 114 (64.8) Yes - Human monkeypox virus 22 (29.7) 52 (70.3) 13 (17.6) 61 (82.4) 32 (43.2) 42 (56.8) No - Rabies 23 (12.9) 155 (87.1) 22 (12.4) 156 (87.6) 64 (36.0) 114 (64.0) Yes - Rabies 19 (26.4) 53 (73.6) 11 (15.3) 61 (84.7) 30 (41.7) 42 (58.3) Information Access Characteristics Current Source of Zoonotic Disease Information No - Conventional media 24 (25.3) 71 (74.7) 15 (15.8) 80 (84.2) 41 (43.2) 54 (56.8) Yes - Conventional media 18 (11.6) 137 (88.4) 18 (11.6) 137 (88.4) 53 (34.2) 102 (65.8) No - Public media 32 (20.5) 124 (79.5) 22 (14.1) 134 (85.9) 64 (41.0) 92 (59.0) Yes - Public Media 10 (10.6) 84 (89.4) 11 (11.7) 83 (88.3) 30 (31.9) 64 (68.1) Current Source of Climate Change Information No - Conventional media 25 (28.7) 62 (71.3) 19 (21.8) 68 (78.2) 39 (44.8) 48 (55.2) Yes - Conventional media 17 (10.4) 146 (89.6) 14 (8.6) 149 (91.4) 55 (33.7) 108 (66.3) No - Public media 35 (21.0) 132 (79.0) 24 (14.4) 143 (85.6) 67 (40.1) 100 (59.9) Yes - Public Media 7 (8.4) 76 (91.6) 9 (10.8) 74 (89.2) 27 (32.5) 56 (67.5) Frequency of Climate Change Information Always or Often 3 (11.5) 23 (88.5) 2 (7.7) 24 (92.3) 7 (26.9) 19 (73.1) Sometimes, Rarely, or Never 39 (17.4) 185 (82.6) 31 (13.8) 193 (86.2) 87 (38.8) 137 (61.2) Notes: CHPS = Community-based Health Planning and Services; ID infectious diseases In the adjusted multivariate logistic regression, knowledge, professional role, and training source were the only significant covariates (Table 3). Compared with nurses, other clinical staff (e.g., physicians, pharmacists, and laboratory technologists) had higher odds of good knowledge. Compared with no monkeypox training, receipt of monkeypox training was associated with lower odds of good knowledge. Accessing climate change information via conventional media was associated with higher odds of positive attitudes than no conventional media access. For practices, institutional settings, and training providers emerged as key covariates. Relative to Community-based Health Planning and Services compounds, FHWs based at district or regional hospitals were associated with lower odds of good practices. Compared with no training, participation in international non-governmental organization-led training was associated with higher odds of good practices, whereas Ministry of Health–led training was associated with lower. Receipt of monkeypox was also associated with lower odds of good practices versus no monkeypox training. There were no significant associations in crude logistic regression (Supplementary table 4). Table 3. Predictors of good climate change attitudes among frontline healthcare workers (N = 250). Logistic regression was presented as odds ratios (ORs) with 95% confidence intervals (95% CI), adjusted (adj) for all theoretically relevant variables shown in Table 1 Predictor Level Knowledge Attitudes Practices adjOR 95% CI adjOR 95% CI adjOR 95% CI Sociodemographic Characteristics Age (in years) 20-29 1.00 1.00 1.00 30-34 0.66 0.24-1.82 0.76 0.26-2.16 1.11 0.51-2.44 35-57 0.80 0.22-3.04 0.66 0.16-2.73 1.41 0.53-3.88 Sex Man 1.00 1.00 1.00 Woman 1.65 0.56-4.70 0.40 0.08-1.50 0.57 0.24-1.30 Professional Characteristics Healthcare Facility Type CHPS Compound 1.00 1.00 1.00 District/Regional Hospital 0.70 0.09-3.83 0.69 0.08-3.62 0.18 0.05-0.61 Health Center 0.43 0.06-1.96 0.98 0.13-4.63 0.89 0.25-2.81 Occupational Category Nurse 1.00 1.00 1.00 Midwives 1.00 0.34-3.14 0.87 0.29-2.84 1.39 0.58-3.44 Other Clinical Staff 4.52 1.12-22.76 0.87 0.21-4.24 1.11 0.42-3.00 Experience in Current Role > 5 years 1.00 1.00 1.00 ≤ 5 years 0.98 0.32-2.93 0.40 0.10-1.47 1.22 0.52-2.87 Diagnoses/Treats Patients w/ IDs Yes 1.00 1.00 1.00 No 0.70 0.27-1.79 0.76 0.29-2.03 0.63 0.31-1.26 Training Characteristics Received ID Training Yes 1.00 1.00 1.00 No 0.58 0.19-1.72 0.69 0.23-2.04 0.70 0.31-1.57 Experts Who Delivered ID Training No - Respondents’ Health Facility 1.00 1.00 1.00 Yes - Respondents’ Health Facility 0.55 0.19-1.53 0.65 0.23-1.91 0.83 0.39-1.74 No - Ministry/Government Health Authorities 1.00 1.00 1.00 Yes - Ministry/Government Health Authorities 1.44 0.58-3.72 2.27 0.79-7.34 0.44 0.21-0.91 No - International NGOs 1.00 1.00 1.00 Yes - International NGOs 1.33 0.38-5.76 2.16 0.46-16.71 4.61 1.44-18.47 What ID Training Was Delivered No - COVID-19 1.00 1.00 1.00 Yes - COVID-19 0.62 0.22-1.72 0.63 0.21-1.84 2.10 0.97-4.65 No - Ebola virus disease 1.00 1.00 1.00 Yes - Ebola virus disease 0.91 0.30-2.83 0.80 0.23-2.79 2.44 0.95-6.58 No - Human monkeypox virus 1.00 1.00 1.00 Yes - Human monkeypox virus 0.24 0.08-0.64 0.39 0.12-1.22 0.39 0.17-0.90 No - Rabies 1.00 1.00 1.00 Yes - Rabies 0.70 0.24-2.03 1.25 0.37-4.50 0.50 0.20-1.25 Information Access Characteristics Current Source of Zoonotic Disease Information No - Conventional media 1.00 1.00 1.00 Yes - Conventional media 1.68 0.53-5.31 0.35 0.08-1.36 1.58 0.64-3.86 No - Public media 1.00 1.00 1.00 Yes - Public Media 1.28 0.35-5.06 1.29 0.28-6.87 1.63 0.52-5.39 Current Source of Climate Change Information No - Conventional media 1.00 1.00 1.00 Yes - Conventional media 2.04 0.67-6.57 7.86 1.94-37.37 1.10 0.45-2.73 No - Public media 1.00 1.00 1.00 Yes - Public Media 2.41 0.55-11.14 0.58 0.09-3.18 0.73 0.21-2.50 Frequency of Climate Change Information Always or often 1.00 1.00 1.00 Sometimes, Rarely, or Never 1.16 0.22-4.52 0.72 0.10-3.19 0.62 0.19-1.76 Abbreviations: NGO = non-governmental organization; ID Infectious Diseases Qualitative Results The focus group discussion involved nine FHWs —seven women and two men— ranging in age from 28 to 56 years. While all nine attended the FGD, only eight actively conversed during the discussion (Table S1). Educational backgrounds varied: two participants held upper-secondary diplomas, six held Bachelor of Science degrees, and one held a master’s degree. Participants also represented a range of occupational cadres, including one doctor, one pharmacist, three nurses, three midwives, and one laboratory technician. Their specific professional roles included Senior Medical Officer, Head of Pharmacy, Senior Nursing Officer, Neonatal Intensive Care Unit nurse, inpatient department nurse, maternity ward midwife, two Senior Staff Midwives, and Senior Medical Laboratory Technician, respectively. Time employed at their health facility ranged from nine months to eighteen years. Primary themes from the focus group discussion reflected how frontline workers interpret and understand climate change and its link to zoonotic disease (Supplementary Table 5). Specifically, participants emphasized their lived experiences with shifting weather patterns and related health impacts, and recognized links between environmental change and zoonotic risk. They highlighted community beliefs and economic pressures that delay care-seeking. FHWs also identified institutional gaps in preparedness and collectively called for stronger multisectoral collaboration, infrastructure investment, and follow-through on climate–health policies. FHWs’ understanding of climate change in the local context FHWs described climate change as an observable shift in environmental conditions, particularly weather patterns. In defining climate change, most participants referred to their lived experiences with rising temperatures, unpredictable rainfall, and deviations from expected seasonal norms. For example, many participants often described climate change as a disruption in once-predictable seasonal patterns. One respondent noted: “Climate change might be either excessive or complete change in what is expected. For example, I'm expecting a Harmattan to start somewhere in December, ending in January. I'm now feeling some funny things in my nose, like we are facing harmattan.” (Participant #1, Male, 56 years, Pharmacist). Meanwhile, others highlighted the rising heat as one of the most tangible indicators of climate change, with the same respondent stating, “Change in weather. Yes. Like currently as we are fanning ourselves, the weather is very hot, so there is a change in the weather” (Participant #1, Male, 56 years, Pharmacist). In addition to temperature and seasonal shifts, participants also emphasized changes in rainfall patterns as an indicator of climate change : “Maybe they are expecting this month to be rainy season, but because of climate change, they will see the sun” (Participant #5, Female, 51 years, Midwife). For one participant, climate change was understood as a broader national or even regional phenomenon that manifests differently depending on location. They thoughtfully remarked: “I was expecting to hear a question like, is the climate in Ada different from maybe Accra, or maybe Tema, or Ahafo, or somewhere else? … There are times where it could be raining heavily in Accra, but here in Ada, we are still in the heat. So, … currently our climate has changed to the extent that one state... can be experiencing a cool weather, the other can be experiencing a very hot weather.” (Participant #7, Female, 28 years, Midwife). Furthermore, several respondents linked changing temperatures, heavy rains, and the Harmattan season with increases in specific health conditions. For example, many participants shared that they observed an increase in sickle cell crises during periods of colder weather and rainfall, with one participant stating, “[Patients] with sickle cell crisis, because of the coldness of the weather… Meanwhile, they're supposed to warm themselves up. But because of that, they also face that [pain] crisis during the rainy season.” (Participant #6, Female, 36 years, Midwife). Another participant elaborated on how the prevalence of asthma cases seemed to increase with the onset of the Harmattan season: “The asthma clients visit us more, because most of them get the attacks during this weather [Harmattan season]. So, when it becomes warm, they come a lot. They get triggered.” (Participant #7, Female, 28 years, Midwife). A similar correlation between climate variability and health was observed among children, with participants noting increased upper respiratory and skin-related reactions during periods of rapid weather change: “Most of them [children], they come with cold, catarrh, headache, running nose, and cough. They normally come with such conditions when the weather changes… And then heat rash as well” (Participant #9, Female, 43 years, Nurse). Malaria was also commonly mentioned, with more than half of participants highlighting the role of rainfall and stagnant water in creating mosquito breeding environments, with one participant commenting, “During the rainy season and when there are floods and stagnant water, it breeds mosquitoes” (Participant #3, Female, 32 years, Laboratory Technician). Together, these narratives frame climate change and its impacts on health as a daily reality for FHWs. Perceived link between climate change and zoonotic disease transmission When asked directly about the relationship between climate change and zoonotic disease transmission, some participants pointed to biological and environmental mechanisms they believed could heighten outbreak risk. For instance, one participant explained, “Increasing temperature … aids viruses, bacteria, and the likes to also multiply faster and are more active. There's a possibility of increased variance of those microorganisms. We expect Ebola diseases to be very serious because of climate change... and transmission very fast because of climate change.” (Participant #1, Male, 56 years, Pharmacist) This participant later goes on to emphasize habitat destruction, particularly deforestation and seasonal bushfires, as factors that lead to more frequent interactions between local native populations and animals: “Deforestation and dehabitation, we [humans] tend to deprive these animals from their natural habitat. So, they rather get closer to humans for shelter and for protection. And by that, they end up getting closer to us and causing zoonotic diseases to spread… I know snakes. Normally in the hot seasons, they … come to hide in our rooms and near human settlement, where they can take shelter, because there's a lot of bush fires… their cover is naturally exposed, so they have nowhere to hide, and they find themselves living amongst us.” (Participant #1, Male, 56 years, Pharmacist) This sentiment was followed by a few participants discussing the practices of the local Fulanese population, particularly regarding the hunting and consumption of wild animals such as monkeys. One participant remarked that wild animals “won’t dare” come near town because the Fulanese locals “will kill them before they even come.” (Participant #6, Female, 36 years, Midwife). Another participant added, “They [Fulanese natives] take them [wild animals] around to eat. So they [bushmeat] are all around,” reflecting perceptions of increased human–animal interaction driven by both cultural practices and habitat changes. Lastly, one participant suggested that extreme heat combined with overcrowded public spaces, could facilitate the transmission of infectious diseases like Ebola — especially in transport settings where bodily contact is common: “So in a hot season like this, when you sweat a lot and you sit close… especially in the trotros and the taxi, before you can move your body, somebody has already pasted their whole sweat on you. So it will increase the spread of Ebola in particular.” (Participant #7, Female, 28 years, Midwife). FHW accounts converge on three perceived mechanisms linking climate change and zoonotic diseases: human-induced environmental change, cultural practices, and dense urban living. FHWs' observations of sociocultural and economic drivers of delayed Zoonotic disease care Participants described a range of culturally embedded beliefs and practices that shape how community members respond to illnesses, like zoonotic diseases. These beliefs were seen too often contribute to delayed care-seeking behavior, with implications for both individual and public health. First, many FHW participants described spiritual or religious interpretations of zoonotic disease-related illness among community members. One participant explained, “Some also believe that besides sicknesses, you have to consult the oracles. So, they go and consult the oracle to find out whether it is the cause of you having offended somebody or it is a curse that has been put on you” (Participant #1, Male, 56 years, Pharmacist). Another participant expanded on this idea of prayer camps as the first point of contact for individuals experiencing potentially serious or infectious conditions: "Because they think it's spiritual, they simply go to a prayer camp before they'll think about coming to the hospital" (Participant #2, Female, 32 years, Nurse). Another adds, "In our setting, they believe much in this. So, everything, they will go to the prayer camp first before they'll come to the hospital. And most of the time, before they'll come to the hospital, their condition has gotten worse... when the prophetess or the prophet, they realize the person is about to die, they will push you to the hospital because when you die in their premises, it will spoil their business.” (Participant #4, Female, 39 years, Nurse) Others explained that when community members did eventually arrive at healthcare facilities, they sometimes imposed restrictions on the type of healthcare, as dictated by religious leaders: "They do come with their terms and conditions. The spiritual man says, you shouldn't inject me or I should come for IV fluids and come back to the camp." (Participant #9, Female, 43 years, Nurse). In addition to spiritual healing, participants described widespread use of herbal remedies and over-the-counter medications as initial ‘treatments’ for zoonotic diseases before seeking formal care, with one participant noting, “Sometimes they try with the herbal medicines. If it doesn't work, then they will come" (Participant #6, Female, 36 years, Midwife). Another notes, "Some also choose to medicate themselves. They go to the pharmacies, the chemical shops, and then they buy medications they feel would solve their problem for them. So, it worsens and then they come to the hospital" (Participant #7, Female, 28 years, Midwife). All focus group participants agreed that this combination of spiritual healing and self-medication was a common practice. FHWs further emphasized that these behaviors often contributed to delayed care, with implications for zoonotic disease spread : "They will go to the prayer camp, and before the person will be rushed here, she has already infected those at the prayer camp… It will spread to the community." (Participant # 4). One participant responds, “It will spread like wildfire… we are in trouble” (Participant #7, Female, 28 years, Midwife). Respondents also noted that family expectations and media messaging —particularly radio broadcasts— influenced care-seeking pathways. One participant explained the hierarchical order that community members follow when they suspect a zoonotic disease: “Prophets number one, family members two. I think health workers would be the last because even the learned ones are influenced by family members to go there [prayer camps]. Maybe if you don't go, they will disown you. So, prophets number one, family members number two, maybe the radio number three, and then health workers would be the last.” (Participant #7, Female, 28 years, Midwife). FGD Participant #9 expands on this sentiment and states: “We have a local radio station, Radio Ada. They have specific days that they do programs that they speak their local dialect, and then they educate them.” FHW responses highlight the role of the radio as a tool for community health education. In discussing zoonotic disease detection and response within their practice, participants further described how community members often hesitated to report sick livestock due to economic concerns and limited awareness. As focus group discussion Participant #7 explained, “They will lose revenue… Maybe they lack the knowledge about the fact that they have to report such things to the hospital. Because if my animal is sick, why should I come and tell the healthcare worker that my animal is sick?” Another participant added, “ I think those who are learned will rather go to the veterinary.” (Participant #4, Female, 39 years, Nurse). Participant #1 further noted, “The moment they report a sick animal to the facilities, you might tell them to quarantine it or kill them. And that will end up they losing revenue. Most of the meats we buy in the market are not certified…They buy the cattle from the Fulanese and straight to the market. And we expect that before an animal is slaughtered, it has to be certified that it is healthy for human consumption. Such practices we see in the big cities and some area, but not in the country globally.” (Participant #1, Male, 56 years, Pharmacist) These insights reflect a broader perception among FHWs that low awareness and economic concerns among community members impacted their reporting of zoonotic diseases, particularly in areas where livestock trade occurs without veterinary oversight. Institutional gaps in preparedness for climate-driven zoonotic threats A recurring theme raised by FHWs was the reactive nature of zoonotic disease response within their current health facilities. Participants emphasized that preparedness measures —such as PPE usage and isolation protocols— were rarely implemented until an outbreak had already been declared. One participant explained: "We wear PPEs only when we hear of an outbreak, and we dress like we are living on the moon… Yeah, that is when the alert comes. If we don't get any alert from anywhere, it might be very difficult. Because now we know Mpox … We know COVID-19, the signs and symptoms we must expect. But if some of these zoonotic diseases, that its alert has not been communicated from higher centers, most of our hospitals will miss the diagnosis." (FGD Participant #1, Male, 56 years, Pharmacist) FHWs stressed that in emergency cases, a lack of early warning systems or accessible protective equipment often placed them at personal risk: "The person is rushed in, so before you even get to know that this is what is happening to the person, you've already gotten infected… Yeah, because there's no PPEs around … Because when the person comes in, it's an emergency. The only thing you know is putting on your gloves for you to examine the person, and before later, they will do this test... When the result comes out positive, and by then, most of the health professionals that come in contact with the person are already gotten infected." (Participant #3, Female, 32 years, Laboratory Technician) All participants also described a general lack of institutional guidelines for managing zoonotic disease cases. One participant noted, "I think it's when there is an outbreak, that is when we follow the guidelines. But as of now, that we are all sitting here, there is actually no guidelines for anyone." (Participant #7, Female, 28 years, Midwife). Even for more locally recognized zoonotic threats like rabies, Marburg, or Ebola, participants reported limited awareness of existing protocols, with one participant stating, “When it comes to rabies, we don't have protocols that we follow but we a [have] treatment. So, I don't know of any of them… No, I'm not aware of that [protocols for Marburg or Ebola].” (Participant #6, Female, 36 years, Midwife) Furthermore, respondents described minimal access to ongoing training. One participant mentioned that the only recent opportunity to refer their knowledge had been through informal clinical meetings, which had not occurred in a long time. This point was elaborated on by another participant, “ Training, workshops. Because I don't remember the last time there was any workshop in this country to that effect, even in Ada. You know, nursing is dynamic… You get to know what next step to take or what you should expect if you get a case like this… You can attest that most of us, it's been a very long time we even enter our books, open the books to look at what is going on. So, some of these things it helps. It freshens your memory. You might have forgotten about something, but with this, it [protocols would] freshens your memory.” (Participant #9, Female, 43 years, Nurse) In the absence of formal systems, participants relied heavily on informal communication networks to stay informed about zoonotic outbreaks and climate-related updates. These included personal Google searches, professional WhatsApp groups, and information shared by family members. As one participant explained, “Now Google is closer to us, so on our phones, you just speak into Google, and all the information, the good, the bad, and the ugly will get to you. Better still, you want to look at Google Scholar… Where there are intellectual rights of people that have conducted researches and studies that you can read… Because for them, you know, it has been peer reviewed. No one head wrote it, so it has gone through a lot of corrections and a lot of editing so that the truth actually stands out.” (Participant #1, Male, 56 years, Pharmacist) Another respondent added, “ Sometimes, they post this [information] on our [WhatsApp] page, there is an update… Our family members keep calling, so they will update us. " (FGD Participant #6, Female, 36 years, Midwife). One respondent stated, “Ask AI” (Participant #7, Female, 28 years, Midwife). FHWs expressed a strong desire for more structured and formal training workshops, ideally organized by the Ministry of Health (MOH) or other governmental bodies. These workshops were viewed as more trustworthy and effective than piecemeal updates: “[We prefer] Workshop, because the researcher or the person who is presenting has done his research. He has done his findings. And the person also is an expert in what he or she is talking about.” (Participant #2, Female, 32 years, Nurse). In terms of their own practices, participants described small-scale institutional actions to mitigate environmental risks driving zoonotic outbreaks, such as conserving electricity, turning off unused appliances, or switching to energy-saving bulbs: "When we come, let's say the lights. The lights, when they are not in use, we put them off to preserve energy. And the electrical appliances… we put them off to preserve energy." (Participant #4, Female, 39 years, Nurse). Another respondent notes, "We try and light the energy-saving bulbs. Fridges and other things, we buy the energy-saving ones so that we can save energy" (Participant #5, Female, 51 years, Midwife). They also shared their vision for broader community education on the link between climate change and zoonoses: “Bats, yes. They should desist from killing such animals or even any sick animal around them. They should desist from killing and bringing it to the market to sell them. Secondly, we will talk about the fact that if there is any sick person in the community, they shouldn't treat themselves. They should come to the facility for health care. The third thing would be the mode of transmission. Body fluids, they should wash their hands often, keep their environment clean, and all these things. And then lastly, if there is even a death in the community, they should bring their body to the health facility because they do not know exactly what killed that particular person.” (Participant #7, Female, 28 years, Midwife) These comments reflect FHWs’ emphasis on the importance of discouraging bushmeat consumption, promoting proper hygiene, and encouraging timely reporting of unexplained illnesses or deaths within the community. FHWs’ perceived stakeholder roles and call for action in addressing the climate-zoonosis nexus Participants widely agreed that addressing the dual impact of climate change and zoonotic disease requires multisectoral collaboration, particularly between meteorological agencies, the Ministry of Environment, Science and Technology, and health authorities. One participant suggested: “Inter-sectoral collaboration, where governments would coordinate between the Ministry of Environment, Science and Technology… so that we can be informed that instead of expecting rain, we should expect very dry seasonal conditions... So that at least, they say to be forewarned … about what we should expect might tell us as to what kind of [zoonotic] diseases we are about.” (Participant #1, Male, 56 years, Pharmacist) This same participant, echoing the views of others, further described FHWs as implementers of policies handed down from district or regional health directorates, noting that district directors —many of whom are public health specialists— play a strong coordinating role: “Almost all our district directors are public health specialists… When there is any outbreak, direction and guidance will certainly come from them… We will still fall on the district that will also fall on the regional health directorate for guidance and direction. We here basically are more or less like policy implementers who will implement whatever policy that comes from higher centers… In question, with this cholera outbreak, I realized that was when I had more contact with the district director than anything more. He would call me, do you have this, we are expecting this medicine to come. They will bring it today; come and receive it.” (Participant #1, Male, 56 years, Pharmacist) Governmental actors were also perceived as critical in building resilient infrastructure and protecting environmental resources to reduce future risks: “I think that the government should build a new facility for us here, a well-equipped one that, regardless of whether it's a zoonotic disease or a normal illness, you know that the people are receiving good care.” (Participant #1, Male, 56 years, Pharmacist). The role of the government was further noted on by another participant who stated, "The government should see to it that our forests are being reserved. By preventing this deforestation and waste that force the wild animals to lose their habitats." (Participant #4, Female, 39 years, Nurse). In addition to these comments, one FHW adds, “I think the previous governments wanted us to be having this planting of trees. I don't know how far that thing went, but I think it's a good idea. The planting of trees will help ease the scorching sun on our head.” (FGD Participant #7, Female, 28 years, Midwife). All FHWs in the discussion called for more infectious disease centers, quicker diagnostic access, and adequate supplies like PPE and medications —needs described as basic yet unmet: “We don't even have an isolation place… If we are able to identify an infectious disease at the district hospital, we straight away refer to a specialized center where they can handle professionally, rather than trying to manage them with the general knowledge that we have. As the pharmacist sitting here, if you ask me what are the medicines we used to mitigate the spread of Ebola, I may have to refer… Resources to manage such patients must have to come from the headquarters… PPE has to come from Central Medical Store... Per our facilities, those things were finished when we last heard of COVID.” (FGD Participant #1, Male, 56 years, Pharmacist) Others stressed the need for rapid testing, with one participant stating, “With something like Ebola, for us to diagnose it, they will say take a sample, bring it a place. We cannot do it in our facility. If we could have the places close by… it won’t take 3 days or one week for us to know because we are at risk here.” (Participant #7, Female, 28 years, Midwife). One participant captured these sentiments, voicing the concern shared by many frontline staff: "With this not prepared, not having an isolation bay, and then the way the people in the community, their attitude towards certain conditions, we are in trouble." (Participant #9, Female, 43 years, Nurse) Respondents also emphasized that FHWs themselves deserved greater recognition, protection, and compensation, particularly during zoonotic outbreaks potentially exacerbated by climate change: “We are the frontline health workers. There should be some kind of assurances that we would have, that even though you are the frontline, taking care of people, if you get infected, your medications are free, maybe you will be given this amount of money. COVID, we heard about those things, but truthfully, it didn't work. I never received any of that money.” (Participant #7, Female, 28 years, Midwife). Enthusiasm for continued engagement in research on zoonotic disease and climate change was palpable, with participants seeing research as a means to both document on-the-ground realities and inform policy. However, they also voiced a strong desire that their participation be followed by meaningful implementation. “I hope that this wouldn't be the only research that will be done, because there are a lot of diseases that are coming up. And we would like you people to know how best we know the diseases and how best we handle them, and what the government should do about it because it's these researches that informs them of our knowledge on the grounds and what is being done. So, my hope is that in future, there'll be more researches and then most important, there'll be implementation of them.” (Participant #7, Female, 28 years, Midwife). Another FHW echoed this sentiment, concluding the discussion by stating: "I hope it doesn't end here. We hope that with all that we brought out, it can be linked for something to be done because… we don't have isolation bay, we spoke of lack of gadgets to work with, we spoke of staff, and we spoke of staff welfare, and even medications itself. I don't think this should be just about coming to waste our time... Not just coming to sit us down and then go further and then off you go. It should be channeled to the right people. We want to see a change." (Participant #9, Female, 43 years, Nurse). It is clear that FHWs are calling for action, especially as it relates to diagnostics, PPE provision, staffing, and operational guidance when preparing for climate-sensitive zoonotic diseases. Discussion This mixed-methods study offers a critical district-level examinations of Ghanaian FHWs’ knowledge, attitudes, and practices (KAP) regarding the climate-zoonosis nexus. Additionally, our analysis of how frontline health workers in Ghana perceive and respond to the interconnected challenges of climate change and zoonotic diseases illustrates how climate change is understood and addressed within a health system that faces both resource constraints and increasing environmental pressures. These findings indicate strong baseline awareness among FHWs along with critical gaps in system preparedness. Addressing these challenges will require multisectoral collaboration, investments in infrastructure and diagnostics, and concrete steps to translate policy commitments into frontline practice. High experiential knowledge as an early warning resource for climate-health risks Our findings suggest that FHWs in Ada East, Ghana, are well-informed of climate change’s impacts on health, especially regarding zoonotic diseases. This high awareness positions them as “climate-health sentinels” who can provide early warnings of climate-driven zoonotic threats. Quantitatively, 95.6% of respondents correctly identified how changing climate patterns can drive infectious disease outbreaks. Many also reported climate-linked shifts in patient cases —particularly air-quality-related illnesses, heat-related conditions, and allergic reactions. This experiential, place-based knowledge is valuable as a first signal for emerging zoonotic risks. Qualitative insights reinforced these patterns and illustrated how providers mechanistically linked climate phenomena to everyday health outcomes. For example, participants described erratic rainfall leading to more stagnant water and mosquito breeding, coinciding with spikes in malaria; dry, dusty Harmattan winds aggravating respiratory illnesses like asthma; prolonged cool and wet periods triggering increases in sickle cell crises; and heat waves bringing surges in heat rashes and dehydration. Some also observed that during very hot, dry periods, wildlife encroach closer to homes (e.g., bats or snakes seeking water), increasing human-animal contact and the risk of zoonotic disease spillover. These frontline observations align with broader evidence that climate variability is amplifying health burdens and could accelerate zoonotic spillover under future warming [13, 18–24, 32, 83]. Ghana’s frontline providers are already detecting signals that may foreshadow larger public health threats, as evidenced in our findings, underscoring the value of their experiential knowledge as a complement to formal surveillance data systems [65, 66, 69–72]. Their on-the-ground observations mirror trends documented in climate-health literature and echo global calls to empower healthcare professionals as sentinels and educators at the climate-zoonosis nexus [65, 66, 69–72]. To leverage this local knowledge, health systems should establish formal channels for frontline staff to share climate-linked clinical observations [68, 71, 72]. For instance, routine debriefings or monthly meetings could be instituted for frontline staff to report any unusual case patterns following heat waves, floods, or other weather extremes. Systematically capturing these insights would strengthen surveillance and shorten the lag between the onset of zoonotic outbreaks and a public health response [66, 70]. In essence, incorporating FHWs’ experiential reports into early warning systems can enrich One Health monitoring at the grassroots level [66]. Such community-based reporting is a cornerstone of proposed One Health early warning frameworks, which emphasize that empowering local actors is essential for timely, coordinated outbreak preparedness [66, 79]. We recommend that Ghana’s health authorities pilot mechanisms to integrate frontline climate-health intelligence into district surveillance —a low-cost step that could enhance national outbreak alert systems [67, 69, 79]. Assessment of knowledge gaps through a One Health lens While Ada East FHWs readily recognized direct clinical impacts of climate change, we also found significant knowledge gaps regarding broader climate-health pathways. In particular, the understanding of the One Health dimensions was limited. Few respondents were aware of how agricultural and livestock practices contribute to climate change, despite agriculture being a primary anthropogenic driver of land-use change and greenhouse gas emissions in Ghana [38–42, 45, 51, 84]. Fewer than one-third connected climate change to psychosocial health outcomes, such as stress, anxiety, or social conflict, and recognition of especially vulnerable groups like children, older adults, or women was low despite evidence that these groups face heightened climate-related health risks [85–87]. Notably, we found that attending highly vertical, disease-focused workshops —namely, trainings on monkeypox— was associated with lower overall climate-health knowledge scores. This counterintuitive finding may suggest that siloed training programs might isolate diseases from their environmental context, leaving providers less attuned to how climate and ecological changes influence disease emergence and connect to broader One Health dimensions [74]. Addressing these identified gaps will require retooling health education toward a more holistic, One Health perspective. Educators could expand pre-service curricula and in-service training to include underrepresented climate-health topics such as agriculture-driven greenhouse gas emissions, the dynamics of wildlife-livestock-human interfaces, and the mental health implications of climate change [74, 79]. We also suggest using locally relevant, case-based teaching that explicitly links recent climatic events to changes in disease patterns; for example, analyzing how a recent flood coincided with leptospirosis clusters, a drought with anthrax events, or a heatwave with bat-human contact and Marburg risk in the district. This approach would ensure that even specialized zoonotic disease training is contextualized within the broader climatic and environmental landscape [23]. By integrating One Health concepts into training and continuous professional development, as urged by international frameworks, Ghana’s health workforce may better anticipate indirect and multi-sectoral drivers of climate-driven zoonotic outbreaks [66, 73, 79, 88–90]. From individual initiative to institutional preparedness Despite strong knowledge and positive attitudes, a clear gap remains between frontline workers’ personal climate-friendly behaviors and their institutions’ climate–zoonotic preparedness. Most respondents reported engaging in low-cost individual-level actions—such as conserving water, turning off unused equipment, or using cleaner cookstoves—yet fewer than 12% reported “Good” climate mitigation practices at the facility level. Focus group narratives further noted that frontline staff often take a reactive stance to climate-driven zoonotic threats. Essential resources —including PPE, emergency protocols, or climate-focused guidelines— typically arrive after a crisis begins rather than as preventative measures. Smaller community-based clinics (e.g., CHPS compounds) were positively associated with better climate mitigation practices, whereas larger district hospitals were less engaged in these measures. This pattern of strong individual engagement in climate mitigation but weak institutional climate-zoonotic preparedness might indicate that structural barriers are limiting the translation of frontline commitment into system-wide resilience. Closing this practice gap will require deliberate support from health authorities to climate-proof health facilities as an indirect means to reduce the risk of zoonotic disease and empower staff-led initiatives [37, 68, 72]. Investments are needed to upgrade infrastructure and operations for a climate-resilient approach to zoonotic preparedness [24, 91]. Ensuring essential medicines, vaccines, and supplies are pre-positioned in anticipation of climate-related events, rather than delivered only in emergency response, is another crucial step for zoonotic preparedness [92, 93]. Our data also underscore the importance of training and information flow in driving climate-informed zoonotic preparedness. Both quantitative and qualitative results identified training exposure as a key predictor of good climate-friendly practices. Notably, FHWs who had participated in NGO-led training workshops reported better climate-health practices than those trained through government programs. Participants explained that most official training on emerging zoonotic diseases in the backdrop of climate change is infrequent, prompting them to rely on ad-hoc sources like WhatsApp groups or personal internet searches to fill knowledge gaps. This indicates an opportunity to improve not just the content, but also the delivery of training. Instituting regular, hands-on drills and learning modules focused on climate-related health emergencies may prove beneficial. Developing these trainings in collaboration with frontline staff would ensure they are relevant to local realities, and embedding such exercises and discussions into routine continuing education would keep climate preparedness at the forefront of FHWs’ minds [24, 37, 52, 66, 69, 71, 74, 86, 93]. It would also address the anxiety FHWs voiced about being “in trouble” during a major zoonotic outbreak if left unprepared. Respondents expressed frustration that national climate-health policies and plans often do not translate into tangible support for the local staff. To remedy this, participatory governance mechanisms should be strengthened, for example, via the creation of local climate-health focal points or committees within each district where frontline workers can both receive updates on policies and feed their experiences upward [66, 67, 69, 72, 74, 93]. Regular forums for FHWs to voice needs —such as reporting PPE shortages or flagging upticks in certain illnesses that could signal zoonotic emergence— would help decision-makers allocate resources more responsively [71, 92, 93]. Socio-cultural and economic barriers to rapid outbreak response Community-level factors identified by FHWs, including economic pressures, health-seeking behaviors, and long-standing livelihood practices, seem to strongly shape how quickly climate-sensitive zoonotic threats are detected and addressed. This study highlighted that effective preparedness must therefore extend beyond health facilities into the community, since even well-trained staff and better-equipped clinics cannot overcome delays rooted in the community context. FHWs in Ada East observed that patients’ economic vulnerabilities heavily influenced their care-seeking practices. Similarly, FHWs reported that farmers also rarely report strange illnesses or deaths in their livestock, often out of fear of losing income or because there are no clear mechanisms to do so. These identified gaps signal that animal warning signs, which serve as potential precursors to human outbreaks, are frequently missed. Future research should explore how economic and food insecurity may impact both climate mitigation practices and zoonotic disease reporting. Cultural beliefs and trust in traditional medicine seem to further shape health-seeking behaviors within the community. Participants explained that sudden illness is frequently attributed to spiritual causes, prompting families to seek help first from prayer camps, faith healers, or herbalists. While these practices remain central to community life, FHWs stressed that they delay engagement with the formal health system. They warned that a fast-spreading zoonosis like Ebola could “spread like wildfire” if patients remain at home or in spiritual centers without timely diagnosis and isolation. Even when families choose biomedical care, further delays arise when individuals first try self-medication or over-the-counter drugs, often arriving at clinics only when the illness has advanced. Addressing these socio-cultural challenges will require proactive engagement and multi-sector collaboration [38–40, 43, 68, 69, 71]. Public health authorities should work with trusted local leaders to improve understanding of climate-driven zoonotic risks and foster trust in early reporting [69, 71]. Outreach campaigns can respect cultural traditions while stressing that specific symptoms or unusual illness clusters require immediate medical attention [39, 86]. Leveraging local media, such as Radio Ada, offers promising channels for tailored communication. Strengths and limitations This study’s concurrent mixed-methods design provided a more nuanced understanding of FHWs’ KAP regarding climate change and its link to zoonotic disease. This Ghana district, the Ada East District of Ghana’s Greater Accra Region., where the study was conducted, has demographic and geographic diversity —encompassing urban, peri-urban, and rural areas— and its high concentration of healthcare facilities staffed by a range of clinical personnel, including nurses, midwives, pharmacists, community health officers, and physicians. The district’s dual role as a hotspot for climate-sensitive diseases and a frontline hub for outbreak response made it a highly relevant setting for this study. The survey quantified levels of knowledge, attitudes, and practice, while the focus group offered a platform for FHWs to expand on existing barriers to climate-linked zoonoses preparedness and how providers interpret the challenges they face. The qualitative data added depth and context to the survey findings, strengthening credibility through triangulation. We used validated questions where possible and applied rigorous thematic analysis, grounding findings in participants’ own statements and experiences. The relatively large and diverse sample spanned multiple facility types and professional roles, enhancing the transferability of findings to similar coastal districts in Ghana and increasing their relevance for district-level health planning. However, several limitations should be acknowledged. First, the cross-sectional design prevents causal inference. Second, sampling in a single district limits generalizability, as climate–health awareness may differ in other regions with distinct exposures, health systems, or socio-cultural contexts. That said, Ada East includes urban, peri-urban, and rural facilities, offering a reasonable cross-section for a climate-vulnerable coastal zone. Third, all data were self-reported, raising the possibility of social desirability and recall bias. We attempted to reduce this risk by assuring anonymity and clarifying that the survey was not an evaluation of job performance. We encouraged the frontline staff to describe system gaps they perceive openly. Fourth, thresholds for “Good” practice or attitude (≥60%) were based on Bloom’s taxonomy, a common approach in KAP studies but inherently arbitrary. Finally, the qualitative component involved only one focus group (n=9). Although we sampled diverse roles within the discussion, some perspectives, particularly from those who did not volunteer for the focus group discussion, may not have been captured. Despite these limitations, the consistency we observed between quantitative trends and qualitative narratives lends confidence to the robustness and credibility of our findings. Together, they provide a valuable baseline for future longitudinal or multi-site research on climate–health preparedness among frontline health workers. Conclusion Ghana’s frontline healthcare workers are a critical yet underutilized resource in the national response to climate-sensitive zoonotic threats. They offer valuable experiential knowledge, practical observational skills, and community trust, coupled with a willingness to act. However, conceptual gaps, structural limitations, and social, cultural, and economic barriers hinder the translation of these strengths into sustained institutional preparedness. Bridging this gap requires targeted training, empowerment structures at the facility level, cross-sectoral early-warning systems, and climate-resilient infrastructure. Building on the strengths already present, such as practical observational capacity, media engagement, and community trust, may accelerate climate mitigation efforts and reduce the risk of climate-driven zoonotic outbreaks. Investment in these frontline actors is also an investment in both national health security and global pandemic prevention. Declarations Research Ethics Ethical consideration The study received ethical approval from both the Ghana Health Service Ethical Review Committee (protocol GHS‑ERC 024/08/24) and the Pennsylvania State University Institutional Review Board (STUDY00025492). Written authorization to conduct the study was also obtained from the administrative leadership of all eighteen participating health facilities. Author Contributions A.N.Y. conceived and designed the project, developed the data collection instrument, coordinated data collection, performed data analysis, and drafted and finalized the manuscript. K.P.W. contributed to data management, analysis, and manuscript preparation. H.E.S. participated in the review of the survey instrument and qualitative data analysis. K.K.S. assisted in the study design, reviewed the manuscript for scientific content, and provided critical revisions. G.H., L.B., E.K., and C.L.N. contributed to data collection, review of study instruments, and manuscript review. K.T.R. and A.T.G. reviewed and provided input on the manuscript. M.A.K. supervised the final analysis, contributed to the interpretation of results, and finalized the results and discussion sections. All authors read and approved the final version of the manuscript. Competing Interests The authors declare no competing interests. Funding This study was supported by the Institute of Energy and the Environment (IEE) at Penn State University [IO Number: 46000000820]. The funders had no role in the design of the study, data collection, analysis, interpretation of data, or in writing the manuscript. Acknowledgements We want to sincerely thank the University of Ghana for facilitating this work and the local data collectors for their dedication in the field. We are especially grateful to the frontline health care workers in Ada East, Ghana, whose participation and insights informed this study and, we hope, will help catalyze change. Data Availability The datasets used and analyzed during the current study are not publicly available due to confidentiality restrictions but can be made available upon reasonable request and collaboration with the corresponding authors (A.N.Y. and M.A.K.). References What Is Climate Change? - NASA Science. (2022, June 15). Retrieved from https://science.nasa.gov/climate-change/what-is-climate-change/ Zell, R. (2004). Global climate change and the emergence/re-emergence of infectious diseases. International Journal of Medical Microbiology Supplements , 293 , 16–26. https://doi.org/10.1016/S1433-1128(04)80005-6 Heffernan, C. (2018). 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Retrieved August 13, 2025, from https://who-africa.africa-newsroom.com/press/strengthening-epidemic-preparedness-and-response-building-resilience-after-ghanas-2023-floods Climate change and health – the health workers’ eyewitness perspective. (n.d.). Retrieved August 13, 2025, from https://www.gavi.org/vaccineswork/climate-change-and-health-health-workers-eyewitness-perspective Sorensen, C. J., & Fried, L. P. (2024). Defining Roles and Responsibilities of the Health Workforce to Respond to the Climate Crisis. JAMA network open , 7 (3), e241435. https://doi.org/10.1001/jamanetworkopen.2024.1435 Pörtner, H.-O., Roberts, D. C., Tignor, M. M. B., Poloczanska, E. S., Mintenbeck, K., Alegría, A., … Rama, B. (Eds.). (2022). Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Mazumder, H., & Hossain, M. M. (2024). Climate change education for health-care professionals: crucial gaps in low-income and middle-income countries. The Lancet Planetary Health , 8 (4), e216. https://doi.org/10.1016/S2542-5196(24)00010-X West, K. P., Sznajder, K. K., Sauve, H. E., Hwang, G., Roba, K. T., Baatiema, L., … Yilma, A. N. (2025, July 9). Zoonotic disease preparedness among frontline healthcare workers in Ghana: Assessing literacy and behaviors in a One Health context. medRxiv. https://doi.org/10.1101/2025.07.08.25331119 Armel, K. C., Yan, K., Todd, A., & Robinson, T. N. (2011). The Stanford Climate Change Behavior Survey (SCCBS): assessing greenhouse gas emissions-related behaviors in individuals and populations. Climatic Change , 109 (3), 671–694. https://doi.org/10.1007/s10584-011-0031-y Collecting Data. (n.d.). One Health Behaviors . Retrieved from https://onehealthbehaviors.org/research/ CDC. (2025, June 4). Completed OHZDP Workshops. One Health . Retrieved June 7, 2025, from https://www.cdc.gov/one-health/php/prioritization/completed-workshops.html Zinsstag, J., Crump, L., Schelling, E., Hattendorf, J., Maidane, Y. O., Ali, K. O., … Cissé, G. (2018). Climate change and One Health. FEMS Microbiology Letters , 365 (11), fny085. https://doi.org/10.1093/femsle/fny085 CDC. (2024, May 16). About Zoonotic Diseases. One Health . Retrieved June 7, 2025, from https://www.cdc.gov/one-health/about/about-zoonotic-diseases.html Mohamud, A. K., Ali, I. A., Ali, A. I., Dirie, N. I., Inchon, P., Ahmed, O. A., & Mohamud, A. A. (2023). Assessment of healthcare workers’ knowledge and attitude on Ebola virus disease in Somalia: a multicenter nationwide survey. BMC Public Health , 23 (1), 1650. https://doi.org/10.1186/s12889-023-16562-2 Wang, L., Abualfoul, M., Oduor, H., Acharya, P., Cui, M., Murray, A., … Pagadala, M. (2022). A cross-sectional study of knowledge, attitude, and practice toward COVID-19 in solid organ transplant recipients at a transplant center in the United States. Frontiers in Public Health , 10 . https://doi.org/10.3389/fpubh.2022.880774 Willoughby, A. R., Phelps, K. L., PREDICT Consortium, & Olival, K. J. (2017). A Comparative Analysis of Viral Richness and Viral Sharing in Cave-Roosting Bats. Diversity , 9 (3), 35. https://doi.org/10.3390/d9030035 Acheampong, E. O., Macgregor, C. J., Sloan, S., & Sayer, J. (2019). Deforestation is driven by agricultural expansion in Ghana’s forest reserves. Scientific African , 5 , e00146. https://doi.org/10.1016/j.sciaf.2019.e00146 Experts warn of serious health impacts from climate change for pregnant women, children, and older people. (2024). Saudi Medical Journal , 45 (7), 754–755. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11237281/ Sorensen, C., Murray, V., Lemery, J., & Balbus, J. (2018). Climate change and women’s health: Impacts and policy directions. PLoS Medicine , 15 (7), e1002603. https://doi.org/10.1371/journal.pmed.1002603 US EPA, O. (2022, March 21). Climate Change and the Health of Older Adults. Overviews and Factsheets. Retrieved August 23, 2025, from https://www.epa.gov/climateimpacts/climate-change-and-health-older-adults Ahmed, M. M., Okesanya, O. J., Othman, Z. K., Ibrahim, A. M., Adigun, O. A., Ukoaka, B. M., … Lucero-Prisno, D. E. (2025). Holistic Approaches to Zoonoses: Integrating Public Health, Policy, and One Health in a Dynamic Global Context. Zoonotic Diseases , 5 (1), 5. https://doi.org/10.3390/zoonoticdis5010005 Amuguni, H., Bikaako, W., Naigaga, I., & Bazeyo, W. (2019). Building a framework for the design and implementation of One Health curricula in East and Central Africa: OHCEAs One Health Training Modules Development Process. One Health (Amsterdam, Netherlands) , 7 , 002–002. https://doi.org/10.1016/j.onehlt.2018.08.002 CDC. (2025, May 14). About One Health. One Health . Retrieved June 7, 2025, from https://www.cdc.gov/one-health/about/index.html Codjoe, S. N. A., & Owusu, G. (2011). Climate change/variability and food systems: evidence from the Afram Plains, Ghana. Regional Environmental Change , 11 (4), 753–765. https://doi.org/10.1007/s10113-011-0211-3 EcoHealth Alliance. (2021, April). Strengthening Pandemic Preparedness in Ghana. World Health Organization. (2024). 2024 Annual Report WHO Ghana. Regional Office for Africa. Retrieved from https://www.afro.who.int/sites/default/files/2025-06/WHO%20Ghana%202024%20Annual%20Report.pdf Additional Declarations No competing interests reported. Supplementary Files MKisielSupplementaryTablefrontlinewrokers252207.docx Cite Share Download PDF Status: Published Journal Publication published 04 Mar, 2026 Read the published version in Discover Public Health → Version 1 posted Editorial decision: Revision requested 16 Jan, 2026 Reviews received at journal 03 Jan, 2026 Reviewers agreed at journal 02 Jan, 2026 Reviews received at journal 29 Dec, 2025 Reviewers agreed at journal 17 Dec, 2025 Reviewers invited by journal 12 Dec, 2025 Editor assigned by journal 05 Dec, 2025 Submission checks completed at journal 05 Dec, 2025 First submitted to journal 04 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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09:16:39","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":302461,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8282544/v1/2558db8c0c99e84746e5a8ef.html"},{"id":98778557,"identity":"16f46275-9ab9-4b05-a9bc-bcda79957c4e","added_by":"auto","created_at":"2025-12-22 12:29:27","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":119198,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic distribution of health facilities and frontline healthcare worker (FHW) focus group participants in Ada East District, Ghana\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote: \u003c/strong\u003eLocations were geocoded and mapped using ArcGIS Pro v3.2. Color gradients indicate the density of participating frontline healthcare workers (FHWs), with yellow representing higher respondent density, red medium, and blue lower density.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8282544/v1/d4235693f5f57d0c2e32caab.jpeg"},{"id":104250657,"identity":"62509446-aa9a-4bce-980c-050a6124a3d2","added_by":"auto","created_at":"2026-03-09 16:04:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2650417,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8282544/v1/08fc280f-11ae-4cb9-a599-d7ecb5b4f4d9.pdf"},{"id":98752624,"identity":"eb2dcb5c-4b20-418a-8756-69cf773a17b4","added_by":"auto","created_at":"2025-12-22 09:16:40","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":44433,"visible":true,"origin":"","legend":"","description":"","filename":"MKisielSupplementaryTablefrontlinewrokers252207.docx","url":"https://assets-eu.researchsquare.com/files/rs-8282544/v1/8561bb3ad36f36c12a812a8f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Frontline knowledge, attitudes, and practices on climate change and its link to zoonotic diseases: a mixed-methods study of healthcare workers in Ada East, Ghana","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHuman-induced climate change, defined as long-term alterations in local, regional, and global weather patterns driven primarily by anthropogenic greenhouse gas emissions and land-use changes, has emerged as a key modifier of infectious disease dynamics [\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Such climate stressors are intensifying the emergence and re-emergence of zoonotic diseases by altering environmental conditions that influence pathogen transmission [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9 CR10 CR11 CR12 CR13\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In recent decades, zoonotic outbreaks have increased in both frequency and geographic range, a trend expected to worsen as climate pressures escalate [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Over 60% of emerging infectious disease events since 1940 have been zoonotic, with most traced to wildlife reservoirs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These climate-related hazards are already intensifying global health risks [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. While global evidence links climate stressors to zoonotic emergence, limited research explores how these mechanisms operate in specific regional contexts such as West Africa.\u003c/p\u003e \u003cp\u003eClimate variability amplifies zoonotic spillover risk through disrupted ecosystems and host-pathogen dynamics [\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Species migration, vector expansion, and habitat overlap increase cross-species viral exchange [\u003cspan additionalcitationids=\"CR26 CR27 CR28 CR29 CR30 CR31 CR32\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. These changes increase the likelihood of new pathogen transmission cycles, especially in biodiversity-rich, rapidly urbanizing regions as in West Africa.\u003c/p\u003e \u003cp\u003eThese global patterns in climate change and disease vectors are acutely relevant to Ghana, which is home to 221 species of amphibians and reptiles, 728 bird species, and 225 mammal species [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Wetlands in Accra provide stopover habitats for migratory species, further contributing to the region\u0026rsquo;s potential reservoir of zoonotic pathogens [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Urban ecosystems like Accra\u0026rsquo;s wetlands host migratory birds and bat colonies, while bushmeat consumption and livestock encroachment into wildlife habitats intensify human\u0026ndash;animal interfaces [\u003cspan additionalcitationids=\"CR37 CR38 CR39 CR40 CR41 CR42 CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Clearly, much of Ghana\u0026rsquo;s population relies directly on these ecosystems for their livelihoods [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Few studies explore how environmental and livelihood changes affect zoonotic disease risks in Ghana, despite its ecological and social vulnerabilities.\u003c/p\u003e \u003cp\u003eFrontline healthcare workers (FHWs)\u0026mdash;including community nurses, clinicians, and public health officers\u0026mdash;are pivotal to early outbreak detection and climate-resilient health systems in vulnerable regions such as Accra [\u003cspan additionalcitationids=\"CR66 CR67\" citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Embedded within their communities, they are trusted communicators who bridge clinical and community knowledge, translating climate\u0026ndash;health messages into practical action[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70 CR71\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. However, the effectiveness of FHWs in this role depends on adequate awareness, knowledge, and training related to the climate\u0026ndash;zoonoses nexus.\u003c/p\u003e \u003cp\u003eThe Intergovernmental Panel on Climate Change (IPCC) warns that the severity of climate-related health risks will hinge on how effectively health systems and their staff can anticipate and manage emerging threats [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e]. Yet gaps remain between high-level climate\u0026ndash;health policy and local implementation [\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. In Ghana, limited climate-specific training and constrained resources remain significant barriers to operationalizing climate\u0026ndash;health strategies [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Without insight into how FHWs perceive and manage these interconnected challenges, it is difficult to tailor solutions that enhance zoonotic outbreak prevention, preparedness, and resilience at the community level in an era of climate change.\u003c/p\u003e \u003cp\u003eTo address these gaps, this study employed a mixed-methods approach to examine how FHWs in Ghana\u0026rsquo;s Ada East District understand and perceive the relationship between climate change and zoonotic disease transmission. This study (i) quantitatively assessed FHWs\u0026rsquo; knowledge, attitudes, and practices (KAP) related to the climate-zoonoses nexus, gauging both their understanding and the extent to which this knowledge informs their practices; (ii) identified predictors of higher KAP, such as sociodemographics, professional experience, and prior training; and (iii) qualitatively contextualized survey findings through a focus group discussion, exploring FHWs\u0026rsquo; perspectives on climate\u0026ndash;zoonosis dynamics, barriers to climate adaptation in healthcare settings, and recommendations for strengthening zoonotic preparedness in a changing climate.\u003c/p\u003e"},{"header":"Materials and method","content":"\u003cp\u003e\u003cstrong\u003eStudy design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a concurrent exploratory mixed-methods design, integrating quantitative cross-sectional survey data with a qualitative, semi-structured focus group discussion. Data collection took place from January 30th to February 7th, 2025, in the Ada East District of Ghana\u0026rsquo;s Greater Accra Region. Eighteen healthcare facilities were purposively sampled in collaboration with the University of Ghana (Figure 1). These included district hospitals, local health centers, and Community-Based Health Planning and Services compounds, chosen to reflect the diversity of the regional healthcare delivery system. We describe both the quantitative and qualitative procedures in the following section.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEligible participants included FHWs employed at the selected facilities who met the following inclusion criteria: (1) age \u0026ge;18 years; (2) actively involved in direct patient care at the facility for \u0026ge;3 months; (3) \u0026ge;6 months post-completion of formal clinical training; (4) proficient in English\u0026mdash;the official language of healthcare delivery in Ghana; and (5) able to provide written informed consent. Individuals were excluded if they were not engaged in patient care, were unavailable during data collection, or declined to participate. Eligibility was confirmed at the time of enrollment by trained research personnel. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe required sample size was calculated using a single-population proportion formula, as outlined in a prior manuscript [75]. Due to the absence of existing data specific to the Ada East District, we assumed a 6% prevalence of poor KAP, a 3% margin of error, and a 95% confidence level. This yielded a minimum sample size of 241 participants. To accommodate potential nonresponse and ensure sample diversity, we targeted 250 participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative part\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipant recruitment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSurvey recruitment was conducted on-site at each selected healthcare facility. In total, 250 subjects fulfilled inclusion criteria to this study, and thus, were included in the study. \u0026nbsp;Recruitment at each facility continued until no additional eligible participants remained. Local data collectors coordinated with facility administrators to identify optimal recruitment windows that minimized disruption to clinical activities across day and night shifts. During these time windows, trained research assistants approached eligible staff in common areas to introduce the study and distribute informational leaflets. Interested individuals were escorted to a private area where the study was explained and questions were addressed. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eSurvey pilot testing\u0026nbsp;\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe survey instrument underwent pilot testing with 10 FHWs at a nearby hospital to assess question clarity, survey flow, and technical usability of tablet devices for data collection. Based on feedback, we refined the instrument by incorporating a standardized definition of climate change at the start of the attitude\u0026rsquo;s module. We clarified select climate mitigation practices to eliminate any ambiguity among participants.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eTen research assistants were recruited and completed a two-day training in Good Clinical Practice, study-specific protocols, informed consent procedures, survey administration techniques, and hands-on instruction using the Research Electronic Data Capture (REDCap) platform. Surveys were administered using REDCap-enabled tablets via structured, interviewer-led sessions conducted in private areas of each facility. Research assistants read each survey question (in English) aloud to the participant and entered the participant\u0026rsquo;s responses into the REDCap-enabled tablet in real time. Each session lasted approximately 45 to 60 minutes. No personal identifiers were collected with the survey data, unless participants were willing to participate in the follow-up focus discussion groups. Those provided a first name and phone number, which were recorded in a separate, password-protected file accessible only to the principal investigator. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eSurvey Measures\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eA structured questionnaire was developed to assess FHWs\u0026rsquo; KAP regarding climate change, its health impacts, and its links to zoonotic diseases such as EVD. Several items were adapted from previously validated KAP surveys and other peer-reviewed information sources on the topics of climate change, its health impacts, and the link to zoonotic diseases [76\u0026ndash;80].\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e The tool included \u003cstrong\u003efour main sections\u003c/strong\u003e: sociodemographic and professional background, knowledge, attitudes, and practices related to climate change and health.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003e\u003cem\u003eSociodemographic and Professional Characteristics\u003c/em\u003e\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eRespondents reported age, sex, education, occupational role, facility type, total years of healthcare experience, and years managing infectious diseases. They also indicated prior formal training on infectious diseases (topics covered, training providers), and their frequency and preferred sources of information about climate change and zoonotic diseases (radio, television, internet, social media, or mobile applications).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eKnowledge of Climate Change and its Health Impacts\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKnowledge was assessed using \u003cstrong\u003e37 items\u003c/strong\u003e (true/false and multiple-response) across three domains:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eClimate change (16 items):\u003c/strong\u003e understanding of definitions, anthropogenic causes (industrial activity, deforestation, greenhouse gas emissions), and environmental effects (temperature rise, altered rainfall, floods, droughts).\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHealth impacts (12 items):\u003c/strong\u003e awareness of climate-related diseases (heat stress, vector- and water-borne diseases, malnutrition, respiratory and mental health conditions) and recognition of vulnerable groups.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eClimate\u0026ndash;zoonoses link (9 items):\u003c/strong\u003e knowledge of how climatic shifts alter pathogen ecology, host migration, and disease emergence.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eEach correct answer scored \u003cstrong\u003e1 point\u003c/strong\u003e, incorrect/unsure scored \u003cstrong\u003e0\u003c/strong\u003e, yielding a total score of 0\u0026ndash;37, expressed as a percentage. Scores \u003cstrong\u003e\u0026ge;60% (\u0026ge;23 points)\u003c/strong\u003e were classified as \u003cem\u003egood knowledge\u003c/em\u003e, both overall and by domain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAttitudes Toward Climate Change Mitigation and Health\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeven \u003cstrong\u003eLikert-scale statements\u003c/strong\u003e (1 = strongly disagree to 4 = strongly agree) assessed attitudes toward:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eSupport for climate change mitigation actions,\u003c/li\u003e\n \u003cli\u003eStakeholder responsibility (government, individuals, private sector, donors),\u003c/li\u003e\n \u003cli\u003eHealth sector\u0026rsquo;s environmental role, and\u003c/li\u003e\n \u003cli\u003eBeliefs about human capacity to influence climate outcomes.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eFor analysis, responses were dichotomized: \u0026ldquo;agree/strongly agree\u0026rdquo; = favorable (1); \u0026ldquo;disagree/strongly disagree\u0026rdquo; = unfavorable (0). The negatively worded item (\u0026ldquo;Climate change is an act of God and cannot be controlled\u0026rdquo;) was reverse-coded. Total attitude scores ranged from \u003cstrong\u003e0\u0026ndash;7\u003c/strong\u003e\u003cstrong\u003e,\u0026nbsp;\u003c/strong\u003ewith \u003cstrong\u003e\u0026ge;4\u003c/strong\u003e indicating \u003cem\u003epositive attitudes\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClimate Change Mitigation Practices\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants were asked about \u003cstrong\u003e13 practice items\u003c/strong\u003e, divided into:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eIndividual-level behaviors (8 items):\u003c/strong\u003e actions such as energy and water conservation, recycling, clean cookstove use, and low-carbon transport.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eInstitutional-level behaviors (5 items):\u003c/strong\u003e facility-based practices such as reducing medical waste, switching off unused equipment, and promoting sustainability in meetings.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026ldquo;Yes/No\u0026rdquo; items were scored 1 for \u0026ldquo;Yes\u0026rdquo;; frequency items (\u0026ldquo;often/always\u0026rdquo;) were also scored 1. The composite practice score ranged \u003cstrong\u003e0\u0026ndash;13\u003c/strong\u003e\u003cstrong\u003e,\u003c/strong\u003e with higher scores reflecting \u003cem\u003ebetter climate mitigation practices\u003c/em\u003e. Sub-scores for individual and institutional practices were analyzed separately.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eAll analyses were conducted in RStudio v4.3.1. Descriptive statistics were used to summarize participant characteristics. Continuous variables were presented as means and standard deviations (SD), and categorical variables as frequencies and percentages. Composite KAP scores were calculated by summing responses, converting total scores to percentages, and classifying participants according to Bloom\u0026rsquo;s taxonomy, as used in prior KAP research [81, 82]. That is, scores \u0026gt;60% were labeled \u0026ldquo;Good\u0026rdquo; or \u0026ldquo;Positive,\u0026rdquo; while scores \u0026le;60% were considered \u0026ldquo;Poor\u0026rdquo; or \u0026ldquo;Negative.\u0026rdquo; Geospatial data visualizing facility locations and participant distributions across Ada East were generated using ArcGIS Online v3.2. Logistic regression was used to identify covariates associated with \u0026ldquo;Good\u0026rdquo; knowledge, \u0026ldquo;Positive\u0026rdquo; attitudes, and \u0026ldquo;Good\u0026rdquo; practices. Covariates included sociodemographic factors (e.g., sex, age), occupational characteristics (e.g., facility type, clinical role, years of experience), training history (e.g., training source, content), and information access (e.g., source type, frequency). Univariate models yielded crude odds ratios (ORs) with 95% Cis. These were followed by a fully adjusted multivariable logistic regression \u0026mdash;adjusting for all theoretically relevant variables shown in Table 1\u0026mdash; which yielded adjusted odds ratios (AORs) with 95% CIs. Covariates with \u0026lt; 5% prevalence or near-zero variance were excluded from modeling. Participants with missing covariate data were omitted list-wise in subsequent regression analyses. Statistical significance was set at \u0026alpha; = 0.05, using two-sided Wald chi-square tests. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative Part\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFocus Group Discussion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA semi-structured focus group discussion guide was developed to explore FHWs\u0026rsquo; KAP regarding zoonotic diseases\u0026mdash;particularly Ebola Virus Disease\u0026mdash;and their perceived links with climate change. The guide covered two domains:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eZoonotic disease knowledge and preparedness\u003c/strong\u003e \u0026ndash; beliefs, misconceptions, and management practices.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eClimate change and health\u003c/strong\u003e \u0026ndash; awareness, perceived impacts, and mitigation or adaptation strategies.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eQuestions were open-ended, with targeted probes to encourage discussion and clarify survey findings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTraining for Focus Group Discussion\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo capture a broad range of frontline perspectives, we employed a maximum-variation purposive sampling approach during the same five-day period as the survey. Survey responses were reviewed in real time to identify interested FHWs and ensure diversity across occupational roles, facility types, sex, experience levels, and training backgrounds. Sampling continued until the target of 7 to 10 participants was reached. Participants in the focus group discussion were either newly recruited from the 18 study sites or selected from among survey respondents. Ultimately, we enrolled nine FHWs (2 men, 7 women), purposively selected to deliberately yield a diverse sample for the focus group discussion on climate change and zoonotic disease. \u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFocus Group Discussion\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Data Collection\u0026nbsp;\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe focus group discussion was conducted in a private room at \u003cstrong\u003eAda East District Hospital\u003c/strong\u003e to ensure comfort and confidentiality. The session was facilitated in \u003cstrong\u003eEnglish and Dangme\u003c/strong\u003e by a trained moderator, supported by a note-taker. Participants were assigned \u003cstrong\u003enumeric identifiers (P1\u0026ndash;P9)\u003c/strong\u003e for anonymity. The moderator reviewed the study purpose, ground rules, and obtained \u003cstrong\u003everbal group consent\u003c/strong\u003e for recording. The session lasted \u003cstrong\u003e~100 minutes\u003c/strong\u003e, with member-checking used throughout to confirm interpretations. Audio was transcribed verbatim and translated into English when needed by the bilingual moderator and note-taker. All data were de-identified and securely stored by the principal investigator.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQualitative Data Analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA \u003cstrong\u003ethematic analysis\u003c/strong\u003e guided by grounded theory principles was used. Three researchers (one senior, two trained assistants) independently reviewed the transcript and developed a \u003cstrong\u003ehybrid codebook\u003c/strong\u003e, combining deductive codes from the guide and inductive codes emerging from the data.\u003c/p\u003e\n\u003cp\u003eLine-by-line coding was performed with \u003cstrong\u003econstant comparison\u003c/strong\u003e to ensure consistency. The team met to reconcile differences and refine the codebook. Themes were formed by clustering related codes and were supported by \u003cstrong\u003erepresentative quotations and counterexamples\u003c/strong\u003e to capture variation in perspectives.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from both the Ghana Health Service Ethical Review Committee (protocol GHS‑ERC 024/08/24) and the Pennsylvania State University Institutional Review Board (STUDY00025492). Written authorization to conduct the study was also obtained from the administrative leadership of all eighteen participating health facilities. Then, all survey data were collected anonymously, with no direct identifiers included in the analytic dataset. Participation was voluntary, and individuals were assured that declining or withdrawing from the study would have no impact on their employment or benefits. \u0026nbsp;Written informed consent was obtained from all participants before enrollment. All participants were provided 160 Ghanian Cedi (13.39 USD) upon completion of the survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOnly individuals who expressed interest in the focus group discussion voluntarily provided their name and phone number for recontact. This identifying information was stored in a separate, encrypted, password-protected file accessible only to the principal investigator and was not linked to survey responses. Participants in the focus group discussion signed a separate consent form specific to the qualitative component. Upon completion of the focus group discussion, all participants were provided with 160 Ghanaian cedis (13.39 USD).\u003c/p\u003e"},{"header":"Results","content":"\u003ch3\u003e\u003cstrong\u003eStudy demographics\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eA total of 250 FHWs (73.2% women) in Ada East completed the survey (Table 1). The mean age was 32.8 years (SD = 6.4). Most participants were stationed at either district or regional hospitals (46.4%) or health centers (44.8%), while 8.8% worked in Community-based Health Planning and Services compounds. Nurses comprised the largest cadre (61.2%). Respondents averaged 6.0 years (SD = 5.6) of professional experience. Nearly all reported active involvement in direct clinical care and preventive services. The most frequently covered diseases included COVID-19, monkeypox, rabies, and Ebola virus disease. Digital platforms were the predominant source of professional information, accessed by 96.4% for zoonoses and 95.2% for climate-related health topics. Conventional media such as television and radio remained common, while public channels were cited less often. The majority of FHWs reported engaging with climate change information only occasionally or not at all.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSociodemographic, professional, training, and information-access characteristics of study participants (N=250), frontline healthcare workers (FHWs).\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"448\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN (%)\u003c/strong\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (in years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e20 - 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e84 (33.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e30 - 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e83 (33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e35-37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 145px;\"\u003e\n \u003cp\u003e83 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 1px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex - Women\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e183 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eSSS/SHS/Technical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e11 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e239 (95.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthcare Facility Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eCHPS Compound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e22 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eDistrict/Regional Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e116 (46.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eHealth Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e112 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupational Category\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eNurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e153 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eMidwives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e45 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eOther Clinical Staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e41 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eAdministrative and Support Staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e11 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActivities Performed in Job Role\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eProvision of clinical services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e245 (98.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eClinical support group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e93 (37.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003ePreventative health services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e229 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1 (0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears of Experience in Current Job\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e94 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u0026le; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e156 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnoses and Treats Patients with Infectious Diseases\u003c/strong\u003e\u003cstrong\u003e**\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e156 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReceived Infectious Diseases Training\u003c/strong\u003e\u003cstrong\u003e*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e175 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWho Provided Infectious Diseases Training\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eExperts from the Respondents\u0026rsquo; Health Facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e121 (48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eExperts from the Ministry and the Government Health Authorities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e104 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eExperts from International NGOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e27 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eAcademic or School-Based Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e8 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eNo Training Received / Other\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e75 (30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 448px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhat Infectious Diseases Training Provide\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eCOVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e149 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eEbola virus disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e64 (25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eMarburg virus disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e24 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eHuman monkeypox virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e74 (29.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eRabies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e72 (28.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eAnthrax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e14 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eCholera\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e45 (18.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eTuberculosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e14 (5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e13 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 448px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent Source of Zoonotic Disease Information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eElectronic media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e241 (96.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eConventional media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e155 (62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003ePublic media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e94 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 448px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent Source of Climate Change Information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eElectronic media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e238 (95.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eConventional media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e163 (65.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003ePublic media\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e93 (33.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 448px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFrequency of Engagement with Climate Change Information\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eAlways or often\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e26 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 302px;\"\u003e\n \u003cp\u003eSometimes, rarely, or never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 146px;\"\u003e\n \u003cp\u003e224 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u0026nbsp;\u003c/strong\u003eMissing variables: *n=1 and **n=4; \u0026nbsp;multi-response items (e.g., training topics and information sources) are not mutually exclusive and may exceed 100%. Abbreviations: CHPS = Community-based Health Planning and Services; SSS/SHS = senior secondary school / technical school (e.g., secondary); NGO = non-governmental organizatio\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eKnowledge of climate change and its health impacts\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eMost FHWs (83.2%) met the \u0026ge;60% threshold for \u0026ldquo;Good\u0026rdquo; climate change and health knowledge (Supplementary Table 1). Participants correctly identified major biophysical indicators of climate change, including changes in temperature and rainfall (89.2%), increased frequency of droughts and floods (94.0%), and rising sea levels and coastal erosion (74.4%). Key drivers such as deforestation (96.0%), industrial emissions (90.8%), atmospheric pollution from open waste burning (96.4%), and carbon dioxide emissions (86.0%) were widely recognized. However, fewer respondents linked agriculture (56.0%) and methane from livestock (40.8%) to climate change. In the health impacts domain, most FHWs associated climate change with heat-related (91.6%) and air-quality-related illnesses (94.4%). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecognition of indirect impacts was lower: malnutrition (54.8%), mental health conditions (28.0%), and social conflict (26.0%). Awareness of vulnerable populations was also limited, with fewer than half identifying children (46.4%), older adults (44.4%), or women (11.6%) as especially susceptible to climate-related health risks. Nearly all respondents (96.4%) agreed that climate change increases infectious disease outbreaks, and 98.8% linked it to illness in both humans and livestock. Most participants understood that rising temperatures and shifting rainfall patterns expand vector habitats (93.2%), and many anticipated increased EVD outbreak risk (81.6%) and emergence in new locations (83.2%).\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAttitudes toward climate change\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eMost respondents expressed strong pro-mitigation attitudes, with 86.8% (n = 217) meeting the \u0026ge;60% threshold for a \u0026ldquo;Positive\u0026rdquo; climate change attitude (Supplementary Table 2). Support for climate change mitigation was nearly universal; 94.4% agreed it is essential for controlling emerging and re-emerging zoonoses. Most respondents assigned primary responsibility to the Ministry of Health (84.8%) and private citizens (79.6%). Fewer attributed responsibility to international actors such as industrialized nations (57.6%) and donors or NGOs (59.6%). A majority (72.8%) acknowledged that healthcare systems contribute to climate change. Fatalistic beliefs were uncommon\u0026mdash;only 17.2% agreed that climate-related disasters are unavoidable \u0026ldquo;acts of God.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003ePractices regarding climate change mitigation\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eOverall engagement in climate change mitigation practices was moderate, with 62.4% (n = 156) classified as having \u0026ldquo;Good\u0026rdquo; climate change mitigation practices (Supplementary Table 3). Individual-level practices were more commonly adopted than institutional ones. Nearly 80% (79.6%) met the threshold for \u0026ldquo;Good\u0026rdquo; individual practices (mean = 6.39, SD = 1.02). Routine behaviors included switching off lights and appliances (92.0%), using energy-efficient bulbs (85.2%), and adopting low-energy devices (82.0%). Water conservation (76.4%) and clean cookstove use (89.2%) were also widely reported. Fewer respondents reported harvesting rainwater (50.0%), practicing waste sorting (45.6%), or using low-carbon transport (59.2%). Institutional-level practices were limited. Only 11.2% (n = 28) achieved \u0026ldquo;Good\u0026rdquo; institutional practice scores. While most reported turning off unused digital (64.4%) and clinical equipment (61.6%), a minority reported minimizing single-use plastics (15.2%) or integrating climate mitigation into staff meetings or training (4.4%).\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFactors associated with climate-change knowledge, attitudes, and practices\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eMost frontline healthcare workers demonstrated good knowledge and positive attitudes toward climate change and health across sociodemographic, professional, and training categories. Slight variations were observed by age, facility type, and prior infectious-disease training, but overall awareness and attitudes remained consistently high across all groups (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eProportions of good climate change and health knowledge among frontline healthcare workers (N = 250).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"681\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 154px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnowledge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitudes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitudes\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGood\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 67px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNegative\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 681px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSociodemographic Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 112px;\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e20-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e73 (86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e73 (86.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e49 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e15 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e68 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e72 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e32 (38.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e51 (61.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e35-57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e16 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e67 (80.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e72 (86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e27 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e56 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eMan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e12 (17.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e55 (82.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e6 (9.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e61 (91.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e24 (35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e43 (64.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eWoman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e30 (16.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e153 (83.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e27 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e156 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e70 (38.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e113 (61.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 681px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 112px;\"\u003e\n \u003cp\u003eHealthcare Facility Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eCHPS Compound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e2 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e20 (90.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e2 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e20 (90.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e5 (22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e17 (77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eDistrict/Regional Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e21 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e95 (81.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e18 (15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e98 (84.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e56 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e60 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eHealth Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e19 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e93 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e13 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e99 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e33 (29.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e79 (70.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 112px;\"\u003e\n \u003cp\u003eOccupational Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e29 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e125 (81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e19 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e134 (87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e56 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e97 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eMidwives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e9 (20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e36 (80.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e8 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e37 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e19 (42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e26 (57.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eOther Clinical Staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e4 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e37 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e4 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e37 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e15 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e26 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eExperience in Current Role\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20 (21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e74 (78.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e83 (88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e34 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e60 (63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003e\u0026le; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e22 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e134 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e22 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e134 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e60 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e96 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eDiagnoses/Treats Patients w/ IDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e26 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e130 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e19 (12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e137 (87.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e55 (35.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e101 (64.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e15 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e75 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e14 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e76 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e35 (38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e55 (61.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 681px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraining Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eReceived ID Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e31 (17.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e144 (82.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e21 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e154 (88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e64 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e111 (63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e63 (85.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e12 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e62 (83.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e29 (39.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e45 (60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 112px;\"\u003e\n \u003cp\u003eExperts Who Delivered ID Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Respondents\u0026rsquo; Health Facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e14 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e115 (89.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e12 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e117 (90.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e44 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e85 (65.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Respondents\u0026rsquo; Health Facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e28 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e93 (76.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e21 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e100 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e50 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e71 (58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Ministry/Government Health Authorities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e28 (19.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e118 (80.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e26 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e120 (82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e54 (37.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e92 (63.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Ministry/Government Health Authorities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e14 (13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e90 (86.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e7 (6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e97 (93.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e40 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e64 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - International NGOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e38 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e185 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e31 (13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e192 (86.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e88 (39.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e135 (60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - International NGOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e4 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e23 (85.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e2 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e25 (92.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e6 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e21 (77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" style=\"width: 112px;\"\u003e\n \u003cp\u003eWhat ID Training Was Delivered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - COVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e11 (10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e90 (89.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e12 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e89 (88.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e42 (41.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e59 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - COVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e31 (20.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e118 (79.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e21 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e128 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e52 (34.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e97 (65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Ebola virus disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e26 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e160 (86.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e23 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e163 (87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e74 (39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e112 (60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Ebola virus disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e16 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e48 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e10 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e54 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e20 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e44 (68.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Human monkeypox virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e20 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e156 (88.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e20 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e156 (88.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e62 (35.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e114 (64.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Human monkeypox virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e22 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e52 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e13 (17.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e61 (82.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e32 (43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e42 (56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Rabies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e23 (12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e155 (87.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e22 (12.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e156 (87.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e64 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e114 (64.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Rabies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e19 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e53 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e61 (84.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e30 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e42 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 681px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation Access Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 112px;\"\u003e\n \u003cp\u003eCurrent Source of Zoonotic Disease Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e24 (25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e71 (74.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e15 (15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e80 (84.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e41 (43.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e54 (56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e18 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e137 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e18 (11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e137 (88.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e53 (34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e102 (65.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Public media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e32 (20.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e124 (79.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e22 (14.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e134 (85.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e64 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e92 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Public Media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e10 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e84 (89.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11 (11.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e83 (88.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e30 (31.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e64 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 112px;\"\u003e\n \u003cp\u003eCurrent Source of Climate Change Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e25 (28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e62 (71.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e19 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e68 (78.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e39 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e48 (55.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e17 (10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e146 (89.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e14 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e149 (91.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e55 (33.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e108 (66.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eNo - Public media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e35 (21.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e132 (79.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e24 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e143 (85.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e67 (40.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e100 (59.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eYes - Public Media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e7 (8.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e76 (91.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e9 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e74 (89.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e27 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e56 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 112px;\"\u003e\n \u003cp\u003eFrequency of Climate Change Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eAlways or Often\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e3 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e23 (88.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e2 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e24 (92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e7 (26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e19 (73.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 137px;\"\u003e\n \u003cp\u003eSometimes, Rarely, or Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003e39 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e185 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e31 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e193 (86.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e87 (38.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e137 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u0026nbsp;\u003c/strong\u003eCHPS = Community-based Health Planning and Services; ID infectious diseases \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the adjusted multivariate logistic regression, knowledge, professional role, and training source were the only significant covariates (Table 3). Compared with nurses, other clinical staff (e.g., physicians, pharmacists, and laboratory technologists) had higher odds of good knowledge. Compared with no monkeypox training, receipt of monkeypox training was associated with lower odds of good knowledge. Accessing climate change information via conventional media was associated with higher odds of positive attitudes than no conventional media access.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor practices, institutional settings, and training providers emerged as key covariates. Relative to Community-based Health Planning and Services compounds, FHWs based at district or regional hospitals were associated with lower odds of good practices. Compared with no training, participation in international non-governmental organization-led training was associated with higher odds of good practices, whereas Ministry of Health\u0026ndash;led training was associated with lower. Receipt of monkeypox was also associated with lower odds of good practices versus no monkeypox training. There were no significant associations in crude logistic regression (Supplementary table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003ePredictors of good climate change attitudes among frontline healthcare workers (N = 250). Logistic regression was presented as odds ratios (ORs) with 95% confidence intervals (95% CI), adjusted (adj) for all theoretically relevant variables shown in Table 1\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"662\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKnowledge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAttitudes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePractices\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eadjOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eadjOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eadjOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 662px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSociodemographic Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 116px;\"\u003e\n \u003cp\u003eAge (in years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e20-29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e30-34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.24-1.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.26-2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.51-2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e35-57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.22-3.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.16-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.53-3.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eWoman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.56-4.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.08-1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.24-1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 662px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 116px;\"\u003e\n \u003cp\u003eHealthcare Facility Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eCHPS Compound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eDistrict/Regional Hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09-3.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.08-3.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.05-0.61\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eHealth Center\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.06-1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.13-4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.25-2.81\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 116px;\"\u003e\n \u003cp\u003eOccupational Category\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNurse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMidwives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.34-3.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.29-2.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.58-3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eOther Clinical Staff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.12-22.76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.21-4.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.42-3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eExperience in Current Role\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u0026le; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.32-2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.10-1.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52-2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eDiagnoses/Treats Patients w/ IDs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.27-1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.29-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.31-1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 662px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTraining Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eReceived ID Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.19-1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.23-2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.31-1.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 116px;\"\u003e\n \u003cp\u003eExperts Who Delivered ID Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Respondents\u0026rsquo; Health Facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Respondents\u0026rsquo; Health Facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.19-1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.23-1.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.39-1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Ministry/Government Health Authorities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Ministry/Government Health Authorities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.58-3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.79-7.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.21-0.91\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - International NGOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - International NGOs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.38-5.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.46-16.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e4.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e1.44-18.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" style=\"width: 116px;\"\u003e\n \u003cp\u003eWhat ID Training Was Delivered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - COVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - COVID-19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.22-1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.21-1.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.97-4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Ebola virus disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Ebola virus disease\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.30-2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.23-2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.95-6.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Human monkeypox virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Human monkeypox virus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.08-0.64\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.12-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.39\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.17-0.90\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Rabies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Rabies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.24-2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.37-4.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.20-1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" valign=\"top\" style=\"width: 662px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInformation Access Characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 116px;\"\u003e\n \u003cp\u003eCurrent Source of Zoonotic Disease Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.53-5.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.08-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.64-3.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Public media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Public Media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.35-5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.28-6.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.52-5.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 116px;\"\u003e\n \u003cp\u003eCurrent Source of Climate Change Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Conventional media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.67-6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.94-37.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.45-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo - Public media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes - Public Media\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e2.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.55-11.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09-3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.21-2.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 116px;\"\u003e\n \u003cp\u003eFrequency of Climate Change Information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eAlways or often\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSometimes, Rarely, or Never\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.22-4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.10-3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e0.19-1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: NGO = non-governmental organization; ID Infectious Diseases\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eQualitative Results\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe focus group discussion involved nine FHWs \u0026mdash;seven women and two men\u0026mdash; ranging in age from 28 to 56 years. While all nine attended the FGD, only eight actively conversed during the discussion (Table S1). Educational backgrounds varied: two participants held upper-secondary diplomas, six held Bachelor of Science degrees, and one held a master\u0026rsquo;s degree. Participants also represented a range of occupational cadres, including one doctor, one pharmacist, three nurses, three midwives, and one laboratory technician. Their specific professional roles included Senior Medical Officer, Head of Pharmacy, Senior Nursing Officer, Neonatal Intensive Care Unit nurse, inpatient department nurse, maternity ward midwife, two Senior Staff Midwives, and Senior Medical Laboratory Technician, respectively. Time employed at their health facility ranged from nine months to eighteen years. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePrimary themes from the focus group discussion reflected how frontline workers interpret and understand climate change and its link to zoonotic disease (Supplementary Table 5). Specifically, participants emphasized their lived experiences with shifting weather patterns and related health impacts, and recognized links between environmental change and zoonotic risk. They highlighted community beliefs and economic pressures that delay care-seeking. FHWs also identified institutional gaps in preparedness and collectively called for stronger multisectoral collaboration, infrastructure investment, and follow-through on climate\u0026ndash;health policies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFHWs\u0026rsquo; understanding of climate change in the local context\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFHWs described climate change as an observable shift in environmental conditions, particularly weather patterns. In defining climate change, most participants referred to their lived experiences with rising temperatures, unpredictable rainfall, and deviations from expected seasonal norms. For example, many participants often described climate change as a disruption in once-predictable seasonal patterns. One respondent noted:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Climate change might be either excessive or complete change in what is expected. For example, I\u0026apos;m expecting a Harmattan to start somewhere in December, ending in January. I\u0026apos;m now feeling some funny things in my nose, like we are facing harmattan.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMeanwhile, others highlighted the rising heat as one of the most tangible indicators of climate change, with the same respondent stating, \u003cem\u003e\u0026ldquo;Change in weather. Yes. Like currently as we are fanning ourselves, the weather is very hot, so there is a change in the weather\u0026rdquo;\u003c/em\u003e (Participant #1, Male, 56 years, Pharmacist). In addition to temperature and seasonal shifts, participants also emphasized changes in rainfall patterns as an indicator of climate change\u003cem\u003e: \u0026ldquo;Maybe they are expecting this month to be rainy season, but because of climate change, they will see the sun\u0026rdquo;\u003c/em\u003e (Participant #5, Female, 51 years, Midwife). For one participant, climate change was understood as a broader national or even regional phenomenon that manifests differently depending on location. They thoughtfully remarked:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;I was expecting to hear a question like, is the climate in Ada different from maybe Accra, or maybe Tema, or Ahafo, or somewhere else? \u0026hellip; There are times where it could be raining heavily in Accra, but here in Ada, we are still in the heat. So, \u0026hellip; currently our climate has changed to the extent that one state... can be experiencing a cool weather, the other can be experiencing a very hot weather.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, several respondents linked changing temperatures, heavy rains, and the Harmattan season with increases in specific health conditions. For example, many participants shared that they observed an increase in sickle cell crises during periods of colder weather and rainfall, with one participant stating, \u003cem\u003e\u0026ldquo;[Patients] with sickle cell crisis, because of the coldness of the weather\u0026hellip; Meanwhile, they\u0026apos;re supposed to warm themselves up. But because of that, they also face that [pain] crisis during the rainy season.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #6, Female, 36 years, Midwife). Another participant elaborated on how the prevalence of asthma cases seemed to increase with the onset of the Harmattan season:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;The asthma clients visit us more, because most of them get the attacks during this weather [Harmattan season]. So, when it becomes warm, they come a lot. They get triggered.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA similar correlation between climate variability and health was observed among children, with participants noting increased upper respiratory and skin-related reactions during periods of rapid weather change:\u003cem\u003e\u0026nbsp;\u0026ldquo;Most of them [children], they come with cold, catarrh, headache, running nose, and cough. They normally come with such conditions when the weather changes\u0026hellip; And then heat rash as well\u0026rdquo;\u003c/em\u003e (Participant #9, Female, 43 years, Nurse). Malaria was also commonly mentioned, with more than half of participants highlighting the role of rainfall and stagnant water in creating mosquito breeding environments, with one participant commenting,\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cem\u003e\u0026ldquo;During the rainy season and when there are floods and stagnant water, it breeds mosquitoes\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #3, Female, 32 years, Laboratory Technician). Together, these narratives frame climate change and its impacts on health as a daily reality for FHWs.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003ePerceived link between climate change and zoonotic disease transmission\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eWhen asked directly about the relationship between climate change and zoonotic disease transmission, some participants pointed to biological and environmental mechanisms they believed could heighten outbreak risk. For instance, one participant explained,\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Increasing temperature \u0026hellip; aids viruses, bacteria, and the likes to also multiply faster and are more active. There\u0026apos;s a possibility of increased variance of those microorganisms. We expect Ebola diseases to be very serious because of climate change... and transmission very fast because of climate change.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis participant later goes on to emphasize habitat destruction, particularly deforestation and seasonal bushfires, as factors that lead to more frequent interactions between local native populations and animals:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Deforestation and dehabitation, we [humans] tend to deprive these animals from their natural habitat. So, they rather get closer to humans for shelter and for protection. And by that, they end up getting closer to us and causing zoonotic diseases to spread\u0026hellip; I know snakes. Normally in the hot seasons, they \u0026hellip; come to hide in our rooms and near human settlement, where they can take shelter, because there\u0026apos;s a lot of bush fires\u0026hellip; their cover is naturally exposed, so they have nowhere to hide, and they find themselves living amongst us.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis sentiment was followed by a few participants discussing the practices of the local Fulanese population, particularly regarding the hunting and consumption of wild animals such as monkeys. One participant remarked that wild animals \u003cem\u003e\u0026ldquo;won\u0026rsquo;t dare\u0026rdquo;\u003c/em\u003e come near town because the Fulanese locals \u003cem\u003e\u0026ldquo;will kill them before they even come.\u0026rdquo;\u003c/em\u003e (Participant #6, Female, 36 years, Midwife). Another participant added, \u003cem\u003e\u0026ldquo;They [Fulanese natives] take them [wild animals] around to eat. So they [bushmeat] are all around,\u0026rdquo;\u0026nbsp;\u003c/em\u003ereflecting perceptions of increased human\u0026ndash;animal interaction driven by both cultural practices and habitat changes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLastly, one participant suggested that extreme heat combined with overcrowded public spaces, could facilitate the transmission of infectious diseases like Ebola \u0026mdash; especially in transport settings where bodily contact is common:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;So in a hot season like this, when you sweat a lot and you sit close\u0026hellip; especially in the trotros and the taxi, before you can move your body, somebody has already pasted their whole sweat on you. So it will increase the spread of Ebola in particular.\u0026rdquo;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFHW accounts converge on three perceived mechanisms linking climate change and zoonotic diseases: human-induced environmental change, cultural practices, and dense urban living.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFHWs\u0026apos; observations of sociocultural and economic drivers of delayed Zoonotic disease care\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eParticipants described a range of culturally embedded beliefs and practices that shape how community members respond to illnesses, like zoonotic diseases. These beliefs were seen too often contribute to delayed care-seeking behavior, with implications for both individual and public health. First, many FHW participants described spiritual or religious interpretations of zoonotic disease-related illness among community members. One participant explained,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Some also believe that besides sicknesses, you have to consult the oracles. So, they go and consult the oracle to find out whether it is the cause of you having offended somebody or it is a curse that has been put on you\u0026rdquo;\u003c/em\u003e (Participant #1, Male, 56 years, Pharmacist). Another participant expanded on this idea of prayer camps as the first point of contact for individuals experiencing potentially serious or infectious conditions: \u003cem\u003e\u0026quot;Because they think it\u0026apos;s spiritual, they simply go to a prayer camp before they\u0026apos;ll think about coming to the hospital\u0026quot;\u003c/em\u003e (Participant #2, Female, 32 years, Nurse).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother adds,\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;In our setting, they believe much in this. So, everything, they will go to the prayer camp first before they\u0026apos;ll come to the hospital. And most of the time, before they\u0026apos;ll come to the hospital, their condition has gotten worse... when the prophetess or the prophet, they realize the person is about to die, they will push you to the hospital because when you die in their premises, it will spoil their business.\u0026rdquo;\u003c/em\u003e (Participant #4, Female, 39 years, Nurse)\u003c/p\u003e\n\u003cp\u003eOthers explained that when community members did eventually arrive at healthcare facilities, they sometimes imposed restrictions on the type of healthcare, as dictated by religious leaders: \u003cem\u003e\u0026nbsp;\u0026quot;They do come with their terms and conditions. The spiritual man says, you shouldn\u0026apos;t inject me or I should come for IV fluids and come back to the camp.\u0026quot;\u003c/em\u003e (Participant #9, Female, 43 years, Nurse).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to spiritual healing, participants described widespread use of herbal remedies and over-the-counter medications as initial \u0026lsquo;treatments\u0026rsquo; for zoonotic diseases before seeking formal care, with one participant noting, \u003cem\u003e\u0026ldquo;Sometimes they try with the herbal medicines. If it doesn\u0026apos;t work, then they will come\u0026quot;\u003c/em\u003e (Participant #6, Female, 36 years, Midwife). Another notes, \u003cem\u003e\u0026quot;Some also choose to medicate themselves. They go to the pharmacies, the chemical shops, and then they buy medications they feel would solve their problem for them. So, it worsens and then they come to the hospital\u0026quot;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife). All focus group participants agreed that this combination of spiritual healing and self-medication was a common practice. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFHWs further emphasized that these behaviors often contributed to delayed care, with implications for zoonotic disease spread\u003cem\u003e:\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;They will go to the prayer camp, and before the person will be rushed here, she has already infected those at the prayer camp\u0026hellip; It will spread to the community.\u0026quot;\u0026nbsp;\u003c/em\u003e(Participant # 4). One participant responds, \u003cem\u003e\u0026ldquo;It will spread like wildfire\u0026hellip; we are in trouble\u0026rdquo;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRespondents also noted that family expectations and media messaging \u0026mdash;particularly radio broadcasts\u0026mdash; influenced care-seeking pathways. One participant explained the hierarchical order that community members follow when they suspect a zoonotic disease:\u003cem\u003e\u0026nbsp;\u0026ldquo;Prophets number one, family members two. I think health workers would be the last because even the learned ones are influenced by family members to go there [prayer camps]. Maybe if you don\u0026apos;t go, they will disown you. So, prophets number one, family members number two, maybe the radio number three, and then health workers would be the last.\u0026rdquo;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife). FGD Participant #9 expands on this sentiment and states: \u003cem\u003e\u0026ldquo;We have a local radio station, Radio Ada. They have specific days that they do programs that they speak their local dialect, and then they educate them.\u0026rdquo;\u003c/em\u003e FHW responses highlight the role of the radio as a tool for community health education.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn discussing zoonotic disease detection and response within their practice, participants further described how community members often hesitated to report sick livestock due to economic concerns and limited awareness. As focus group discussion Participant #7 explained,\u003cem\u003e\u0026nbsp;\u0026ldquo;They will lose revenue\u0026hellip; Maybe they lack the knowledge about the fact that they have to report such things to the hospital. Because if my animal is sick, why should I come and tell the healthcare worker that my animal is sick?\u0026rdquo;\u003c/em\u003e Another participant added, \u0026ldquo;\u003cem\u003eI think those who are learned will rather go to the veterinary.\u0026rdquo;\u003c/em\u003e (Participant #4, Female, 39 years, Nurse). Participant #1 further noted,\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;The moment they report a sick animal to the facilities, you might tell them to quarantine it or kill them. And that will end up they losing revenue. Most of the meats we buy in the market are not certified\u0026hellip;They buy the cattle from the Fulanese and straight to the market. And we expect that before an animal is slaughtered, it has to be certified that it is healthy for human consumption. Such practices we see in the big cities and some area, but not in the country globally.\u0026rdquo;\u003c/em\u003e (Participant #1, Male, 56 years, Pharmacist)\u003c/p\u003e\n\u003cp\u003eThese insights reflect a broader perception among FHWs that low awareness and economic concerns among community members impacted their reporting of zoonotic diseases, particularly in areas where livestock trade occurs without veterinary oversight.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eInstitutional gaps in preparedness for climate-driven zoonotic threats\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eA recurring theme raised by FHWs was the reactive nature of zoonotic disease response within their current health facilities. Participants emphasized that preparedness measures \u0026mdash;such as PPE usage and isolation protocols\u0026mdash; were rarely implemented until an outbreak had already been declared. One participant explained:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;We wear PPEs only when we hear of an outbreak, and we dress like we are living on the moon\u0026hellip; Yeah, that is when the alert comes. If we don\u0026apos;t get any alert from anywhere, it might be very difficult. Because now we know Mpox \u0026hellip; We know COVID-19, the signs and symptoms we must expect. But if some of these zoonotic diseases, that its alert has not been communicated from higher centers, most of our hospitals will miss the diagnosis.\u0026quot;\u003c/em\u003e (FGD Participant #1, Male, 56 years, Pharmacist)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFHWs stressed that in emergency cases, a lack of early warning systems or accessible protective equipment often placed them at personal risk:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026quot;The person is rushed in, so before you even get to know that this is what is happening to the person, you\u0026apos;ve already gotten infected\u0026hellip; Yeah, because there\u0026apos;s no PPEs around \u0026hellip; Because when the person comes in, it\u0026apos;s an emergency. The only thing you know is putting on your gloves for you to examine the person, and before later, they will do this test... When the result comes out positive, and by then, most of the health professionals that come in contact with the person are already gotten infected.\u0026quot;\u003c/em\u003e (Participant #3, Female, 32 years, Laboratory Technician)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll participants also described a general lack of institutional guidelines for managing zoonotic disease cases. One participant noted, \u003cem\u003e\u0026quot;I think it\u0026apos;s when there is an outbreak, that is when we follow the guidelines. But as of now, that we are all sitting here, there is actually no guidelines for anyone.\u0026quot;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife). Even for more locally recognized zoonotic threats like rabies, Marburg, or Ebola, participants reported limited awareness of existing protocols, with one participant stating, \u003cem\u003e\u0026ldquo;When it comes to rabies, we don\u0026apos;t have protocols that we follow but we a [have] treatment. So, I don\u0026apos;t know of any of them\u0026hellip; No, I\u0026apos;m not aware of that [protocols for Marburg or Ebola].\u0026rdquo;\u003c/em\u003e (Participant #6, Female, 36 years, Midwife)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurthermore, respondents described minimal access to ongoing training. One participant mentioned that the only recent opportunity to refer their knowledge had been through informal clinical meetings, which had not occurred in a long time. This point was elaborated on by another participant,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026ldquo;\u003c/em\u003e\u003c/strong\u003e\u003cem\u003eTraining, workshops. Because I don\u0026apos;t remember the last time there was any workshop in this country to that effect, even in Ada. You know, nursing is dynamic\u0026hellip; You get to know what next step to take or what you should expect if you get a case like this\u0026hellip; You can attest that most of us, it\u0026apos;s been a very long time we even enter our books, open the books to look at what is going on. So, some of these things it helps. It freshens your memory. You might have forgotten about something, but with this, it [protocols would] freshens your memory.\u0026rdquo;\u003c/em\u003e (Participant #9, Female, 43 years, Nurse)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the absence of formal systems, participants relied heavily on informal communication networks to stay informed about zoonotic outbreaks and climate-related updates. These included personal Google searches, professional WhatsApp groups, and information shared by family members. As one participant explained,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Now Google is closer to us, so on our phones, you just speak into Google, and all the information, the good, the bad, and the ugly will get to you. Better still, you want to look at Google Scholar\u0026hellip; Where there are intellectual rights of people that have conducted researches and studies that you can read\u0026hellip; Because for them, you know, it has been peer reviewed. No one head wrote it, so it has gone through a lot of corrections and a lot of editing so that the truth actually stands out.\u0026rdquo;\u003c/em\u003e (Participant #1, Male, 56 years, Pharmacist)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother respondent added, \u0026ldquo;\u003cem\u003eSometimes, they post this [information] on our [WhatsApp] page, there is an update\u0026hellip; Our family members keep calling, so they will update us.\u003c/em\u003e\u0026quot; (FGD Participant #6, Female, 36 years, Midwife). One respondent stated, \u003cem\u003e\u0026ldquo;Ask AI\u0026rdquo;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFHWs expressed a strong desire for more structured and formal training workshops, ideally organized by the Ministry of Health (MOH) or other governmental bodies. These workshops were viewed as more trustworthy and effective than piecemeal updates:\u003cem\u003e\u0026ldquo;[We prefer] Workshop, because the researcher or the person who is presenting has done his research. He has done his findings. And the person also is an expert in what he or she is talking about.\u0026rdquo;\u003c/em\u003e (Participant #2, Female, 32 years, Nurse).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn terms of their own practices, participants described small-scale institutional actions to mitigate environmental risks driving zoonotic outbreaks, such as conserving electricity, turning off unused appliances, or switching to energy-saving bulbs:\u003cem\u003e\u0026nbsp;\u0026quot;When we come, let\u0026apos;s say the lights. The lights, when they are not in use, we put them off to preserve energy. And the electrical appliances\u0026hellip; we put them off to preserve energy.\u0026quot;\u003c/em\u003e (Participant #4, Female, 39 years, Nurse). \u003cem\u003eAnother respondent notes, \u0026quot;We try and light the energy-saving bulbs. Fridges and other things, we buy the energy-saving ones so that we can save energy\u0026quot;\u0026nbsp;\u003c/em\u003e(Participant #5, Female, 51 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThey also shared their vision for broader community education on the link between climate change and zoonoses:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Bats, yes. They should desist from killing such animals or even any sick animal around them. They should desist from killing and bringing it to the market to sell them. Secondly, we will talk about the fact that if there is any sick person in the community, they shouldn\u0026apos;t treat themselves. They should come to the facility for health care. The third thing would be the mode of transmission. Body fluids, they should wash their hands often, keep their environment clean, and all these things. And then lastly, if there is even a death in the community, they should bring their body to the health facility because they do not know exactly what killed that particular person.\u0026rdquo;\u003c/em\u003e (Participant #7, Female, 28 years, Midwife)\u003c/p\u003e\n\u003cp\u003eThese comments reflect FHWs\u0026rsquo; emphasis on the importance of discouraging bushmeat consumption, promoting proper hygiene, and encouraging timely reporting of unexplained illnesses or deaths within the community.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFHWs\u0026rsquo; perceived stakeholder roles and call for action in addressing the climate-zoonosis nexus\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eParticipants widely agreed that addressing the dual impact of climate change and zoonotic disease requires multisectoral collaboration, particularly between meteorological agencies, the Ministry of Environment, Science and Technology, and health authorities. One participant suggested:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Inter-sectoral collaboration, where governments would coordinate between the Ministry of Environment, Science and Technology\u0026hellip; so that we can be informed that instead of expecting rain, we should expect very dry seasonal conditions... So that at least, they say to be forewarned \u0026hellip; about what we should expect might tell us as to what kind of [zoonotic] diseases we are about.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist)\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis same participant, echoing the views of others, further described FHWs as implementers of policies handed down from district or regional health directorates, noting that district directors \u0026mdash;many of whom are public health specialists\u0026mdash; play a strong coordinating role:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;Almost all our district directors are public health specialists\u0026hellip; When there is any outbreak, direction and guidance will certainly come from them\u0026hellip; We will still fall on the district that will also fall on the regional health directorate for guidance and direction. We here basically are more or less like policy implementers who will implement whatever policy that comes from higher centers\u0026hellip; In question, with this cholera outbreak, I realized that was when I had more contact with the district director than anything more. He would call me, do you have this, we are expecting this medicine to come. They will bring it today; come and receive it.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGovernmental actors were also perceived as critical in building resilient infrastructure and protecting environmental resources to reduce future risks:\u003cem\u003e\u0026nbsp;\u0026ldquo;I think that the government should build a new facility for us here, a well-equipped one that, regardless of whether it\u0026apos;s a zoonotic disease or a normal illness, you know that the people are receiving good care.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #1, Male, 56 years, Pharmacist). The role of the government was further noted on by another participant who stated,\u003cem\u003e\u0026nbsp;\u0026quot;The government should see to it that our forests are being reserved. By preventing this deforestation and waste that force the wild animals to lose their habitats.\u0026quot;\u0026nbsp;\u003c/em\u003e(Participant #4, Female, 39 years, Nurse). In addition to these comments, one FHW adds,\u003cem\u003e\u0026nbsp;\u0026ldquo;I think the previous governments wanted us to be having this planting of trees. I don\u0026apos;t know how far that thing went, but I think it\u0026apos;s a good idea. The planting of trees will help ease the scorching sun on our head.\u0026rdquo;\u003c/em\u003e (FGD Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll FHWs in the discussion called for more infectious disease centers, quicker diagnostic access, and adequate supplies like PPE and medications \u0026mdash;needs described as basic yet unmet:\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026ldquo;We don\u0026apos;t even have an isolation place\u0026hellip; If we are able to identify an infectious disease at the district hospital, we straight away refer to a specialized center where they can handle professionally, rather than trying to manage them with the general knowledge that we have. As the pharmacist sitting here, if you ask me what are the medicines we used to mitigate the spread of Ebola, I may have to refer\u0026hellip; Resources to manage such patients must have to come from the headquarters\u0026hellip; PPE has to come from Central Medical Store... Per our facilities, those things were finished when we last heard of COVID.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(FGD Participant #1, Male, 56 years, Pharmacist)\u003c/p\u003e\n\u003cp\u003eOthers stressed the need for rapid testing, with one participant stating, \u003cem\u003e\u0026ldquo;With something like Ebola, for us to diagnose it, they will say take a sample, bring it a place. We cannot do it in our facility. If we could have the places close by\u0026hellip; it won\u0026rsquo;t take 3 days or one week for us to know because we are at risk here.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #7, Female, 28 years, Midwife). One participant captured these sentiments, voicing the concern shared by many frontline staff: \u003cem\u003e\u0026quot;With this not prepared, not having an isolation bay, and then the way the people in the community, their attitude towards certain conditions, we are in trouble.\u0026quot;\u0026nbsp;\u003c/em\u003e(Participant #9, Female, 43 years, Nurse) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRespondents also emphasized that FHWs themselves deserved greater recognition, protection, and compensation, particularly during zoonotic outbreaks potentially exacerbated by climate change: \u003cem\u003e\u0026ldquo;We are the frontline health workers. There should be some kind of assurances that we would have, that even though you are the frontline, taking care of people, if you get infected, your medications are free, maybe you will be given this amount of money. COVID, we heard about those things, but truthfully, it didn\u0026apos;t work. I never received any of that money.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEnthusiasm for continued engagement in research on zoonotic disease and climate change was palpable, with participants seeing research as a means to both document on-the-ground realities and inform policy. However, they also voiced a strong desire that their participation be followed by meaningful implementation. \u003cem\u003e\u0026ldquo;I hope that this wouldn\u0026apos;t be the only research that will be done, because there are a lot of diseases that are coming up. And we would like you people to know how best we know the diseases and how best we handle them, and what the government should do about it because it\u0026apos;s these researches that informs them of our knowledge on the grounds and what is being done. So, my hope is that in future, there\u0026apos;ll be more researches and then most important, there\u0026apos;ll be implementation of them.\u0026rdquo;\u0026nbsp;\u003c/em\u003e(Participant #7, Female, 28 years, Midwife).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnother FHW echoed this sentiment, concluding the discussion by stating:\u003cem\u003e\u0026nbsp;\u0026quot;I hope it doesn\u0026apos;t end here. We hope that with all that we brought out, it can be linked for something to be done because\u0026hellip; we don\u0026apos;t have isolation bay, we spoke of lack of gadgets to work with, we spoke of staff, and we spoke of staff welfare, and even medications itself. I don\u0026apos;t think this should be just about coming to waste our time... Not just coming to sit us down and then go further and then off you go. It should be channeled to the right people. We want to see a change.\u0026quot;\u0026nbsp;\u003c/em\u003e(Participant #9, Female, 43 years, Nurse). It is clear that FHWs are calling for action, especially as it relates to diagnostics, PPE provision, staffing, and operational guidance when preparing for climate-sensitive zoonotic diseases.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis mixed-methods study offers a critical district-level examinations of Ghanaian FHWs\u0026rsquo; knowledge, attitudes, and practices (KAP) regarding the climate-zoonosis nexus. Additionally, our analysis of how frontline health workers in Ghana perceive and respond to the interconnected challenges of climate change and zoonotic diseases illustrates how climate change is understood and addressed within a health system that faces both resource constraints and increasing environmental pressures. These findings indicate strong baseline awareness among FHWs along with critical gaps in system preparedness. Addressing these challenges will require multisectoral collaboration, investments in infrastructure and diagnostics, and concrete steps to translate policy commitments into frontline practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHigh experiential knowledge as an early warning resource for climate-health risks\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur findings suggest that FHWs in Ada East, Ghana, are well-informed of climate change\u0026rsquo;s impacts on health, especially regarding zoonotic diseases. This high awareness positions them as \u0026ldquo;climate-health sentinels\u0026rdquo; who can provide early warnings of climate-driven zoonotic threats. Quantitatively, 95.6% of respondents correctly identified how changing climate patterns can drive infectious disease outbreaks. Many also reported climate-linked shifts in patient cases \u0026mdash;particularly air-quality-related illnesses, heat-related conditions, and allergic reactions. This experiential, place-based knowledge is valuable as a first signal for emerging zoonotic risks.\u003c/p\u003e\n\u003cp\u003eQualitative insights reinforced these patterns and illustrated how providers mechanistically linked climate phenomena to everyday health outcomes. For example, participants described erratic rainfall leading to more stagnant water and mosquito breeding, coinciding with spikes in malaria; dry, dusty Harmattan winds aggravating respiratory illnesses like asthma; prolonged cool and wet periods triggering increases in sickle cell crises; and heat waves bringing surges in heat rashes and dehydration. Some also observed that during very hot, dry periods, wildlife encroach closer to homes (e.g., bats or snakes seeking water), increasing human-animal contact and the risk of zoonotic disease spillover. These frontline observations align with broader evidence that climate variability is amplifying health burdens and could accelerate zoonotic spillover under future warming [13, 18\u0026ndash;24, 32, 83].\u003c/p\u003e\n\u003cp\u003eGhana\u0026rsquo;s frontline providers are already detecting signals that may foreshadow larger public health threats, as evidenced in our findings, underscoring the value of their experiential knowledge as a complement to formal surveillance data systems [65, 66, 69\u0026ndash;72]. Their on-the-ground observations mirror trends documented in climate-health literature and echo global calls to empower healthcare professionals as sentinels and educators at the climate-zoonosis nexus [65, 66, 69\u0026ndash;72].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo leverage this local knowledge, health systems should establish formal channels for frontline staff to share climate-linked clinical observations [68, 71, 72]. For instance, routine debriefings or monthly meetings could be instituted for frontline staff to report any unusual case patterns following heat waves, floods, or other weather extremes. Systematically capturing these insights would strengthen surveillance and shorten the lag between the onset of zoonotic outbreaks and a public health response [66, 70]. In essence, incorporating FHWs\u0026rsquo; experiential reports into early warning systems can enrich One Health monitoring at the grassroots level [66]. Such community-based reporting is a cornerstone of proposed One Health early warning frameworks, which emphasize that empowering local actors is essential for timely, coordinated outbreak preparedness [66, 79]. We recommend that Ghana\u0026rsquo;s health authorities pilot mechanisms to integrate frontline climate-health intelligence into district surveillance \u0026mdash;a low-cost step that could enhance national outbreak alert systems [67, 69, 79].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssessment of knowledge gaps through a One Health lens\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile Ada East FHWs readily recognized direct clinical impacts of climate change, we also found significant knowledge gaps regarding broader climate-health pathways. In particular, the understanding of the One Health dimensions was limited. Few respondents were aware of how agricultural and livestock practices contribute to climate change, despite agriculture being a primary anthropogenic driver of land-use change and greenhouse gas emissions in Ghana [38\u0026ndash;42, 45, 51, 84]. Fewer than one-third connected climate change to psychosocial health outcomes, such as stress, anxiety, or social conflict, and recognition of especially vulnerable groups like children, older adults, or women was low despite evidence that these groups face heightened climate-related health risks [85\u0026ndash;87]. Notably, we found that attending highly vertical, disease-focused workshops \u0026mdash;namely, trainings on monkeypox\u0026mdash; was associated with lower overall climate-health knowledge scores. This counterintuitive finding may suggest that siloed training programs might isolate diseases from their environmental context, leaving providers less attuned to how climate and ecological changes influence disease emergence and connect to broader One Health dimensions [74].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAddressing these identified gaps will require retooling health education toward a more holistic, One Health perspective. Educators could expand pre-service curricula and in-service training to include underrepresented climate-health topics such as agriculture-driven greenhouse gas emissions, the dynamics of wildlife-livestock-human interfaces, and the mental health implications of climate change [74, 79]. We also suggest using locally relevant, case-based teaching that explicitly links recent climatic events to changes in disease patterns; for example, analyzing how a recent flood coincided with leptospirosis clusters, a drought with anthrax events, or a heatwave with bat-human contact and Marburg risk in the district. This approach would ensure that even specialized zoonotic disease training is contextualized within the broader climatic and environmental landscape [23]. By integrating One Health concepts into training and continuous professional development, as urged by international frameworks, Ghana\u0026rsquo;s health workforce may better anticipate indirect and multi-sectoral drivers of climate-driven zoonotic outbreaks [66, 73, 79, 88\u0026ndash;90].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFrom individual initiative to institutional preparedness\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDespite strong knowledge and positive attitudes, a clear gap remains between frontline workers\u0026rsquo; personal climate-friendly behaviors and their institutions\u0026rsquo; climate\u0026ndash;zoonotic preparedness. Most respondents reported engaging in low-cost individual-level actions\u0026mdash;such as conserving water, turning off unused equipment, or using cleaner cookstoves\u0026mdash;yet fewer than 12% reported \u0026ldquo;Good\u0026rdquo; climate mitigation practices at the facility level. Focus group narratives further noted that frontline staff often take a reactive stance to climate-driven zoonotic threats. Essential resources \u0026mdash;including PPE, emergency protocols, or climate-focused guidelines\u0026mdash; typically arrive after a crisis begins rather than as preventative measures. Smaller community-based clinics (e.g., CHPS compounds) were positively associated with better climate mitigation practices, whereas larger district hospitals were less engaged in these measures. This pattern of strong individual engagement in climate mitigation but weak institutional climate-zoonotic preparedness might indicate that structural barriers are limiting the translation of frontline commitment into system-wide resilience.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClosing this practice gap will require deliberate support from health authorities to climate-proof health facilities as an indirect means to reduce the risk of zoonotic disease and empower staff-led initiatives [37, 68, 72]. Investments are needed to upgrade infrastructure and operations for a climate-resilient approach to zoonotic preparedness [24, 91]. Ensuring essential medicines, vaccines, and supplies are pre-positioned in anticipation of climate-related events, rather than delivered only in emergency response, is another crucial step for zoonotic preparedness [92, 93].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur data also underscore the importance of training and information flow in driving climate-informed zoonotic preparedness. Both quantitative and qualitative results identified training exposure as a key predictor of good climate-friendly practices. Notably, FHWs who had participated in NGO-led training workshops reported better climate-health practices than those trained through government programs. Participants explained that most official training on emerging zoonotic diseases in the backdrop of climate change is infrequent, prompting them to rely on ad-hoc sources like WhatsApp groups or personal internet searches to fill knowledge gaps. This indicates an opportunity to improve not just the content, but also the delivery of training. Instituting regular, hands-on drills and learning modules focused on climate-related health emergencies may prove beneficial. Developing these trainings in collaboration with frontline staff would ensure they are relevant to local realities, and embedding such exercises and discussions into routine continuing education would keep climate preparedness at the forefront of FHWs\u0026rsquo; minds [24, 37, 52, 66, 69, 71, 74, 86, 93]. It would also address the anxiety FHWs voiced about being \u0026ldquo;in trouble\u0026rdquo; during a major zoonotic outbreak if left unprepared.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRespondents expressed frustration that national climate-health policies and plans often do not translate into tangible support for the local staff. To remedy this, participatory governance mechanisms should be strengthened, for example, via the creation of local climate-health focal points or committees within each district where frontline workers can both receive updates on policies and feed their experiences upward [66, 67, 69, 72, 74, 93]. Regular forums for FHWs to voice needs \u0026mdash;such as reporting PPE shortages or flagging upticks in certain illnesses that could signal zoonotic emergence\u0026mdash; would help decision-makers allocate resources more responsively [71, 92, 93].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocio-cultural and economic barriers to rapid outbreak response\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCommunity-level factors identified by FHWs, including economic pressures, health-seeking behaviors, and long-standing livelihood practices, seem to strongly shape how quickly climate-sensitive zoonotic threats are detected and addressed. This study highlighted that effective preparedness must therefore extend beyond health facilities into the community, since even well-trained staff and better-equipped clinics cannot overcome delays rooted in the community context. FHWs in Ada East observed that patients\u0026rsquo; economic vulnerabilities heavily influenced their care-seeking practices. Similarly, FHWs reported that farmers also rarely report strange illnesses or deaths in their livestock, often out of fear of losing income or because there are no clear mechanisms to do so. These identified gaps signal that animal warning signs, which serve as potential precursors to human outbreaks, are frequently missed. Future research should explore how economic and food insecurity may impact both climate mitigation practices and zoonotic disease reporting.\u003c/p\u003e\n\u003cp\u003eCultural beliefs and trust in traditional medicine seem to further shape health-seeking behaviors within the community. Participants explained that sudden illness is frequently attributed to spiritual causes, prompting families to seek help first from prayer camps, faith healers, or herbalists. While these practices remain central to community life, FHWs stressed that they delay engagement with the formal health system. They warned that a fast-spreading zoonosis like Ebola could \u003cem\u003e\u0026ldquo;spread like wildfire\u0026rdquo;\u003c/em\u003e if patients remain at home or in spiritual centers without timely diagnosis and isolation. Even when families choose biomedical care, further delays arise when individuals first try self-medication or over-the-counter drugs, often arriving at clinics only when the illness has advanced.\u003c/p\u003e\n\u003cp\u003eAddressing these socio-cultural challenges will require proactive engagement and multi-sector collaboration [38\u0026ndash;40, 43, 68, 69, 71]. Public health authorities should work with trusted local leaders to improve understanding of climate-driven zoonotic risks and foster trust in early reporting [69, 71]. Outreach campaigns can respect cultural traditions while stressing that specific symptoms or unusual illness clusters require immediate medical attention [39, 86]. Leveraging local media, such as Radio Ada, offers promising channels for tailored communication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study\u0026rsquo;s concurrent mixed-methods design provided a more nuanced understanding of FHWs\u0026rsquo; KAP regarding climate change and its link to zoonotic disease. This Ghana district, the Ada East District of Ghana\u0026rsquo;s Greater Accra Region., where the study was conducted, has demographic and geographic diversity \u0026mdash;encompassing urban, peri-urban, and rural areas\u0026mdash; and its high concentration of healthcare facilities staffed by a range of clinical personnel, including nurses, midwives, pharmacists, community health officers, and physicians. The district\u0026rsquo;s dual role as a hotspot for climate-sensitive diseases and a frontline hub for outbreak response made it a highly relevant setting for this study. The survey quantified levels of knowledge, attitudes, and practice, while the focus group offered a platform for FHWs to expand on existing barriers to climate-linked zoonoses preparedness and how providers interpret the challenges they face. The qualitative data added depth and context to the survey findings, strengthening credibility through triangulation. We used validated questions where possible and applied rigorous thematic analysis, grounding findings in participants\u0026rsquo; own statements and experiences. The relatively large and diverse sample spanned multiple facility types and professional roles, enhancing the transferability of findings to similar coastal districts in Ghana and increasing their relevance for district-level health planning.\u003c/p\u003e\n\u003cp\u003eHowever, several limitations should be acknowledged. First, the cross-sectional design prevents causal inference. Second, sampling in a single district limits generalizability, as climate\u0026ndash;health awareness may differ in other regions with distinct exposures, health systems, or socio-cultural contexts. That said, Ada East includes urban, peri-urban, and rural facilities, offering a reasonable cross-section for a climate-vulnerable coastal zone. Third, all data were self-reported, raising the possibility of social desirability and recall bias. We attempted to reduce this risk by assuring anonymity and clarifying that the survey was not an evaluation of job performance. We encouraged the frontline staff to describe system gaps they perceive openly. Fourth, thresholds for \u0026ldquo;Good\u0026rdquo; practice or attitude (\u0026ge;60%) were based on Bloom\u0026rsquo;s taxonomy, a common approach in KAP studies but inherently arbitrary. Finally, the qualitative component involved only one focus group (n=9). Although we sampled diverse roles within the discussion, some perspectives, particularly from those who did not volunteer for the focus group discussion, may not have been captured. Despite these limitations, the consistency we observed between quantitative trends and qualitative narratives lends confidence to the robustness and credibility of our findings. Together, they provide a valuable baseline for future longitudinal or multi-site research on climate\u0026ndash;health preparedness among frontline health workers.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGhana\u0026rsquo;s frontline healthcare workers are a critical yet underutilized resource in the national response to climate-sensitive zoonotic threats. They offer valuable experiential knowledge, practical observational skills, and community trust, coupled with a willingness to act. However, conceptual gaps, structural limitations, and social, cultural, and economic barriers hinder the translation of these strengths into sustained institutional preparedness. Bridging this gap requires targeted training, empowerment structures at the facility level, cross-sectoral early-warning systems, and climate-resilient infrastructure. Building on the strengths already present, such as practical observational capacity, media engagement, and community trust, may accelerate climate mitigation efforts and reduce the risk of climate-driven zoonotic outbreaks. Investment in these frontline actors is also an investment in both national health security and global pandemic prevention.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eResearch Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received ethical approval from both the Ghana Health Service Ethical Review Committee (protocol GHS‑ERC 024/08/24) and the Pennsylvania State University Institutional Review Board (STUDY00025492). Written authorization to conduct the study was also obtained from the administrative leadership of all eighteen participating health facilities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA.N.Y. conceived and designed the project, developed the data collection instrument, coordinated data collection, performed data analysis, and drafted and finalized the manuscript.\u003cbr\u003e\u0026nbsp;K.P.W. contributed to data management, analysis, and manuscript preparation.\u003cbr\u003e\u0026nbsp;H.E.S. participated in the review of the survey instrument and qualitative data analysis.\u003cbr\u003e\u0026nbsp;K.K.S. assisted in the study design, reviewed the manuscript for scientific content, and provided critical revisions.\u003cbr\u003e\u0026nbsp;G.H., L.B., E.K., and C.L.N. contributed to data collection, review of study instruments, and manuscript review.\u003cbr\u003e\u0026nbsp;K.T.R. and A.T.G. reviewed and provided input on the manuscript.\u003cbr\u003e\u0026nbsp;M.A.K. supervised the final analysis, contributed to the interpretation of results, and finalized the results and discussion sections.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Institute of Energy and the Environment (IEE) at Penn State University [IO Number: 46000000820]. The funders had no role in the design of the study, data collection, analysis, interpretation of data, or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe want to sincerely thank the University of Ghana for facilitating this work and the local data collectors for their dedication in the field. We are especially grateful to the frontline health care workers in Ada East, Ghana, whose participation and insights informed this study and, we hope, will help catalyze change.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are not publicly available due to confidentiality restrictions but can be made available upon reasonable request and collaboration with the corresponding authors (A.N.Y. and M.A.K.).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWhat Is Climate Change? - NASA Science. (2022, June 15). Retrieved from https://science.nasa.gov/climate-change/what-is-climate-change/\u003c/li\u003e\n\u003cli\u003eZell, R. (2004). 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The Stanford Climate Change Behavior Survey (SCCBS): assessing greenhouse gas emissions-related behaviors in individuals and populations. \u003cem\u003eClimatic Change\u003c/em\u003e, \u003cem\u003e109\u003c/em\u003e(3), 671\u0026ndash;694. https://doi.org/10.1007/s10584-011-0031-y\u003c/li\u003e\n\u003cli\u003eCollecting Data. (n.d.). \u003cem\u003eOne Health Behaviors\u003c/em\u003e. Retrieved from https://onehealthbehaviors.org/research/\u003c/li\u003e\n\u003cli\u003eCDC. (2025, June 4). Completed OHZDP Workshops. \u003cem\u003eOne Health\u003c/em\u003e. Retrieved June 7, 2025, from https://www.cdc.gov/one-health/php/prioritization/completed-workshops.html\u003c/li\u003e\n\u003cli\u003eZinsstag, J., Crump, L., Schelling, E., Hattendorf, J., Maidane, Y. O., Ali, K. O., \u0026hellip; Ciss\u0026eacute;, G. (2018). Climate change and One Health. \u003cem\u003eFEMS Microbiology Letters\u003c/em\u003e, \u003cem\u003e365\u003c/em\u003e(11), fny085. https://doi.org/10.1093/femsle/fny085\u003c/li\u003e\n\u003cli\u003eCDC. (2024, May 16). About Zoonotic Diseases. \u003cem\u003eOne Health\u003c/em\u003e. Retrieved June 7, 2025, from https://www.cdc.gov/one-health/about/about-zoonotic-diseases.html\u003c/li\u003e\n\u003cli\u003eMohamud, A. K., Ali, I. A., Ali, A. I., Dirie, N. I., Inchon, P., Ahmed, O. A., \u0026amp; Mohamud, A. A. (2023). Assessment of healthcare workers\u0026rsquo; knowledge and attitude on Ebola virus disease in Somalia: a multicenter nationwide survey. \u003cem\u003eBMC Public Health\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e(1), 1650. https://doi.org/10.1186/s12889-023-16562-2\u003c/li\u003e\n\u003cli\u003eWang, L., Abualfoul, M., Oduor, H., Acharya, P., Cui, M., Murray, A., \u0026hellip; Pagadala, M. (2022). A cross-sectional study of knowledge, attitude, and practice toward COVID-19 in solid organ transplant recipients at a transplant center in the United States. \u003cem\u003eFrontiers in Public Health\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e. https://doi.org/10.3389/fpubh.2022.880774\u003c/li\u003e\n\u003cli\u003eWilloughby, A. R., Phelps, K. L., PREDICT Consortium, \u0026amp; Olival, K. J. (2017). A Comparative Analysis of Viral Richness and Viral Sharing in Cave-Roosting Bats. \u003cem\u003eDiversity\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(3), 35. https://doi.org/10.3390/d9030035\u003c/li\u003e\n\u003cli\u003eAcheampong, E. O., Macgregor, C. J., Sloan, S., \u0026amp; Sayer, J. (2019). Deforestation is driven by agricultural expansion in Ghana\u0026rsquo;s forest reserves. \u003cem\u003eScientific African\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, e00146. https://doi.org/10.1016/j.sciaf.2019.e00146\u003c/li\u003e\n\u003cli\u003eExperts warn of serious health impacts from climate change for pregnant women, children, and older people. (2024). \u003cem\u003eSaudi Medical Journal\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e(7), 754\u0026ndash;755. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11237281/\u003c/li\u003e\n\u003cli\u003eSorensen, C., Murray, V., Lemery, J., \u0026amp; Balbus, J. (2018). Climate change and women\u0026rsquo;s health: Impacts and policy directions. \u003cem\u003ePLoS Medicine\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(7), e1002603. https://doi.org/10.1371/journal.pmed.1002603\u003c/li\u003e\n\u003cli\u003eUS EPA, O. (2022, March 21). Climate Change and the Health of Older Adults. Overviews and Factsheets. Retrieved August 23, 2025, from https://www.epa.gov/climateimpacts/climate-change-and-health-older-adults\u003c/li\u003e\n\u003cli\u003eAhmed, M. M., Okesanya, O. J., Othman, Z. K., Ibrahim, A. M., Adigun, O. A., Ukoaka, B. M., \u0026hellip; Lucero-Prisno, D. E. (2025). Holistic Approaches to Zoonoses: Integrating Public Health, Policy, and One Health in a Dynamic Global Context. \u003cem\u003eZoonotic Diseases\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(1), 5. https://doi.org/10.3390/zoonoticdis5010005\u003c/li\u003e\n\u003cli\u003eAmuguni, H., Bikaako, W., Naigaga, I., \u0026amp; Bazeyo, W. (2019). Building a framework for the design and implementation of One Health curricula in East and Central Africa: OHCEAs One Health Training Modules Development Process. \u003cem\u003eOne Health (Amsterdam, Netherlands)\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e, 002\u0026ndash;002. https://doi.org/10.1016/j.onehlt.2018.08.002\u003c/li\u003e\n\u003cli\u003eCDC. (2025, May 14). About One Health. \u003cem\u003eOne Health\u003c/em\u003e. Retrieved June 7, 2025, from https://www.cdc.gov/one-health/about/index.html\u003c/li\u003e\n\u003cli\u003eCodjoe, S. N. A., \u0026amp; Owusu, G. (2011). Climate change/variability and food systems: evidence from the Afram Plains, Ghana. \u003cem\u003eRegional Environmental Change\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(4), 753\u0026ndash;765. https://doi.org/10.1007/s10113-011-0211-3\u003c/li\u003e\n\u003cli\u003eEcoHealth Alliance. (2021, April). Strengthening Pandemic Preparedness in Ghana.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2024). 2024 Annual Report WHO Ghana. Regional Office for Africa. Retrieved from https://www.afro.who.int/sites/default/files/2025-06/WHO%20Ghana%202024%20Annual%20Report.pdf\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Climate change, Zoonotic diseases, Knowledge, attitudes and practices (KAP), Frontline healthcare workers, One Health, West Africa","lastPublishedDoi":"10.21203/rs.3.rs-8282544/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8282544/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction\u003c/h2\u003e \u003cp\u003eClimate change alters patterns of infectious diseases and increases the risk of zoonotic spillover in vulnerable areas. This study examines how frontline healthcare workers (FHWs) in Ghana\u0026rsquo;s Ada East District understand and perceive the relationship between climate change and zoonotic disease transmission.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a concurrent mixed-methods study in the Ada East District, Ghana. A cross-sectional survey of FHWs evaluated knowledge, attitudes, and practices (KAP) regarding climate change and its link to zoonotic diseases. KAP scores were classified using Bloom\u0026rsquo;s cutoffs; adjusted logistic regression models identified predictors of good KAP. A purposively selected focus group (n\u0026thinsp;=\u0026thinsp;9) explored perceived links between climate change and zoonotic disease, lived experiences, and institutional barriers.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eMost participants demonstrated good knowledge (\u0026ge;60% correct; 83.2%) and attitudes (\u0026ge;60% positive attitudes; 86.8%), but fewer reported good climate-mitigation practices (\u0026ge;60% of good practices; 62.4%). Clinical staff other than nurses and midwives were associated with higher odds of good knowledge (adjOR\u0026thinsp;=\u0026thinsp;4.52, 95% CI 1.12\u0026ndash;22.76), while those trained on the human monkeypox virus were associated with lower odds of good knowledge (adjOR\u0026thinsp;=\u0026thinsp;0.24, 95% CI 0.08\u0026ndash;0.64). For practices, working in a district/regional hospital was associated with lower odds (adjOR\u0026thinsp;=\u0026thinsp;0.18, 95% CI 0.05\u0026ndash;0.61), as was training delivered by Ministry/Government authorities (adjOR\u0026thinsp;=\u0026thinsp;0.44, 95% CI 0.21\u0026ndash;0.91) and training on human monkeypox virus (adjOR\u0026thinsp;=\u0026thinsp;0.39, 95% CI 0.17\u0026ndash;0.90). Providers associated land-use change and bushmeat hunting with zoonotic spillover risk. They noted that spiritual beliefs, self-medication, and fear of income loss delayed care-seeking for suspected cases. Institutional preparedness was perceived as reactive. Participants called for climate-resilient infrastructure, integrated early-warning systems, and One Health training.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eFHWs in Ghana\u0026rsquo;s Ada East District are knowledgeable and motivated to address climate-sensitive zoonotic risks. Yet, structural and sociocultural barriers limit the translation of frontline commitment into system-wide resilience. Strengthening climate-health education, investing in facility-level preparedness, and integrating FHW insights into surveillance could enable a shift from reactive outbreak response to proactive, community-based preparedness.\u003c/p\u003e","manuscriptTitle":"Frontline knowledge, attitudes, and practices on climate change and its link to zoonotic diseases: a mixed-methods study of healthcare workers in Ada East, Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-22 09:16:34","doi":"10.21203/rs.3.rs-8282544/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-16T08:30:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T03:09:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"40100598806658928099783659059814202552","date":"2026-01-02T11:18:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-30T02:25:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"170891473495415844335093443113401387232","date":"2025-12-17T15:28:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-12T13:49:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-05T12:06:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-05T12:02:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2025-12-04T20:44:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"91de5320-246e-461e-8611-2c04c65234e0","owner":[],"postedDate":"December 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:01:37+00:00","versionOfRecord":{"articleIdentity":"rs-8282544","link":"https://doi.org/10.1186/s12982-026-01622-w","journal":{"identity":"discover-public-health","isVorOnly":false,"title":"Discover Public Health"},"publishedOn":"2026-03-04 15:58:08","publishedOnDateReadable":"March 4th, 2026"},"versionCreatedAt":"2025-12-22 09:16:34","video":"","vorDoi":"10.1186/s12982-026-01622-w","vorDoiUrl":"https://doi.org/10.1186/s12982-026-01622-w","workflowStages":[]},"version":"v1","identity":"rs-8282544","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8282544","identity":"rs-8282544","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}