The Status of Public Health Emergency Preparedness and Response in the War-Ridden Tigrai, Ethiopia: A descriptive study benchmarking the Competency Framework

The Status of Public Health Emergency Preparedness and Response in the War-Ridden Tigrai, Ethiopia: A descriptive study benchmarking the Competency Framework | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Status of Public Health Emergency Preparedness and Response in the War-Ridden Tigrai, Ethiopia: A descriptive study benchmarking the Competency Framework Meresa Gebremedhin Weldu, Mache Tsadik Adhana, Akeza Awalom Asgedom, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5312606/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: Public health emergency preparedness and readiness stand for quickly obtaining and effectively using relevant information and resources to improve the efficiency of emergency response to minimize harm and negative impacts. Ethiopia has been used to pursue health emergency procedures for decades; however, there is a paucity of scientific evidence. This study aimed to assess public health emergency preparedness and response benchmarking in the competency framework within the local context during the postwar period in Tigrai, Ethiopia. Methods: A quantitative cross-sectional study was carried out using semi-structured piloted interviewer-administered tools extracted from the core domains of the competency framework to collect the necessary data. The study included 110 randomly selected health institutions (primary hospitals, N=9; health centers, N=23; health posts, N=54; and district health offices, N=24. An Open Data Kit was used to collect the data, which were then exported to SPSS version 27 for data analysis. Finally, the overall status of preparedness and readiness was classified as low if the percentage score was 33%-66.6% and high if it was 66.7%-100%. The data are presented in text narratives, graphs and tables. Results : More than half (53.1%) of the district health offices, 54.6% of the primary hospitals, and 52.2% of the health centers in the study area have no specific health emergency plans. Similarly, more than half (53.1%) of the districts, 52.2% of the health centers and 66.6% of the primary hospitals did not report outbreak-prone diseases. More than fifty-six percent of the health centers, 59.4% of the districts and almost two-thirds (66.6%) of the primary hospitals reported that they failed to investigate and treat the outbreaks observed in the study area. Conclusions : The current findings revealed that primary health care units, along with district health offices, were challenged in maintaining basic health emergency preparedness and readiness. Disease surveillance, readiness and response with a collaborative and coordinated action of the region and stakeholders was unacceptably low. Thus, strengthening supervision, proper health emergency planning, digitalizing swift reporting activities and establishing functional regional links through intensified training of health professionals at all levels of health services are recommended. Health emergency preparedness and response competency framework Tigrai Ethiopia Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Background Public health emergencies are defined as unexplained diseases, major food or drinking water and occupation poisoning, and other serious public health events that suddenly occur, thereby causing major infectious diseases or even serious damage to public health groups ( 1 ). The health impacts of infectious disease outbreaks and other disasters have demonstrated the importance of strengthening public health emergency management (PHEM), which is an emergent field of practice that draws on specific sets of knowledge, techniques, and organizing principles necessary for the effective management of complex health events( 2 ). The establishment of PHEM has led to improved coordination, coherence of thoughts among public health officials, government ownership, commitment and collaboration ( 2 , 3 ). PHEM is designed to ensure rapid detection of any public health threats, preparedness related to logistic and fund administration, and prompt response to and recovery from various public health emergencies, which range from recurrent epidemics, emerging infections, nutritional emergencies, chemical spills, and bioterrorism ( 4 ). PHEM means quickly obtaining and effectively using relevant information and resources to improve the effectiveness and efficiency of emergency response to minimize harm and negative impact ( 5 ). Competency models are key tools in human resource systems and practice; regardless of approach, the competency model provides an operational definition for each competency together with core measurable/observable performance indicators against which to evaluate the organization. Public health emergencies need to involve the routine activities of all sectors, particularly primary health care units (PHCUs) along with district health offices (DHOs), which are at the frontline of managing health-related incidents, and it is critical to practice and evaluate their status regularly( 6 ). Deficiencies in manpower, weakened health systems, mishandling scarce resources, and political instability are among the challenges facing disaster management. Furthermore, medical economic constraints, apathy in risk perception among administrators, planning assumptions that expect orderly and usual occurrences, cost benefits of early preparedness, and legal risks were identified as potential barriers to emergency preparedness among health institutions( 7 , 8 ). Although public health emergencies provide opportunities to assess public health emergency preparedness and response, few studies have investigated how health administrators at all levels and their respective primary health care units manage public health emergencies. This study aimed to assess the postwar status of public health emergency preparedness and response in Tigrai, Ethiopia. Methods Study area and period Tigrai forms the northernmost reaches of Ethiopia and is located between 36 0 and 40 0 East longitudes. Its north‒south extent spans 12 and half degrees to 15 degrees north. It is bordered by Eritrea in the north, Sudan to the west, the Amhara regional state to the southwest and the Afar region to the east. The region has a population of approximately 6 million (9), and approximately 80% of the population is rural dwellers. The region had a well-established healthcare system with 1,011 public health institutions prior to the start of the war in November 2020. The public healthcare services are provided through two specialized referral hospitals, 14 general hospitals, 24 primary hospitals, 226 health centers, and 743 health posts. The region has emphasized disease prevention and health promotion through primary health care units (PHCUs), which are composed of health posts, health centers, and primary hospitals. Primary healthcare units, district health offices, and regional health bureaus were included in the study. The study was conducted from January 16–February 14, 2024. Fig. 1 : The position of the study areas in the Tigrai regional state of Ethiopia. Study design and population A quantitative cross-sectional survey was employed to assess the status of public health emergency management systems benchmarking the competency framework of the system domain (10). Health emergency management assessment is an integral part of primary health care. Among the different types of health emergency management assessment approaches with indicators of health emergency management that best fit with the current study is the evaluation system called the competency model of health emergencies. The model has four phases with functional indicators of health emergency assessment, which are wide in dimension. The assessment indicators include risk analysis potential, leadership potential, response ability, and the collaborative and reporting ability of the responsible bodies. Public health preparedness and response core competencies were created to establish common performance goals for healthcare on the basis of WHO evaluation tools (11). The goal was defined as the ability to proficiently perform assigned prevention, preparedness, response and recovery roles in accordance with the established national and regional health systems(2, 12). For this particular research, the competency framework of health emergency management within a system domain was used to evaluate the health emergency management status of the Tigrai regional state. Fig. 2 : The competency framework of public health emergency preparedness and response systems. The study population included primary healthcare facilities (primary hospitals, health centers and health posts), healthcare providers at each level of primary healthcare facilities and healthcare leaders (at regional health bureaus, districts, and primary healthcare facilities). Sample size and sampling procedure The sample size for the study was determined by random selection of districts from each zone. A representative sample of approximately 30% of the accessible and semi accessible districts was randomly selected and proportionally allocated for each zone. For this particular study, 110 institutions (30% of the accessible primary health facilities constituting 9 primary hospitals, 23 health centers, 54 health posts, and 24 DHOs) were included from the randomly selected districts for the survey. Data collection procedures A semi structured and pretested questionnaire adapted from the core competency elements of public health emergencies and the WHO benchmark evaluation tool (2, 11) were used and collected through the interviewer administered technique. The tool primarily includes (mitigation, preparedness, response and recovery indicators) training and risk analysis potential, leadership potential, response ability, and the collaborative and reporting ability of the responsible bodies. The data collection instrument was first prepared in English and then translated to the local language. Data were collected by 48 bachelor’s degree holder health care providers via an electronic tool, i.e., the Open Data Kit (ODK). A total of 24 Master’s degree health professionals were assigned as supervisors in the study districts to follow and monitor the overall data collection process. Data analysis The dataset was cleaned, coded, and processed for analysis, and data analysis was performed via SPSS Version 27 software. An assessment of missing values and outliers was performed through appropriate cleaning procedures before actual data analysis. Descriptive statistical measures, such as proportions for categorical variables and means, standard deviations (SDs), and medians, were subsequently calculated for the general characteristics of the study participants and percentages for health services. Similarly, data extracted from health facilities were also analyzed and compared with respect to regional and national targets. Finally, the overall status of public health emergency preparedness and readiness was classified as “low” if the average percentage score was 33%-66.6% and as “high” if the percentage score ranged from 66.7% to 100% (13). The analyzed data were presented in textual, graphical and tabular formats accordingly. Results 1. Health emergency preparedness and response at the zone level This study aimed to collect data from 110 randomly selected public health institutions, including district health offices (DHOs), in the Tigrai regional state regarding specific indicators of public health emergency preparedness and readiness. In total, nearly one-third (39.3%) (27.8%) of the zonas have trained staff on health emergency management in the Central Zone and Northwest Zone; similarly, more than one-third (40%) and (42.9%) trained staff in the Southeast Zone and Southern Zone, respectively, have trained staff. The southeastern zone has approximately one-third (33.3%) of its facilities equipped with health emergency management-specific plans; however, the Mekelle zone does not have any plans. On the other hand, with the exception of Mekelle, the remaining zones did not report outbreak-prone diseases observed at their facilities in the last six months. With respect to reporting, most of the zones have been using digital data for surveillance reporting thus far, whereas the Mekelle and North West zones have not yet been used. Similarly, most (80%) and half (50%) of the facilities in the Eastern and Mekelle zones did not have annual plans, whereas in the Southeast Zone, all the surveyed facilities had annual plans. Except for the Mekelle, the remaining zones did not report suspected cases of nonpolio acute flaccid paralysis (NP-AFP) (Table 1 ). Table 1 Health emergency preparedness and response at the zonal level in Tigrai, Ethiopia, February 2024. Variables (N = 32) Zone Central Eastern Mekelle Northwest Southeast Southern Number of staffs trained PHEM Yes 11 (39.3%) 5 (31.3%) 2(100%) 5 (27.8%) 6 (40%) 3(42.9%) No 17 (60.7%) 11(68.8%) 0 13(72.2%) 9 (60%) 4(57.1%) Yes 4(26.7%) 1 (6.7%) 0 3(20%) 5(33.3%) 2(13.3%) Presence of PHEM plan No 7(41.2%) 4(23.5%) 2(11.8%) 2 (11.8%) 1(5.9%) 1(5.9%) Yes 5(33.3%) 1(6.7%) 2(13.3%) 3(20%) 2(13.3%) 2(13.3%) Report outbreak prone disease No 6 (35.5%) 4(23.5%) 0 2(11.8%) 4(23.5%) 1(5.9%) Yes 5(45.5%) 0 2 (100%) 1(20%) 2(33.3%) 3(100%) Investigate prone outbreak cases No 6 (54.5%) 5(100%) 0 4 (80%) 4(66.7%) 0 Yes 5(45.5%) 1(20%) 2 (100%) 2(40%) 2(33.3%) 2(66.7%) Treat for outbreak at facility No 6(54.5%) 4(80%) 0 3(60%) 4(66.7%) 1(33.3%) Yes 1(9%) 2(40%) 0 0 116.7%) 1(33.3%) Use of digital systems for reporting No 10(91%) 3(60%) 2(100%) 5(100%) 5(83.3%) 2(66.7%) Yes 6(54.5%) 1(20%) 1(50%) 4(80%) 6(100%) 2(66.7%) Presence of annual plan No 5(45.5%) 4(80%) 1(50%) 1(20%) 0 1(33.3%) Yes 2 (18.2%) 1(20%) 1(50%) 1(20%) 1(16.7%) 1(33.3%) Report of non-measles febrile rash per year No 9(81.8%) 4(80%) 1(50%) 4(80%) 5(83.3%) 2(66.7%) Yes 0 0 2(100%) 0 1(16.7%) 0 Report of NP-AFP cases per year No 11(100%) 5(100%) 0 5(100%) 5(83.3%) 3(100%) Table 1 : Health emergency preparedness and response at the zonal level in Tigrai, Ethiopia, February 2024. With respect to planning and reporting, nearly half (53.1%) of the districts, (54.6%) of the primary hospitals, and (52.2%) of the health centers included in the study did not have a PHEM-specific plan. Similarly, more than half (53.1%) of the districts and (52.2%) health centers and two-thirds (66.6%) of the primary hospitals did not report outbreak-prone diseases in the last six months. Similarly, more than fifty (56.5%) of the health centers and (59.4%) of the districts and almost two-thirds (66.6%) of the primary hospitals reported that they did not investigate and treat outbreak-prone cases (Fig. 3 ). Figure 3 : Reporting, investigating and treating outbreaks of health facilities in Tigrai, Ethiopia, Feb. 2024 Most (84.4%) of the districts and the majority (91.3%) of the health centers reported that they did not use digital technologies for reporting surveillance data. Approximately two-thirds (62.5%) of the districts, 61% of the health centers, and 66.6% of the primary hospitals included the PHEM annual plan. Most (78.1%) of the districts (87%) of the health centers and more than half (54.6%) of the primary hospitals did not report non-measles febrile rash; similarly, the majority (90.6%) of the districts (95.7%) of the health centers and 77.8% of the primary hospitals did not report suspected NP-APF cases (Fig. 4 ). Figure 4 : Planning and early warning activities in health facilities in Tigrai, Ethiopia, Feb, 2024 2. Emergency preparedness, commands and feedback at the health post level PHEM training among health extension workers (HEWs) was also studied; most HEWs (77.7%) in Southeast and nearly two-thirds in Eastern and Northwestern (63.6%) and (63.8%) were trained, respectively, and more than half of Central and South HEW were trained on PHEM-related plans/producers. Almost all HEWs working at each health post had clear communication channels with health centers, local health authorities, and other relevant stakeholders. More than half (54.5%) of the HEW in Eastern zone HEW had plans for collaboration and coordination with other emergency response agencies. The majority of HEWs in each zone reported immediately for suspected or confirmed outbreaks to their local health authorities, except in the South Zone, which reported 75% of the expected reporting activities. More than half (55.6%) of Southeast and half (50%) of HEW in South zones did not have immediately and weekly reported surveillance data at their health post as backup data during the survey. Community-based public health emergency management has been surveyed on the basis of zonal segmentation; the majority of HEWs in the Eastern and Southeastern zones actively participate in community-based PHEM activities, such as outreach programs and awareness campaigns. In most of the zones, the HEW did not have a clear assignment of roles and responsibilities for emergency response operations except Eastern and Southeast that account 77.8% and 100% of the expected emergency reports, respectively (Table 2 ). Table 2 Emergency preparedness, command and feedback channels at health posts in Tigrai, Ethiopia, February 2024. Variables (N = 54) Zones Central Eastern North west South east South Trained HEW on PHEM procedures Yes 10(58.8%) 7(63.6%) 7(63.8%) 7(77.8%) 2(50%) No 7(41.2%) 4(36.4%) 6(46.2%) 2(22.2%) 2(50%) Clear communication channel with health centers, local health authorities, and other relevant stakeholders Yes 16 (94%) 11(100%) 13(100%) 9(100%) 4(100%) No 1 (6%) 0 0 0 0 Plan for collaboration and coordination with other emergency response agencies Yes 3(17.6%) 6(54.5%) 3(23%) 2(22.2%) 0 No 14(82.4%) 5 (45.5%) 10(76.9%) 7(77.8%) 4(100%) Immediately reporting of suspected or confirmed outbreaks to health authorities Yes 15(88.2%) 10(91%) 13(100%) 8(89%) 3(75%) No 2(11.8%) 1(9%) 0 1(11%) 1(25% Presence of surveillance data at health post (immediately or weekly backup) Yes 15(88.2%) 9(81.8%) 11(84.6% 4(44.4%) 2(50%) No 2(11.8%) 2(18.2%) 2(15.4%) 5(55.6%) 2(50%) Actively participate in community-based PHEM activities (outreach programs & awareness campaigns) Yes 11(64.7%) 9(81.8%) 10(76.9%) 8(89%) 2(50%) No 6(35.3%) 2(18.2%) 3(23.1%) 1(11%) 2(50%) Clear assignment of roles and responsibilities for emergency response operations Yes 8(47%) 11(100%) 6(46%) 7(77.8%) 1(25%) No 9(53%) 0 7(54%) 2(22.2%) 3(75%) Table 2 : Emergency preparedness, command and feedback channels at health posts in Tigrai, Ethiopia. Two-thirds (61.1%) of the health extension workers had trained in PHEM-related plans/procedures, and the majority (98.10%) of the health extension workers had clear communication channels among health centers and local actors or and stakeholders. Similarly, the majority (90.70%) of HEW reported immediately suspected and confirmed cases to their higher-level health authorities; nevertheless, approximately three-fourths of HEW did not have a clear plan for collaboration and coordination for emergency operations (Fig. 5 ). Figure 5 : Health emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024 Nearly three-fourths (75.9%) of HEW had backup surveillance data at their health post, and approximately 61.1% of the HEW had actively engaged in community-based PHEM activities, whereas the majority (92.6%) and 94.4% of HEW did not report suspected non-Measles rash febrile illness and suspected NP-AFP cases, respectively, in the last six months (Fig. 6 ). Figure 6 : Health emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024 Out of the surveyed zones, malaria outbreaks were reported from five health posts, namely, Selam health post (Asegede woreda), Mayliham health post (Bora woreda), Metikel health post (Enderta woreda), Werie health post (Maykinetal woreda), and Finariwa health post (Samire woreda), and scabies outbreaks were also reported from Tsankanaet health post (Tsaedaemba woreda). Both of the outbreaks (malaria and scabies) had been reported by health extension workers, but providentially, there was no death reported during the survey. With respect to the action taken for the outbreaks that have been reported in the last six months, most (83.3%) of the outbreak actions/measures have been taken by woreda surveillance focal persons and two-thirds (66.6%) each by health extension workers (HEWs) and partners/stakeholders (Fig. 7 ). Figure 7 : Outbreak response, health actors and stakeholders in Tigrai, Ethiopia, February 2024 With respect to malaria case management at the level of health posts, approximately two-thirds (64.80%) of the respondents had been diagnosed with malaria cases via RDT; the majority (97%) of the cases were treated for malaria, and most (85.70%) were referred to as malaria cases for further action (Fig. 8 ). Figure 8 : Malaria management at the health post level in Tigrai, Ethiopia, February 2024 3. Health emergency status at the district health office level All the selected health offices (100%) included in the survey had a functional surveillance and early warning system across all health facilities, but only sixteen (66.7%) of the woreda health offices had functional emergency operation and coordination centers, and 18 (75%) of the offices had expertise in communication during emergencies. Among the respondents, only 8 (33.3%) of the woreda health offices had used digital means to report weekly surveillance systems. Most of the woredas 21 (87.5%) reported complete surveillance data on time. The majority 22 (91.7%) of the woredas health offices had annual plans. Approximately 20 (83.3%) of the woreda health offices had risk assessment and mitigation plans (Table 3). Table 3: Preparedness and response from interviews and observations in woreda health offices of Tigrai, Ethiopia, Feb, 2024 With respect to the reporting of non-measles febrile rash and non-polio acute flaccid paralysis (NP-AFP), less than half 11 (45.8%) and only 6 (25%) of the woreda health offices reported non-measles febrile rash illness and NP-AFP cases, respectively (Fig. 9 ) Figure 9 : Reporting childhood illnesses from the woreda health offices of Tigrai, Ethiopia, Feb, 2024 Discussion The study results provide insights into vital details of health emergency preparedness and response in the war ridden Tigrai regional state. From the perspective of health emergency preparedness and response dimensions, planning and reporting of health incidents at the woreda level is the mainstay of health emergency management; the southeastern zone had only 33.3% of its facilities equipped with health emergency plans, 80% of the facilities in Eastern and 50%, and the Mekelle zone did not have plans during the survey. Similarly, almost all zones did not report suspected cases of nonpolio acute flaccid paralysis (NP-AFP), except for the Mekelle zone. This has placed the emergency preparedness and response of the region within the range of low percentage scores, and the results are congruent with those of studies conducted in selected health institutions in the Amhara region, Tunisia, and Italy ( 13 – 16 ). According to the data obtained from the health facilities, irrespective of the increasing occurrence of public health emergencies, the planning capability, prompt reporting and response of public health incidents were found to be low; more than half (53.1%) of the districts, (54.6%) of the primary hospitals, and (52.2%) of the health centers in the study area had no specific health emergency plans. Similarly, more than half (53.1%) of the districts and (52.2%) health centers and two-thirds (66.6%) of the primary hospitals did not report outbreak-prone diseases. Similarly, more than half (56.5%) of the health centers and (59.4%) of the districts and almost two-thirds (66.6%) of the primary hospitals stated that they failed to investigate and treat outbreak prone cases in the study area. This result is consistent with the results of a study conducted in western Ethiopia and Saudi Arabia ( 17 , 18 ). The findings of the present study revealed that communication and information management readiness were insufficient. Most (84.4%) of the districts and the majority (91.3%) of the health centers reported that they did not use digital technologies for reporting surveillance data. Most (78.1%) of the districts (87%) of the health centers and (54.6%) of the primary hospitals did not report non-measles febrile rash, and the majority (90.6%) of the districts (95.7%) of the health centers and (77.8%) of the primary hospitals did not report suspected NP-APF cases. This finding was consistent with the findings of similar studies performed elsewhere ( 17 – 19 ); however, these results contrast with the results of studies conducted in Europe ( 20 ). This implies that primary health care units must create a well-functioning communication and information management system for efficient and prompt public health emergency management. Notably, impediments to the coordination and collaboration of the community and event-based surveillance were identified as insufficient during the survey, with considerably low coordination and collaboration with other emergency response agencies. Only 61.1% of the health extension workers at health posts had actively engaged in community-based health emergency management activities. Concerning the action taken for the outbreaks, most (83.3%) of the outbreak measures have been taken by the woreda PHEM surveillance focal person alone and two-thirds (66.6%) each by health extension workers (HEWs) and stakeholders. This unsatisfactory performance of collaboration in emergency health incidents is in line with studies conducted in sub-Saharan African countries and South Asia, China and the United States( 21 – 23 ). The use of real-time data to inform healthcare providers, public health experts and government decision makers is crucial for emergency health management; digitalizing alert notification and communication for prompt and timely responses has been remained low in most of the surveyed health institutions. This result is similar to that of a study carried out in the developed world and Southwest Ethiopia ( 24 , 25 ). This has indicated that due emphasis must be given to the importance of adequate preparation and response during emergencies, advocating for centralized digital communication systems and prompt feedback circles. The observed low performance of health emergency preparedness and response in this study could be due to deliberate damage to the health care system during the war. Strengths and limitations of the study This study has benchmarked the competency framework to evaluate the public health emergency preparedness and readiness of the region. Nevertheless, recall bias may be introduced during data collection, as some of the variables need to be recalled to situations that have occurred a few months prior. The inability to include inaccessible health institutions is due to security reasons, and the findings may not be generalizable. Conclusions The current findings revealed that primary health care facilities are challenged by the need to maintain meticulous health emergency preparedness and readiness activities. Owing to the existing postwar administrative structure, a lack of conceptual health emergency preparedness and readiness, disparities across zones and districts, and insufficient application of digital technologies lag behind. Furthermore, the study revealed the following important issues: low reporting, verification, and investigation of alerts promptly; poor coordination, collaboration and planning at all levels of health services and partners; and low community engagement in health emergency preparedness and response; as a result, there was evidence of re-emergence of previously controlled diseases. Forthcoming priorities should be to develop the response stage, establish closed feedback between the preparedness and recovery stages, and strengthen capacity building in collaboration with stakeholders through increasing training and improving quality prompt responses with relevant partners/stakeholders. Digitalizing alert notifications and communication for prompt response and strengthening electronic public health emergency management (ePHEM) by integrating with the available work force with due attention in the war-ridden localities. The implementation of community platforms (community-based and event-based surveillance) that enhance community engagement, particularly in public health emergency activities, should be strengthened. Declarations Ethics approval and consent to participate Ethical clearance was obtained from the Tigrai Health Research Institute (THRI) (Reference number: THRI/4031/0503/16). A letter of support was secured from the Tigrai Health Bureau, and permission was also obtained from the selected districts. The participants and institution representatives provided consent via an information sheet that described the purpose, procedure, and confidentiality of the study. The right to withdraw from participation was also asked. All the collected data were handled anonymously, confidentially, and securely. Availability of data and materials Data will be made available on request Consent for publication The authors, give their consent for the publication of this research article to be published in the journal BMC Conflict and Health. Competing interests The authors declare that they have no competing interests. Funding Tigray Health Bureau has financially supported this study. Authors' contributions MTA, AAA, HGW, MH and MGW wrote the proposal, performed the statistical analysis and drafted the paper. HDH, GBG, TB, HG and MME approved the proposal with some revisions and participated in the design of the study and data analysis. YBT, AKB, GGM, GGG, MHD, MHA, RE and MGB supervised and coordinated the data collection and participated in the statistical analysis. All the authors read and approved the final manuscript. Acknowledgments We would like to express our heartfelt thanks to the Tigrai Health Bureau, study participants, data collectors, supervisors, district health offices, and local administrators for their cooperation during the study. References Cao K. Interpretation of Regulations on Preparedness for and Response to Emergent Public Health Hazards. Beijing: China Legal Publishing House; 2003. (in Chinese). Rose DA, Murthy S, Brooks J, Bryant J. The evolution of public health emergency management as a field of practice. Am J Public Health. 2017;107(S2):S126–33. Oyebanji O, Ibrahim Abba F, Akande OW. Building local capacity for emergency coordination: establishment of subnational. Public Health Emerg Oper Centers Nigeria. 2021;6(10). Organization WH. Standard operating procedures for coordinating public health event preparedness and response in the WHO African Region. 2014. Schnall A, Nakata N, Talbert T, Bayleyegn T, Martinez D, Wolkin A. Community Assessment for Public Health Emergency Response (CASPER): an innovative emergency management tool in the United States. Am J Public Health. 2017;107(S2):S186–92. Adini B, Ohana A, Furman E, Ringel R, Golan Y, Fleshler E et al. Learning lessons in emergency management: the 4th International Conference on Healthcare System Preparedness and Response to Emergencies and Disasters. Disaster and military medicine. 2016;2:1–6. Aliyu A. Management of disasters and complex emergencies in Africa: The challenges and constraints. Ann Afr Med. 2015;14(3):123–31. Barbera JA, Yeatts DJ, Macintyre AG. Challenge of hospital emergency preparedness: analysis and recommendations. Disaster Med Pub Health Prep. 2009;3(S1):S74–82. Agency CS. Population Size by Sex, Region, Zone and Wereda: July 2021. Ethiopia: CSA: Addis Ababa; 2021. Schor KW, Altman BA. Proposals for aligning disaster health competency models. Disaster Med Pub Health Prep. 2013;7(1):8–12. Organization WH. WHO benchmarks for strengthening health emergency capacities. World Health Organization; 2024. Nelson C, Lurie N, Wasserman J, Zakowski S. Conceptualizing and defining public health emergency preparedness. American Public Health Association; 2007. pp. S9–11. Ayenew T, Tassew SF, Workneh BS. Level of emergency and disaster preparedness of public hospitals in Northwest Ethiopia: A cross-sectional study. Afr J Emerg Med. 2022;12(3):246–51. Organization WH. Health emergency and disaster risk management framework. 2019. Geniosa BP, Aini Q. Hospital preparedness level and policy implementation analysis of hospital disaster plan in RSUD Kota Yogyakarta. J Indonesian Health Policy Adm. 2020;5(3). Lamine H, Tlili M, Aouicha W, Taghouti E, Chebili N, Zedini C. Disaster preparedness level of university hospitals of Sousse-Tunisia. Eur J Pub Health. 2020;30(Supplement5):ckaa166. Bajow NA, Alkhalil SM. Evaluation and analysis of hospital disaster preparedness in Jeddah. Health. 2014;6(19):2668. Woyessa AH, Teshome M, Mulatu B, Abadiga M, Hiko N, Kebede B. Disaster preparedness in selected hospitals of western Ethiopia and risk perceptions of their authorities. Open access Emerg Med. 2020:219–25. Koka PM, Sawe HR, Mbaya KR, Kilindimo SS, Mfinanga JA, Mwafongo VG, et al. Disaster preparedness and response capacity of regional hospitals in Tanzania: a descriptive cross-sectional study. BMC Health Serv Res. 2018;18:1–7. Ingrassia PL, Mangini M, Azzaretto M, Ciaramitaro I, Costa L, Burkle FM Jr, et al. Hospital Disaster Preparedness in Italy: a preliminary study utilizing the World Health Organization Hospital Emergency Response Evaluation Toolkit. Minerva Anestesiol. 2016;82(12):1259–66. Gooding K, Bertone MP, Loffreda G, Witter S. How can we strengthen partnership and coordination for health system emergency preparedness and response? Findings from a synthesis of experience across countries facing shocks. BMC Health Serv Res. 2022;22(1):1441. Liu J, Dong C, An S, Mai Q, editors. Dynamic evolution analysis of the emergency collaboration network for compound disasters: A case study involving a public health emergency and an accident disaster during COVID-19. Healthcare: MDPI; 2022. Wolf-Fordham S. Integrating government silos: Local emergency management and public health department collaboration for emergency planning and response. Am Rev Public Adm. 2020;50(6–7):560–7. Damaševičius R, Bacanin N, Misra S. From sensors to safety: internet of Emergency Services (IoES) for emergency response and disaster management. J Sens Actuator Networks. 2023;12(3):41. Berhanu N, Abrha H, Ejigu Y, Woldemichael K. Knowledge, experiences and training needs of health professionals about disaster preparedness and response in southwest Ethiopia: a cross sectional study. Ethiop J health Sci. 2016;26(5):415–26. Table Table 3 is not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Oct, 2024 Editor assigned by journal 23 Oct, 2024 Submission checks completed at journal 23 Oct, 2024 First submitted to journal 22 Oct, 2024 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5312606","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":369900895,"identity":"bbad5168-17a7-4719-b056-3503ea8c895d","order_by":0,"name":"Meresa Gebremedhin Weldu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIie3QsQrCMBCA4SuVdEnpekXsGwiVQBH0YeySzb2TdKqLxVXfwkncFIq65AHipC5ugiCIgoJxc6pxE8w/ZLqP4wJgMv1qpxApgL0AK9UU1ihpBgCko09sKhIGQEM9Uu/n+52bYTx0xAVvs3YATrGclJFIrFnoKzIedKd+LjgDyrksJZITbCgyke4U3ayIU6RROdkenGusyFzSg//QIpIQWAhk6p9JVW+L4LafJhigOqNVyzgjH29Zr6zzPexRr1/sN8esHXhOsSol71Xw9RLd8Vf26Ztpk8lk+p+eYwRKEEvS+sAAAAAASUVORK5CYII=","orcid":"","institution":"Aksum University College of Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Meresa","middleName":"Gebremedhin","lastName":"Weldu","suffix":""},{"id":369900897,"identity":"23ccdab3-2a43-4f3a-a4d9-dc4c5f373a3d","order_by":1,"name":"Mache Tsadik Adhana","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mache","middleName":"Tsadik","lastName":"Adhana","suffix":""},{"id":369900898,"identity":"3606a961-fc3b-4243-84dd-1c619300d1cf","order_by":2,"name":"Akeza Awalom Asgedom","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Akeza","middleName":"Awalom","lastName":"Asgedom","suffix":""},{"id":369900899,"identity":"44f7ac91-cff0-4452-b23f-ad302b822ad4","order_by":3,"name":"Haftom Gebrehiwot Woldearegay","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Haftom","middleName":"Gebrehiwot","lastName":"Woldearegay","suffix":""},{"id":369900900,"identity":"e57ea968-73f6-46e8-a630-c8ee1533f422","order_by":4,"name":"Mengistu Hagazi Tequare","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mengistu","middleName":"Hagazi","lastName":"Tequare","suffix":""},{"id":369900901,"identity":"b1aa91cd-8497-4985-b2ae-25a493cbb25c","order_by":5,"name":"Gebregziabher Berihu Gebrekidan","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gebregziabher","middleName":"Berihu","lastName":"Gebrekidan","suffix":""},{"id":369900902,"identity":"0a8da399-3c83-41a1-876b-3e2858752e83","order_by":6,"name":"Tedros Bereket","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Tedros","middleName":"","lastName":"Bereket","suffix":""},{"id":369900903,"identity":"2a37322e-680a-4e9c-8a7a-0497993953c1","order_by":7,"name":"Mohamedawel Mohamednigus Ebrahim","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohamedawel","middleName":"Mohamednigus","lastName":"Ebrahim","suffix":""},{"id":369900906,"identity":"300ca413-59b7-4292-b6b8-aeb7705d154f","order_by":8,"name":"Gebrekiros Gebremichael Meles","email":"","orcid":"","institution":"Mekelle University College of Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gebrekiros","middleName":"Gebremichael","lastName":"Meles","suffix":""},{"id":369900908,"identity":"e8af3b78-c824-43db-b728-7800e13bb3c6","order_by":9,"name":"Abadi Kidanemariam Berhe","email":"","orcid":"","institution":"Adigrat University College of Medicine and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abadi","middleName":"Kidanemariam","lastName":"Berhe","suffix":""},{"id":369900911,"identity":"8fa18bbe-624a-4dd5-b9be-45198597dec8","order_by":10,"name":"Yemane Berhane Tesfau","email":"","orcid":"","institution":"Adigrat University College of Medicine and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yemane","middleName":"Berhane","lastName":"Tesfau","suffix":""},{"id":369900913,"identity":"74ffb02d-4164-4bcb-bc3d-6653cc08feed","order_by":11,"name":"Gebremedhin Gebreegzabiher Gebretsadik","email":"","orcid":"","institution":"Adigrat University College of Medicine and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Gebremedhin","middleName":"Gebreegzabiher","lastName":"Gebretsadik","suffix":""},{"id":369900914,"identity":"c0da558d-0c87-42a8-9f55-5758663e8ae6","order_by":12,"name":"Muzey Gebremichael Berhe","email":"","orcid":"","institution":"Adigrat University College of Medicine and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Muzey","middleName":"Gebremichael","lastName":"Berhe","suffix":""},{"id":369900915,"identity":"1448bbea-f18a-45fc-9ff8-684b3ab6f756","order_by":13,"name":"Hailay Gebretnsae","email":"","orcid":"","institution":"Tigrai Health Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Hailay","middleName":"","lastName":"Gebretnsae","suffix":""},{"id":369900916,"identity":"9faaa3f5-7fb0-40c9-a256-1daaa9d3f1d8","order_by":14,"name":"Micheale Hagos Debesay","email":"","orcid":"","institution":"Tigrai Regional Health Bureau","correspondingAuthor":false,"prefix":"","firstName":"Micheale","middleName":"Hagos","lastName":"Debesay","suffix":""},{"id":369900917,"identity":"84113d38-1fd4-4915-a96b-a75002f7c359","order_by":15,"name":"Rieye Esayas","email":"","orcid":"","institution":"Tigrai Regional Health Bureau","correspondingAuthor":false,"prefix":"","firstName":"Rieye","middleName":"","lastName":"Esayas","suffix":""},{"id":369900918,"identity":"2f1cc626-74d3-461c-bd7e-2e296843ad16","order_by":16,"name":"Mebrahtom Hafte Ameha","email":"","orcid":"","institution":"Tigrai Regional Health Bureau","correspondingAuthor":false,"prefix":"","firstName":"Mebrahtom","middleName":"Hafte","lastName":"Ameha","suffix":""},{"id":369900919,"identity":"057dac8b-0b7b-4e1f-b5df-de0ebe5cb8e8","order_by":17,"name":"Hagos Degefa Hidru","email":"","orcid":"","institution":"Tigrai Health Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Hagos","middleName":"Degefa","lastName":"Hidru","suffix":""}],"badges":[],"createdAt":"2024-10-22 14:23:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5312606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5312606/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68280529,"identity":"bf4f020a-f237-4276-96da-ddf0d1f283b3","added_by":"auto","created_at":"2024-11-05 15:19:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":580588,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe position of the study areas in the Tigrai regional state of Ethiopia.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/8d93138e876f1b1448e9a30c.png"},{"id":68280527,"identity":"4497d267-ce50-42e6-b139-f7dd4e422672","added_by":"auto","created_at":"2024-11-05 15:19:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":225457,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eThe competency framework of public health emergency preparedness and response systems.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/f646b285419d12040299b461.png"},{"id":68281654,"identity":"7a2a8ad3-2925-4594-8c4a-b763c7d55c09","added_by":"auto","created_at":"2024-11-05 15:27:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":152441,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eReporting, investigating and treating outbreaks of health facilities in Tigrai, Ethiopia, Feb. 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/673ea7a1ac7bb4f1f12ea9e0.png"},{"id":68280531,"identity":"c23f50ba-e8f7-4f36-91f4-ed5733e48c2b","added_by":"auto","created_at":"2024-11-05 15:19:43","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":136109,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePlanning and early warning activities in health facilities in Tigrai, Ethiopia, Feb, 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/1b3aa9c8bc0084094db56ed6.png"},{"id":68280536,"identity":"a03aca6d-9dd5-4e37-869c-f934becd40ea","added_by":"auto","created_at":"2024-11-05 15:19:43","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":98216,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHealth emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/33b1e6ce7bb2487583a3e278.png"},{"id":68281652,"identity":"8e19f0bf-3f7c-4f25-a5a7-b483e058ab9a","added_by":"auto","created_at":"2024-11-05 15:27:43","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":107174,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eHealth emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/8ae27ecca059c531713c1777.png"},{"id":68281651,"identity":"ac1966b5-e20a-4450-b103-18e04227e727","added_by":"auto","created_at":"2024-11-05 15:27:43","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":115547,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eOutbreak response, health actors and stakeholders in Tigrai, Ethiopia, February 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/49fc044b972d626a90290283.png"},{"id":68280534,"identity":"23b8aaee-901b-4d5b-a78e-8eca83658b21","added_by":"auto","created_at":"2024-11-05 15:19:43","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":105357,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMalaria management at the health post level in Tigrai, Ethiopia, February 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/08d016afa371bd1fa235f4ba.png"},{"id":68281655,"identity":"2f76bf62-a441-40e2-a92c-481b97259051","added_by":"auto","created_at":"2024-11-05 15:27:49","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":86587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eReporting childhood illnesses from the woreda health offices of Tigrai, Ethiopia, Feb, 2024.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/ebd974ba70a422686b84222b.png"},{"id":68281997,"identity":"b7f249f2-aef3-499b-80d3-ed2d04c9f6a3","added_by":"auto","created_at":"2024-11-05 15:35:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2062242,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5312606/v1/8d158a12-abb2-4d13-a2fd-4dea8e155e8e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Status of Public Health Emergency Preparedness and Response in the War-Ridden Tigrai, Ethiopia: A descriptive study benchmarking the Competency Framework","fulltext":[{"header":"Background","content":"\u003cp\u003ePublic health emergencies are defined as unexplained diseases, major food or drinking water and occupation poisoning, and other serious public health events that suddenly occur, thereby causing major infectious diseases or even serious damage to public health groups (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The health impacts of infectious disease outbreaks and other disasters have demonstrated the importance of strengthening public health emergency management (PHEM), which is an emergent field of practice that draws on specific sets of knowledge, techniques, and organizing principles necessary for the effective management of complex health events(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The establishment of PHEM has led to improved coordination, coherence of thoughts among public health officials, government ownership, commitment and collaboration (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). PHEM is designed to ensure rapid detection of any public health threats, preparedness related to logistic and fund administration, and prompt response to and recovery from various public health emergencies, which range from recurrent epidemics, emerging infections, nutritional emergencies, chemical spills, and bioterrorism (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). PHEM means quickly obtaining and effectively using relevant information and resources to improve the effectiveness and efficiency of emergency response to minimize harm and negative impact (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Competency models are key tools in human resource systems and practice; regardless of approach, the competency model provides an operational definition for each competency together with core measurable/observable performance indicators against which to evaluate the organization. Public health emergencies need to involve the routine activities of all sectors, particularly primary health care units (PHCUs) along with district health offices (DHOs), which are at the frontline of managing health-related incidents, and it is critical to practice and evaluate their status regularly(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Deficiencies in manpower, weakened health systems, mishandling scarce resources, and political instability are among the challenges facing disaster management. Furthermore, medical economic constraints, apathy in risk perception among administrators, planning assumptions that expect orderly and usual occurrences, cost benefits of early preparedness, and legal risks were identified as potential barriers to emergency preparedness among health institutions(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Although public health emergencies provide opportunities to assess public health emergency preparedness and response, few studies have investigated how health administrators at all levels and their respective primary health care units manage public health emergencies. This study aimed to assess the postwar status of public health emergency preparedness and response in Tigrai, Ethiopia.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy area and period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTigrai forms the northernmost reaches of Ethiopia and is located between 36\u003csup\u003e0\u003c/sup\u003e and 40\u003csup\u003e0\u003c/sup\u003e East longitudes. Its north‒south extent spans 12 and half degrees to 15 degrees north. It is bordered by Eritrea in the north, Sudan to the west, the Amhara regional state to the southwest and the Afar region to the east. The region has a population of approximately 6 million (9), and approximately 80% of the population is rural dwellers. The region had a well-established healthcare system with 1,011 public health institutions prior to the start of the war in November 2020. The public healthcare services are provided through two specialized referral hospitals, 14 general hospitals, 24 primary hospitals, 226 health centers, and 743 health posts. The region has emphasized disease prevention and health promotion through primary health care units (PHCUs), which are composed of health posts, health centers, and primary hospitals. Primary healthcare units, district health offices, and regional health bureaus were included in the study. The study was conducted from January 16\u0026ndash;February 14, 2024.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFig. 1\u003c/em\u003e\u003cem\u003e: The position of the study areas in the Tigrai regional state of Ethiopia.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy design and population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA quantitative cross-sectional survey was employed to assess the status of public health emergency management systems benchmarking the competency framework of the system domain (10). Health emergency management assessment is an integral part of primary health care. Among the different types of health emergency management assessment approaches with indicators of health emergency management that best fit with the current study is the evaluation system called the competency model of health emergencies. The model has four phases with functional indicators of health emergency assessment, which are wide in dimension. The assessment indicators include risk analysis potential, leadership potential, response ability, and the collaborative and reporting ability of the responsible bodies. Public health preparedness and response core competencies were created to establish common performance goals for healthcare on the basis of WHO evaluation tools (11). The goal was defined as the ability to proficiently perform assigned prevention, preparedness, response and recovery roles in accordance with the established national and regional health systems(2, 12). For this particular research, the competency framework of health emergency management within a system domain was used to evaluate the health emergency management status of the Tigrai regional state.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFig. 2\u003c/em\u003e\u003cem\u003e: The competency framework of public health emergency preparedness and response systems.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study population included primary healthcare facilities (primary hospitals, health centers and health posts), healthcare providers at each level of primary healthcare facilities and healthcare leaders (at regional health bureaus, districts, and primary healthcare facilities).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size and sampling procedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size for the study was determined by random selection of districts from each zone. A representative sample of approximately 30% of the accessible and semi accessible districts was randomly selected and proportionally allocated for each zone. For this particular study, 110 institutions (30% of the accessible primary health facilities constituting 9 primary hospitals, 23 health centers, 54 health posts, and 24 DHOs) were included from the randomly selected districts for the survey.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA semi structured and pretested questionnaire adapted from the core competency elements of public health emergencies and the WHO benchmark evaluation tool (2, 11) were used and collected through the interviewer administered technique. The tool primarily includes (mitigation, preparedness, response and recovery indicators) training and risk analysis potential, leadership potential, response ability, and the collaborative and reporting ability of the responsible bodies. The data collection instrument was first prepared in English and then translated to the local language. Data were collected by 48 bachelor\u0026rsquo;s degree holder health care providers via an electronic tool, i.e., the Open Data Kit (ODK). A total of 24 Master\u0026rsquo;s degree health professionals were assigned as supervisors in the study districts to follow and monitor the overall data collection process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset was cleaned, coded, and processed for analysis, and data analysis was performed via SPSS Version 27 software. An assessment of missing values and outliers was performed through appropriate cleaning procedures before actual data analysis. Descriptive statistical measures, such as proportions for categorical variables and means, standard deviations (SDs), and medians, were subsequently calculated for the general characteristics of the study participants and percentages for health services. Similarly, data extracted from health facilities were also analyzed and compared with respect to regional and national targets. Finally, the overall status of public health emergency preparedness and readiness was classified as \u0026ldquo;low\u0026rdquo; if the average percentage score was 33%-66.6% and as \u0026ldquo;high\u0026rdquo; if the percentage score ranged from 66.7% to 100% (13). The analyzed data were presented in textual, graphical and tabular formats accordingly.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e1. Health emergency preparedness and response at the zone level\u003c/h2\u003e \u003cp\u003eThis study aimed to collect data from 110 randomly selected public health institutions, including district health offices (DHOs), in the Tigrai regional state regarding specific indicators of public health emergency preparedness and readiness.\u003c/p\u003e \u003cp\u003eIn total, nearly one-third (39.3%) (27.8%) of the zonas have trained staff on health emergency management in the Central Zone and Northwest Zone; similarly, more than one-third (40%) and (42.9%) trained staff in the Southeast Zone and Southern Zone, respectively, have trained staff.\u003c/p\u003e \u003cp\u003eThe southeastern zone has approximately one-third (33.3%) of its facilities equipped with health emergency management-specific plans; however, the Mekelle zone does not have any plans. On the other hand, with the exception of Mekelle, the remaining zones did not report outbreak-prone diseases observed at their facilities in the last six months.\u003c/p\u003e \u003cp\u003eWith respect to reporting, most of the zones have been using digital data for surveillance reporting thus far, whereas the Mekelle and North West zones have not yet been used. Similarly, most (80%) and half (50%) of the facilities in the Eastern and Mekelle zones did not have annual plans, whereas in the Southeast Zone, all the surveyed facilities had annual plans. Except for the Mekelle, the remaining zones did not report suspected cases of nonpolio acute flaccid paralysis (NP-AFP) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHealth emergency preparedness and response at the zonal level in Tigrai, Ethiopia, February 2024.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables (N\u0026thinsp;=\u0026thinsp;32)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c8\" namest=\"c3\"\u003e \u003cp\u003eZone\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMekelle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNorthwest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSoutheast\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSouthern\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNumber of staffs trained PHEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (39.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3(42.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (60.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(68.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13(72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9 (60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4(57.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(26.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of PHEM plan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(13.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReport outbreak prone disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (35.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eInvestigate prone outbreak cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(33.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreat for outbreak at facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(66.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e116.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse of digital systems for reporting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3(60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of annual plan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(33.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eReport of non-measles febrile rash per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReport of NP-AFP cases per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5(83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: \u003cem\u003eHealth emergency preparedness and response at the zonal level in Tigrai, Ethiopia, February 2024.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWith respect to planning and reporting, nearly half (53.1%) of the districts, (54.6%) of the primary hospitals, and (52.2%) of the health centers included in the study did not have a PHEM-specific plan. Similarly, more than half (53.1%) of the districts and (52.2%) health centers and two-thirds (66.6%) of the primary hospitals did not report outbreak-prone diseases in the last six months. Similarly, more than fifty (56.5%) of the health centers and (59.4%) of the districts and almost two-thirds (66.6%) of the primary hospitals reported that they did not investigate and treat outbreak-prone cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: \u003cem\u003eReporting, investigating and treating outbreaks of health facilities in Tigrai, Ethiopia, Feb. 2024\u003c/em\u003e\u003c/p\u003e \u003cp\u003eMost (84.4%) of the districts and the majority (91.3%) of the health centers reported that they did not use digital technologies for reporting surveillance data. Approximately two-thirds (62.5%) of the districts, 61% of the health centers, and 66.6% of the primary hospitals included the PHEM annual plan. Most (78.1%) of the districts (87%) of the health centers and more than half (54.6%) of the primary hospitals did not report non-measles febrile rash; similarly, the majority (90.6%) of the districts (95.7%) of the health centers and 77.8% of the primary hospitals did not report suspected NP-APF cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e: \u003cem\u003ePlanning and early warning activities in health facilities in Tigrai, Ethiopia, Feb, 2024\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2. Emergency preparedness, commands and feedback at the health post level\u003c/h3\u003e\n\u003cp\u003ePHEM training among health extension workers (HEWs) was also studied; most HEWs (77.7%) in Southeast and nearly two-thirds in Eastern and Northwestern (63.6%) and (63.8%) were trained, respectively, and more than half of Central and South HEW were trained on PHEM-related plans/producers.\u003c/p\u003e \u003cp\u003eAlmost all HEWs working at each health post had clear communication channels with health centers, local health authorities, and other relevant stakeholders. More than half (54.5%) of the HEW in Eastern zone HEW had plans for collaboration and coordination with other emergency response agencies. The majority of HEWs in each zone reported immediately for suspected or confirmed outbreaks to their local health authorities, except in the South Zone, which reported 75% of the expected reporting activities.\u003c/p\u003e \u003cp\u003eMore than half (55.6%) of Southeast and half (50%) of HEW in South zones did not have immediately and weekly reported surveillance data at their health post as backup data during the survey.\u003c/p\u003e \u003cp\u003eCommunity-based public health emergency management has been surveyed on the basis of zonal segmentation; the majority of HEWs in the Eastern and Southeastern zones actively participate in community-based PHEM activities, such as outreach programs and awareness campaigns. In most of the zones, the HEW did not have a clear assignment of roles and responsibilities for emergency response operations except Eastern and Southeast that account 77.8% and 100% of the expected emergency reports, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEmergency preparedness, command and feedback channels at health posts in Tigrai, Ethiopia, February 2024.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables (N\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eZones\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNorth west\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSouth east\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrained HEW on PHEM procedures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(58.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7(63.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(63.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(41.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4(36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(46.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClear communication channel with health centers, local health authorities, and other relevant stakeholders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (94%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlan for collaboration and coordination with other emergency response agencies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6(54.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14(82.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (45.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(76.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4(100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eImmediately reporting of suspected or confirmed outbreaks to health authorities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(88.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(91%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8(89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3(75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of surveillance data at health post (immediately or weekly backup)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(88.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11(84.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(15.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5(55.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eActively participate in community-based PHEM activities (outreach programs \u0026amp; awareness campaigns)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(64.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9(81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10(76.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8(89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6(35.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1(11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2(50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClear assignment of roles and responsibilities for emergency response operations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6(46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7(77.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1(25%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9(53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(54%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2(22.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3(75%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: \u003cem\u003eEmergency preparedness, command and feedback channels at health posts in Tigrai, Ethiopia.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eTwo-thirds (61.1%) of the health extension workers had trained in PHEM-related plans/procedures, and the majority (98.10%) of the health extension workers had clear communication channels among health centers and local actors or and stakeholders. Similarly, the majority (90.70%) of HEW reported immediately suspected and confirmed cases to their higher-level health authorities; nevertheless, approximately three-fourths of HEW did not have a clear plan for collaboration and coordination for emergency operations (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e: \u003cem\u003eHealth emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024\u003c/em\u003e\u003c/p\u003e \u003cp\u003eNearly three-fourths (75.9%) of HEW had backup surveillance data at their health post, and approximately 61.1% of the HEW had actively engaged in community-based PHEM activities, whereas the majority (92.6%) and 94.4% of HEW did not report suspected non-Measles rash febrile illness and suspected NP-AFP cases, respectively, in the last six months (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e: \u003cem\u003eHealth emergency preparedness and response at the health post level in Tigrai, Ethiopia, Feb. 2024\u003c/em\u003e\u003c/p\u003e \u003cp\u003eOut of the surveyed zones, malaria outbreaks were reported from five health posts, namely, Selam health post (Asegede woreda), Mayliham health post (Bora woreda), Metikel health post (Enderta woreda), Werie health post (Maykinetal woreda), and Finariwa health post (Samire woreda), and scabies outbreaks were also reported from Tsankanaet health post (Tsaedaemba woreda). Both of the outbreaks (malaria and scabies) had been reported by health extension workers, but providentially, there was no death reported during the survey.\u003c/p\u003e \u003cp\u003eWith respect to the action taken for the outbreaks that have been reported in the last six months, most (83.3%) of the outbreak actions/measures have been taken by woreda surveillance focal persons and two-thirds (66.6%) each by health extension workers (HEWs) and partners/stakeholders (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e: \u003cem\u003eOutbreak response, health actors and stakeholders in Tigrai, Ethiopia, February 2024\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWith respect to malaria case management at the level of health posts, approximately two-thirds (64.80%) of the respondents had been diagnosed with malaria cases via RDT; the majority (97%) of the cases were treated for malaria, and most (85.70%) were referred to as malaria cases for further action (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e: \u003cem\u003eMalaria management at the health post level in Tigrai, Ethiopia, February 2024\u003c/em\u003e\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3. Health emergency status at the district health office level\u003c/h2\u003e \u003cp\u003eAll the selected health offices (100%) included in the survey had a functional surveillance and early warning system across all health facilities, but only sixteen (66.7%) of the woreda health offices had functional emergency operation and coordination centers, and 18 (75%) of the offices had expertise in communication during emergencies.\u003c/p\u003e \u003cp\u003eAmong the respondents, only 8 (33.3%) of the woreda health offices had used digital means to report weekly surveillance systems. Most of the woredas 21 (87.5%) reported complete surveillance data on time. The majority 22 (91.7%) of the woredas health offices had annual plans. Approximately 20 (83.3%) of the woreda health offices had risk assessment and mitigation plans (Table\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cem\u003eTable\u0026nbsp;3: Preparedness and response from interviews and observations in woreda health offices of Tigrai, Ethiopia, Feb, 2024\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWith respect to the reporting of non-measles febrile rash and non-polio acute flaccid paralysis (NP-AFP), less than half 11 (45.8%) and only 6 (25%) of the woreda health offices reported non-measles febrile rash illness and NP-AFP cases, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e: \u003cem\u003eReporting childhood illnesses from the woreda health offices of Tigrai, Ethiopia, Feb, 2024\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study results provide insights into vital details of health emergency preparedness and response in the war ridden Tigrai regional state. From the perspective of health emergency preparedness and response dimensions, planning and reporting of health incidents at the woreda level is the mainstay of health emergency management; the southeastern zone had only 33.3% of its facilities equipped with health emergency plans, 80% of the facilities in Eastern and 50%, and the Mekelle zone did not have plans during the survey. Similarly, almost all zones did not report suspected cases of nonpolio acute flaccid paralysis (NP-AFP), except for the Mekelle zone. This has placed the emergency preparedness and response of the region within the range of low percentage scores, and the results are congruent with those of studies conducted in selected health institutions in the Amhara region, Tunisia, and Italy (\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to the data obtained from the health facilities, irrespective of the increasing occurrence of public health emergencies, the planning capability, prompt reporting and response of public health incidents were found to be low; more than half (53.1%) of the districts, (54.6%) of the primary hospitals, and (52.2%) of the health centers in the study area had no specific health emergency plans. Similarly, more than half (53.1%) of the districts and (52.2%) health centers and two-thirds (66.6%) of the primary hospitals did not report outbreak-prone diseases. Similarly, more than half (56.5%) of the health centers and (59.4%) of the districts and almost two-thirds (66.6%) of the primary hospitals stated that they failed to investigate and treat outbreak prone cases in the study area. This result is consistent with the results of a study conducted in western Ethiopia and Saudi Arabia (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe findings of the present study revealed that communication and information management readiness were insufficient. Most (84.4%) of the districts and the majority (91.3%) of the health centers reported that they did not use digital technologies for reporting surveillance data. Most (78.1%) of the districts (87%) of the health centers and (54.6%) of the primary hospitals did not report non-measles febrile rash, and the majority (90.6%) of the districts (95.7%) of the health centers and (77.8%) of the primary hospitals did not report suspected NP-APF cases. This finding was consistent with the findings of similar studies performed elsewhere (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e); however, these results contrast with the results of studies conducted in Europe (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This implies that primary health care units must create a well-functioning communication and information management system for efficient and prompt public health emergency management.\u003c/p\u003e \u003cp\u003eNotably, impediments to the coordination and collaboration of the community and event-based surveillance were identified as insufficient during the survey, with considerably low coordination and collaboration with other emergency response agencies. Only 61.1% of the health extension workers at health posts had actively engaged in community-based health emergency management activities. Concerning the action taken for the outbreaks, most (83.3%) of the outbreak measures have been taken by the woreda PHEM surveillance focal person alone and two-thirds (66.6%) each by health extension workers (HEWs) and stakeholders. This unsatisfactory performance of collaboration in emergency health incidents is in line with studies conducted in sub-Saharan African countries and South Asia, China and the United States(\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe use of real-time data to inform healthcare providers, public health experts and government decision makers is crucial for emergency health management; digitalizing alert notification and communication for prompt and timely responses has been remained low in most of the surveyed health institutions. This result is similar to that of a study carried out in the developed world and Southwest Ethiopia (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). This has indicated that due emphasis must be given to the importance of adequate preparation and response during emergencies, advocating for centralized digital communication systems and prompt feedback circles. The observed low performance of health emergency preparedness and response in this study could be due to deliberate damage to the health care system during the war.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations of the study\u003c/h2\u003e \u003cp\u003eThis study has benchmarked the competency framework to evaluate the public health emergency preparedness and readiness of the region. Nevertheless, recall bias may be introduced during data collection, as some of the variables need to be recalled to situations that have occurred a few months prior. The inability to include inaccessible health institutions is due to security reasons, and the findings may not be generalizable.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe current findings revealed that primary health care facilities are challenged by the need to maintain meticulous health emergency preparedness and readiness activities. Owing to the existing postwar administrative structure, a lack of conceptual health emergency preparedness and readiness, disparities across zones and districts, and insufficient application of digital technologies lag behind. Furthermore, the study revealed the following important issues: low reporting, verification, and investigation of alerts promptly; poor coordination, collaboration and planning at all levels of health services and partners; and low community engagement in health emergency preparedness and response; as a result, there was evidence of re-emergence of previously controlled diseases. Forthcoming priorities should be to develop the response stage, establish closed feedback between the preparedness and recovery stages, and strengthen capacity building in collaboration with stakeholders through increasing training and improving quality prompt responses with relevant partners/stakeholders. Digitalizing alert notifications and communication for prompt response and strengthening electronic public health emergency management (ePHEM) by integrating with the available work force with due attention in the war-ridden localities. The implementation of community platforms (community-based and event-based surveillance) that enhance community engagement, particularly in public health emergency activities, should be strengthened.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was obtained from the Tigrai Health Research Institute (THRI)\u0026nbsp;(Reference number: THRI/4031/0503/16). A letter of support was secured from the Tigrai Health Bureau, and permission was also obtained from the selected districts. The participants and institution representatives provided consent via an information sheet that described the purpose, procedure, and confidentiality of the study. The right to withdraw from participation was also asked. All the collected data were handled anonymously, confidentially, and securely.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available on request\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors, give their consent for the publication of this research article to be published in the journal BMC Conflict and Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTigray Health Bureau has financially supported this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMTA, AAA, HGW, MH and MGW wrote the proposal, performed the statistical analysis and drafted the paper. HDH, GBG, TB, HG and MME approved the proposal with some revisions and participated in the design of the study and data analysis. YBT, AKB, GGM, GGG, MHD, MHA, RE and MGB\u0026nbsp;supervised and coordinated the data collection and participated in the statistical analysis. All the authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our heartfelt thanks to the Tigrai Health Bureau, study participants, data collectors, supervisors, district health offices, and local administrators for their cooperation during the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCao K. Interpretation of Regulations on Preparedness for and Response to Emergent Public Health Hazards. Beijing: China Legal Publishing House; 2003. (in Chinese).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRose DA, Murthy S, Brooks J, Bryant J. The evolution of public health emergency management as a field of practice. Am J Public Health. 2017;107(S2):S126\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOyebanji O, Ibrahim Abba F, Akande OW. Building local capacity for emergency coordination: establishment of subnational. Public Health Emerg Oper Centers Nigeria. 2021;6(10).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrganization WH. Standard operating procedures for coordinating public health event preparedness and response in the WHO African Region. 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchnall A, Nakata N, Talbert T, Bayleyegn T, Martinez D, Wolkin A. Community Assessment for Public Health Emergency Response (CASPER): an innovative emergency management tool in the United States. Am J Public Health. 2017;107(S2):S186\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdini B, Ohana A, Furman E, Ringel R, Golan Y, Fleshler E et al. Learning lessons in emergency management: the 4th International Conference on Healthcare System Preparedness and Response to Emergencies and Disasters. Disaster and military medicine. 2016;2:1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAliyu A. Management of disasters and complex emergencies in Africa: The challenges and constraints. Ann Afr Med. 2015;14(3):123\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarbera JA, Yeatts DJ, Macintyre AG. Challenge of hospital emergency preparedness: analysis and recommendations. Disaster Med Pub Health Prep. 2009;3(S1):S74\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgency CS. Population Size by Sex, Region, Zone and Wereda: July 2021. Ethiopia: CSA: Addis Ababa; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchor KW, Altman BA. Proposals for aligning disaster health competency models. Disaster Med Pub Health Prep. 2013;7(1):8\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrganization WH. WHO benchmarks for strengthening health emergency capacities. World Health Organization; 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNelson C, Lurie N, Wasserman J, Zakowski S. Conceptualizing and defining public health emergency preparedness. American Public Health Association; 2007. pp. S9\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyenew T, Tassew SF, Workneh BS. Level of emergency and disaster preparedness of public hospitals in Northwest Ethiopia: A cross-sectional study. Afr J Emerg Med. 2022;12(3):246\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrganization WH. Health emergency and disaster risk management framework. 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGeniosa BP, Aini Q. Hospital preparedness level and policy implementation analysis of hospital disaster plan in RSUD Kota Yogyakarta. J Indonesian Health Policy Adm. 2020;5(3).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLamine H, Tlili M, Aouicha W, Taghouti E, Chebili N, Zedini C. Disaster preparedness level of university hospitals of Sousse-Tunisia. Eur J Pub Health. 2020;30(Supplement5):ckaa166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBajow NA, Alkhalil SM. Evaluation and analysis of hospital disaster preparedness in Jeddah. Health. 2014;6(19):2668.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWoyessa AH, Teshome M, Mulatu B, Abadiga M, Hiko N, Kebede B. Disaster preparedness in selected hospitals of western Ethiopia and risk perceptions of their authorities. Open access Emerg Med. 2020:219\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoka PM, Sawe HR, Mbaya KR, Kilindimo SS, Mfinanga JA, Mwafongo VG, et al. Disaster preparedness and response capacity of regional hospitals in Tanzania: a descriptive cross-sectional study. BMC Health Serv Res. 2018;18:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIngrassia PL, Mangini M, Azzaretto M, Ciaramitaro I, Costa L, Burkle FM Jr, et al. Hospital Disaster Preparedness in Italy: a preliminary study utilizing the World Health Organization Hospital Emergency Response Evaluation Toolkit. Minerva Anestesiol. 2016;82(12):1259\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGooding K, Bertone MP, Loffreda G, Witter S. How can we strengthen partnership and coordination for health system emergency preparedness and response? Findings from a synthesis of experience across countries facing shocks. BMC Health Serv Res. 2022;22(1):1441.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Dong C, An S, Mai Q, editors. Dynamic evolution analysis of the emergency collaboration network for compound disasters: A case study involving a public health emergency and an accident disaster during COVID-19. Healthcare: MDPI; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWolf-Fordham S. Integrating government silos: Local emergency management and public health department collaboration for emergency planning and response. Am Rev Public Adm. 2020;50(6\u0026ndash;7):560\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDamaševičius R, Bacanin N, Misra S. From sensors to safety: internet of Emergency Services (IoES) for emergency response and disaster management. J Sens Actuator Networks. 2023;12(3):41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBerhanu N, Abrha H, Ejigu Y, Woldemichael K. Knowledge, experiences and training needs of health professionals about disaster preparedness and response in southwest Ethiopia: a cross sectional study. Ethiop J health Sci. 2016;26(5):415\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003eTable 3 is not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Health emergency, preparedness and response, competency framework Tigrai, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-5312606/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5312606/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Public health emergency preparedness and readiness stand for quickly obtaining and effectively using relevant information and resources to improve the efficiency of emergency response to minimize harm and negative impacts. Ethiopia has been used to pursue health emergency procedures for decades; however, there is a paucity of scientific evidence. This study aimed to assess public health emergency preparedness and response benchmarking in the competency framework within the local context during the postwar period in Tigrai, Ethiopia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA quantitative cross-sectional study was carried out using semi-structured piloted interviewer-administered tools extracted from the core domains of the competency framework to collect the necessary data. The study included 110 randomly selected health institutions (primary hospitals, N=9; health centers, N=23; health posts, N=54; and district health offices, N=24. An Open Data Kit was used to collect the data, which were then exported to SPSS version 27 for data analysis. Finally, the overall status of preparedness and readiness was classified as low if the percentage score was 33%-66.6% and high if it was 66.7%-100%. The data are presented in text narratives, graphs and tables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: More than half (53.1%) of the district health offices, 54.6% of the primary hospitals, and 52.2% of the health centers in the study area have no specific health emergency plans. Similarly, more than half (53.1%) of the districts, 52.2% of the health centers and 66.6% of the primary hospitals did not report outbreak-prone diseases. More than fifty-six percent of the health centers, 59.4% of the districts and almost two-thirds (66.6%) of the primary hospitals reported that they failed to investigate and treat the outbreaks observed in the study area.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The current findings revealed that primary health care units, along with district health offices, were challenged in maintaining basic health emergency preparedness and readiness. Disease surveillance, readiness and response with a collaborative and coordinated action of the region and stakeholders was unacceptably low. Thus, strengthening supervision, proper health emergency planning, digitalizing swift reporting activities and establishing functional regional links through intensified training of health professionals at all levels of health services are recommended.\u003c/p\u003e","manuscriptTitle":"The Status of Public Health Emergency Preparedness and Response in the War-Ridden Tigrai, Ethiopia: A descriptive study benchmarking the Competency Framework","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-05 15:19:38","doi":"10.21203/rs.3.rs-5312606/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-10-24T09:35:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-24T00:28:39+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-10-24T00:26:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Health Services Research","date":"2024-10-22T14:11:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-health-services-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bhsr","sideBox":"Learn more about [BMC Health Services Research](http://bmchealthservres.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/BHSR/default.aspx","title":"BMC Health Services Research","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"343ab8ff-547d-4a1b-9128-8fc6b558212b","owner":[],"postedDate":"November 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-16T09:08:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-05 15:19:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5312606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5312606","identity":"rs-5312606","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}