{"paper_id":"400d3ffd-ee24-412f-9e3a-e0f56f9233ea","body_text":"A Nationally Representative One Health Multi-Pathogen Serosurvey in Cambodia: Study Protocol for the RACSMEI Mixed-Methods Study | 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 Study protocol A Nationally Representative One Health Multi-Pathogen Serosurvey in Cambodia: Study Protocol for the RACSMEI Mixed-Methods Study Andrea ANTONIOLLI, Erik KARLSSON, Tephanie SIENG, Sébastien BOYER, and 37 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9382926/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Cambodia faces a high and complex burden of zoonotic, vector-borne, vaccine-preventable and environmentally transmitted infections, driven by intensive human–animal–environment interactions. However, nationally representative data integrating human, animal and environmental dimensions of pathogen exposure remain limited. The RACSMEI (Risk Assessment of Community Spread of Multiple Endemic Infectious Diseases in a One Health Perspective) study aims to address this gap through a nationwide One Health serosurvey designed to generate policy-relevant epidemiological evidence for precision public health and integrated surveillance. Methods/design : RACSMEI is a nationwide, cross-sectional, mixed-methods study conducted across all 25 provinces of Cambodia. Using a stratified, multi-stage cluster sampling design, approximately 15,000 individuals aged 2–75 years will be enrolled from 4,160 households in 104 randomly selected villages. Human, animal (poultry, pigs, dogs, cattle, small ruminants, rodents) and environmental (water, soil, air, surface swabs) samples will be collected. Exposure to more than 50 endemic, emerging, vaccine-preventable and elimination-targeted pathogens will be assessed using multiplex serological assays, molecular diagnostics and metagenomics sequencing approaches. Quantitative surveys will be complemented by semi-structured interviews and focus group discussions to explore social, behavioural and health system determinants of infection risk and care-seeking behaviours. Analyses will account for the complex survey design and integrate epidemiological, environmental and social science data. Discussion By combining nationally representative sampling with integrated human, animal, environmental and social science data, RACSMEI aims to generate comprehensive evidence on infectious disease exposure and transmission risks across diverse socio-ecological contexts in Cambodia. The study will provide policy-relevant insights to support One Health surveillance strategies and targeted public health interventions. The protocol was approved by the Cambodian National Ethics Committee for Health Research and the Institutional Review Board of Institut Pasteur Paris. Trial registration : ClinicalTrials.gov identifier: NCT07358910. Registered 14 January 2026. One Health Seroepidemiologic study Population-based study Multi-pathogen surveillance Zoonotic diseases Mixed-methods research Cambodia Figures Figure 1 Figure 2 Introduction In low- and middle-income countries (LMICs), controlling emerging and infectious diseases remains a major challenge, driven by limited access to diagnostics, fragmented surveillance systems and the lack of integrated population-level epidemiological data [1]. These constraints hinder accurate assessment of disease burden, transmission dynamics and populations at risk, ultimately limiting the effectiveness of prevention and control policies. Existing research addressing these gaps is often pathogen-specific, resource-intensive or restricted to selected high-risk groups, which limits the ability to characterise infectious disease risks comprehensively at the national scale. In this context, Precision Public Health has emerged as a key approach to optimise resource allocation and guide targeted interventions using multi-level epidemiological data on disease burden, transmission drivers and population vulnerability [2–4]. To be effective, however, precision public health approaches must be grounded in One Health principles [5–8] , explicitly integrating human, animal and environmental dimensions of infectious disease transmission. Such integration is particularly critical in settings where zoonotic, vector-borne and environmentally mediated pathogens circulate within shared ecological and socio-economic systems , despite the operational challenges associated with implementing integrated surveillance frameworks [9,10]. Cambodia represents a high-priority setting for implementing integrated One Health surveillance. The country’s strong reliance on agriculture and livestock production, which supports nearly half of Cambodian households, creates favorable conditions for zoonotic spillover at the human–animal–environment interface [11]. Vector-borne pathogens such as Japanese encephalitis virus (JEV) and dengue virus (DENV) circulate endemically [12–15], while avian influenza viruses (AIV) are regularly detected in domestic poultry, production systems and live-bird markets networks, with documented zoonotic transmission to humans and recurrent circulation of highly pathogenic A(H5N1) strains [16–20]. These challenges are reflected in the national One Health Zoonotic Disease Prioritization process conducted in Cambodia, which identified several zoonotic pathogens of major public health concern requiring strengthened multisectoral surveillance and coordination [21]. Despite this recognized burden, nationally representative data integrating human, animal and environmental dimensions of pathogen circulation remain scarce. Recent advances in sero-epidemiological methods have transformed population-based surveys into powerful tools for monitoring infectious disease burden, identifying emerging threats and informing public health interventions such as vaccination strategies, biosafety measures and vector control [22–28]. In particular, multiplex serological platforms enable the simultaneous investigation of a wide spectrum of pathogens, including endemic, emerging, vaccine-preventable and elimination-targeted diseases within a single integrated survey [26,29–31]. These technologies now allow the efficient generation of large-scale multi-pathogen exposure profiles in population-based samples , providing critical insights into cumulative exposure, immunity gaps and heterogeneity in transmission risk across populations. Transmission of arboviruses (including dengue, chikungunya, Zika and JEV), zoonotic pathogens such as AIV, hantaviruses and leptospirosis, and environmentally mediated infections such as melioidosis is influenced by multiple interacting factors operating at individual (e.g. age, mobility, human behaviours), household (e.g. water storage, animal husbandry, vector control) and broader community contexts (e.g. urbanisation, vector density, biosafety infrastructure) [25,31–34]. Quantifying the relative contribution of these drivers is essential to inform effective, context-adapted and equity-oriented control strategies [35,36]. However, many serological studies rely on convenience samples or selected high-risk populations, often in accessible urban or rural settings [32,37–41]. While informative, these designs do not provide a nationally representative picture of infection risk and immunity. In contrast, population-based sampling across randomly selected communities allows robust estimation of national and subnational seroprevalence, identification of spatial heterogeneity and transmission hotspots and a better understanding of infection risks across diverse socio-ecological contexts. The RACSMEI (Risk Assessment of Community Spread of Multiple Endemic Infectious Diseases) project was designed to address these gaps through a nationwide, integrated One Health serosurvey in Cambodia. By combining harmonised human, animal, environmental and social science data, RACSMEI aims to characterise transmission risks across a broad spectrum of pathogens and to identify key determinants of exposure at multiple scales. Through standardised methodologies, advanced laboratory platforms and close collaboration with national ministries, the project seeks to generate policy-relevant epidemiological evidence to support targeted and culturally appropriate interventions. Beyond its immediate objectives, RACSMEI provides a scalable methodological framework for integrated multi-pathogen surveillance in LMICs, contributing to strengthened national preparedness and offering a proof of concept for the operationalisation of large-scale One Health surveillance approaches. Objectives Primary Objective The primary objective of RACSMEI is to characterise the burden, transmission dynamics and multi-level determinants of exposure to priority endemic and emerging infectious diseases in Cambodia using a nationally representative One Health approach. Secondary Objectives The secondary objectives are to: Estimate population-level exposure and infection patterns for selected zoonotic, vector-borne and environmentally mediated pathogens in human and animal populations. Describe the spatial distribution and heterogeneity of pathogen circulation in order to identify high-risk areas and transmission hotspots and inform targeted public health interventions. Identify transmission drivers at individual, household and community levels by integrating biomedical, behavioural, environmental and socio-demographic factors. Reconstruct historical transmission dynamics using age-stratified serological profiles to infer past outbreaks and changes in transmission intensity. Assess the presence and diversity of selected pathogens in environmental matrices, including water, soil and other high-risk human-animal-environment interface sites. Establish a national biobank of human, animal and environmental samples to support long-term surveillance, molecular characterisation and future research. Explore community perceptions of infectious disease risks, prevention practices, care-seeking behaviours and the acceptability of public health interventions. Extend surveillance to selected vaccine-preventable, emerging and elimination-targeted diseases to support integrated and adaptive One Health surveillance strategies. Methods/design Study design RACSMEI is a nationally representative cross-sectional mixed-methods One Health study conducted across all 25 provinces of Cambodia. A stratified, multi-stage cluster sampling design was implemented to ensure representativeness across provinces and major ecological settings. Approximately 15,000 participants aged 2–75 years are enrolled from randomly selected households in 104 villages. Human participants are sampled in all selected households. Domestic animal and household-level environmental surface sampling are conducted according to a stratified protocol. Rodent trapping and vector collections are performed in a predefined subset of households per village following standardised ecological procedures. Environmental samples (water, soil and air) are additionally collected at predefined human–animal–environment interface sites within selected villages, including slaughter areas, wet markets, shared water access points and agricultural areas. Quantitative surveys are complemented by semi-structured interviews with key community and institutional stakeholders and focus group discussions to capture social and behavioural determinants of exposure, care-seeking behaviours and the acceptability of public health interventions. Study setting and population The study is conducted in 104 randomly selected villages covering urban, peri-urban and rural settings across Cambodia (Figure 1). The primary sampling units are randomly selected households, from which nationally representative estimates for the human population are derived using weighted analyses. Within these households, the study includes human participants and livestock-owning households selected according to a stratified protocol. Rodent trapping, vector collections and additional ecological investigations are conducted in a predefined subset of households and are used to support integrated transmission analyses. Qualitative data are collected from purposively selected community and institutional stakeholders within the selected villages. This integrated design enables nationally representative human estimates while incorporating ecological and stakeholder perspectives to better understand transmission dynamics across diverse socio-ecological contexts. Sampling design and household selection A multistage stratified cluster sampling design was used to obtain a nationally representative sample. In each of the 25 provinces of Cambodia, districts were randomly selected (four districts per province in 22 provinces, two in two smaller provinces and twelve in Phnom Penh). One village was randomly selected per district, yielding a total of 104 villages. Within each village, 40 households were randomly selected from a complete household census conducted prior to the survey, resulting in a total sample of 4,160 households. All household members aged 2–75 years were invited to participate. Individuals outside this age range or unable to provide informed consent (or assent for minors) were not eligible for biological sampling. The expected sample size was approximately 15,000 participants , assuming a minimum average of 3.6 eligible individuals per household and a participation rate of 60%. Sample size calculations assumed a seroprevalence of 50%, a design effect of 2, a 95% confidence level and a margin of error of 1%. Precision estimates under alternative sampling scenarios are presented in Figure 2. Livestock and environment sampling To ensure representation of livestock species, households were classified during the census according to livestock ownership and assigned to mutually exclusive strata using a hierarchical approach prioritising less frequent species (small ruminants, pigs, cattle, poultry and dogs). Within each village, 20 livestock-owning households were selected using stratified simple random sampling, while 20 households without animals were independently selected using simple random sampling. Within livestock-owning households, domestic animals were sampled among the species present in the household . Sampling focused on apparently healthy animals and aimed to include a limited number of individuals per species to minimise disruption to household activities. T arget sample sizes per village were approximately 50–100 poultry, 5–15 pigs, 5–15 small ruminants, 5–15 cattle and 15–25 dogs , depending on local livestock availability. Environmental sampling at household level consisted of five surface swabs collected in five households per village, taken inside and immediately outside participating households. In addition, nine environmental samples per village (three water, three soil and three air samples) were collected at predefined human–animal–environment interface sites, including slaughter areas, wet markets, shared water access points, waste disposal sites and agricultural areas. Rodent trapping and entomological collections were conducted in a subset of 10 households within each village according to standardised ecological protocols. These ecological samples are primarily intended to support integrated transmission analyses rather than to generate population-representative prevalence estimates. Outcome and pathogens detection RACSMEI investigates exposure to a broad spectrum of infectious agents reflecting Cambodia’s epidemiological priorities, using a structured outcome framework aligned with public health relevance, feasibility and policy utility. Pathogens were selected in close collaboration with national stakeholders based on endemicity, epidemic potential, zoonotic or environmental transmission, availability of preventive tools and relevance for integrated One Health surveillance. The analytical strategy distinguishes primary outcomes (priority pathogens), secondary outcomes (expanded pathogen panels) and exploratory outcomes (environmental and metagenomic detection) based on the analytical capacity of multiplex serological and molecular platforms. Primary outcomes Primary outcomes focus on estimating population-level exposure to priority endemic and emerging pathogens, including arboviruses, zoonotic and emerging viruses, bacterial zoonoses and parasitic infections (Table 1). Seroprevalence of pathogen-specific antibodies constitutes the primary outcome measure in humans and selected animal populations. Molecular detection (RT-qPCR) is performed for pathogens with active circulation or amplification potential in relevant animal hosts and environmental samples. During household visits, venous blood samples are collected from participants (up to 10 mL in adults and children ≥7 years; up to 5 mL in children <7 years). Livestock and dogs undergo blood sampling, while poultry and pigs additionally undergo oral and rectal swabbing, and ectoparasites (ticks, fleas) are collected for speciation and metagenomic sequencing. All animal sampling is conducted by trained personnel from the Ministry of Agriculture, Forestry and Fisheries. Rodent trapping is conducted in and around 10 households per village over two consecutive nights, using a total of 50 live traps per village. Traps are placed inside and around selected households following standardised ecological protocols to capture small mammal reservoirs potentially involved in zoonotic pathogen transmission. Entomological investigations In addition, entomological surveys are conducted in each village in a subset of randomly selected households. Adult mosquitoes are collected outdoors for 24 hours in 10 households per village using BG-Sentinel traps and CDC light traps to assess vector density and species diversity [42]. These data will contribute to the generation of national-scale entomological risk maps and support integrated analyses of vector-borne disease transmission. Secondary outcomes: expanded serological profiling Secondary outcomes include expanded serological profiling of vaccine-preventable, elimination-targeted, emerging, enteric and neglected tropical pathogens to inform longer-term surveillance and policy planning (Additional File 1). Exploratory environmental surveillance uses probe-enriched metagenomic sequencing of water, soil, air and surface samples to detect circulating or emerging pathogens and characterise microbial diversity at high-risk environmental interfaces. Laboratory procedures Human and animal blood samples are analyzed using a bead-based multiplex microsphere immunoassay developed by Institut Pasteur Paris, enabling simultaneous detection of antibodies against up to 100 antigens when using the Bioplex 200 multiplexing platform, and up to 500 antigens when using the Luminex INTELLIFLEX. Molecular diagnostics, including RT-qPCR and metagenomic sequencing, are used to detect active infections and characterise pathogen diversity in animal and environmental samples. Data collection Quantitative data are collected using standardised questionnaires covering socio-demographic characteristics, household and environmental conditions, clinical and vaccination history, and knowledge, attitudes and practices related to infectious diseases (Additional File 2). GPS coordinates are recorded to support geospatial analyses. Qualitative data are collected through semi-structured interviews (Additional File 3) and focus group discussions with community members, leaders and key stakeholders to explore risk perceptions, care-seeking pathways and the acceptability of public health interventions. Data management and analysis Data are collected using REDCap on encrypted tablets and stored on secure servers at the Institut Pasteur du Cambodge. Pseudonymisation is ensured through unique identifiers, and access is restricted to authorised personnel. Weighted prevalence estimates and 95% confidence intervals are calculated while accounting for the complex survey design. Multivariable regression models are used to identify individual-, household- and community-level determinants of exposure. Age-stratified serological data are analysed using mathematical transmission models to reconstruct historical transmission dynamics across demographic groups and geographic areas. Trial registration The study is registered on ClinicalTrials.gov (NCT07358910). The study was retrospectively registered on 14 January 2026. Dissemination Plan Study findings will be shared with participating communities through dedicated public dissemination events and structured feedback sessions presenting and discussing key preliminary results. To minimise the risk of community stigmatisation, results will be reported and discussed at national and provincial levels rather than at the level of individual villages. Results will also be communicated to national authorities from the health, agriculture and environment sectors through the Interministerial One Health Coordination Committee (IMCC) to support evidence-based surveillance and control strategies. Scientific dissemination will include publication in open-access, peer-reviewed journals to ensure broad accessibility and support the downstream use of project results, as well as presentations at national and international scientific conferences. A bilingual (Khmer and English) summary of key findings will be made publicly available online and disseminated through the project’s annual newsletter to promote transparency and knowledge sharing. Discussion This study describes the design and early implementation of RACSMEI, which, to our knowledge, represents one of the first nationally representative One Health multi-pathogen serosurveys integrating human, animal and environmental data within a single population-based framework in a low- and middle-income country . By combining epidemiological, ecological and social science data collected at national scale, the study aims to generate comprehensive evidence on exposure patterns and transmission risks for multiple infectious diseases across diverse socio-ecological contexts. The study integrates nationally representative sampling, multiplex laboratory diagnostics and mixed-methods social science investigations, providing a unique opportunity to better characterise transmission risks at the human–animal–environment interface. Such integrated national surveys remain rare, particularly in low- and middle-income countries where surveillance systems are often fragmented across human, animal and environmental sectors. By combining multiplex serology, ecological investigations and social science approaches within a single nationally representative framework, RACSMEI also contributes to advancing methodological approaches for integrated multi-pathogen surveillance in resource-constrained settings. Large-scale serological surveys have increasingly been used to complement routine surveillance systems by providing insights into population-level exposure to infectious diseases that are often underreported or poorly captured by passive surveillance [23–26,31,32,44,45]. National serosurveys conducted in several settings have demonstrated the value of multiplex serology for investigating exposure to multiple pathogens within a single survey framework. Such approaches have generated new epidemiological insights, including the identification of previously unrecognised hotspots of infection and the reconstruction of past circulation dynamics of several pathogens, thereby improving understanding of transmission patterns and informing targeted public health responses [24,27,31,32]. RACSMEI builds upon these experiences while extending them to an integrated One Health surveillance framework. Previous analyses have shown that many studies claiming to adopt a One Health framework often remain limited to the human health component, with animal and environmental dimensions insufficiently integrated into study design and data collection. By explicitly incorporating animal sampling, environmental investigations and social science components alongside human serology, RACSMEI aims to provide a more comprehensive and system-level understanding of transmission dynamics. The integration of animal and environmental components is particularly important for pathogens whose transmission dynamics cannot be fully understood through human data alone [7,46,47]. For several zoonotic infections, including arboviruses and other emerging pathogens, circulation in animal reservoirs or vectors may precede or exceed detectable transmission in human populations. For example, surveillance of animal hosts and vectors has contributed to early detection of circulation for pathogens such as West Nile virus or Crimean–Congo haemorrhagic fever in several settings, allowing authorities to strengthen preparedness before human cases were widely detected. Similar dynamics may occur for several pathogens included in RACSMEI, such as avian influenza viruses, Nipah virus or hantaviruses, where circulation in animal reservoirs may provide earlier or more detectable signals of transmission than human surveillance alone. Community engagement played an essential role in the feasibility and acceptability of the survey. The involvement of village leaders and community representatives during the preliminary household census helped build trust and facilitated accurate household enumeration. In parallel, semi-structured interviews with local and provincial stakeholders were conducted shortly before and during field activities. This approach helped clarify the objectives of the study, address potential concerns and strengthen coordination between survey teams, local authorities and community actors, thereby facilitating the smooth implementation of field operations. Beyond its immediate epidemiological objectives, RACSMEI also functioned as a capacity-building platform. Training activities in epidemiology, field coordination, and project management strengthened the ability of the research team to plan, implement and monitor complex multi-stakeholder activities. Participatory engagement and repeated interactions with communities and stakeholders also strengthened awareness of One Health principles and highlighted the value of integrated approaches to understanding transmission risks at the human–animal–environment interface. The integration of qualitative components further enhances the usability of findings by explicitly addressing social and behavioural determinants, such as risk perception, care-seeking pathways and acceptability of interventions, which are often critical for the effective implementation of public health policies. At the national level, RACSMEI is designed to generate evidence that is directly relevant for public health decision-making in Cambodia. The stratified sampling strategy captures diverse socio-ecological contexts across urban, peri-urban and rural settings, enabling comparison of exposure patterns across regions and identification of both shared and context-specific determinants of transmission. Rather than producing isolated local estimates, the study aims to support the development of nationally relevant indicators that can inform integrated surveillance strategies and public health interventions. The establishment of a nationally representative biobank further enhances the long-term value of the study by enabling future analyses addressing emerging research and surveillance priorities without requiring additional large-scale field operations. Beyond Cambodia, RACSMEI provides a proof of concept for the implementation of large-scale One Health surveillance in low- and middle-income countries. While epidemiological patterns are context-specific, the integrated methodological framework, combining population-based sampling, multiplex serology, environmental investigation, stakeholder engagement and community participation, is potentially scalable and adaptable to other settings facing similar structural and epidemiological challenges. In this respect, RACSMEI contributes to the operationalisation of One Health beyond conceptual frameworks, offering practical lessons for national-level implementation. The study therefore provides an empirical foundation for strengthening integrated One Health surveillance systems and for informing data-driven public health strategies in Cambodia and other settings facing similar epidemiological and health system challenges. Strengths and limitations Strengths This study represents the first nationwide One Health serosurvey conducted in Cambodia, integrating human, animal, environmental and social science data within a single population-based design. The nationally representative sampling strategy captures heterogeneity in socio-ecological contexts, livelihoods and geographic settings, enabling the generation of evidence that is directly relevant for national public health planning. A key strength of the study lies in its co-development with national authorities across the human, animal and environmental health sectors. The Ministry of Health, the Ministry of Agriculture, Forestry and Fisheries, and the Ministry of Environment were involved from the early stages of study conception and implementation through the national One Health coordination mechanisms. This multisectoral collaboration increases the likelihood that study findings will inform policy development and operational surveillance strategies. An important operational strength of the study lies in its nationwide coordination structure involving trained multidisciplinary field teams, established laboratory platforms and strong collaboration with national ministries, enabling the implementation of complex multi-sectoral surveys at national scale. By combining human serology with animal sampling, environmental investigations and qualitative research, RACSMEI aims to provide a more comprehensive assessment of transmission risks across the human–animal–environment interface. This integrated design responds to widely recognised challenges in the implementation of One Health approaches, where methodological fragmentation and limited cross-sector integration have often constrained the translation of interdisciplinary research into operational public health benefits, particularly in low- and middle-income countries [9,10,48–50]. The use of multiplex serological platforms allows the simultaneous investigation of more than 50 pathogens within a single survey, providing an efficient and scalable model for integrated infectious disease surveillance in low- and middle-income settings. This approach may serve as a transferable proof of concept for the design and implementation of nationally representative One Health surveillance systems in other resource-constrained settings. Limitations The cross-sectional design limits the ability to infer causal relationships or directly assess temporal dynamics of infection. Serological cross-reactivity, particularly among flaviviruses, may complicate pathogen-specific attribution. To address this limitation, multiplex antibody signatures will be interpreted alongside confirmatory seroneutralisation assays and age-structured transmission modelling approaches. In addition, the household sampling frame was derived from administrative listings at district level and did not include foreign residents, who represent less than 1% of the national population. While this exclusion is unlikely to substantially affect national estimates, exposure patterns in this subgroup may not be fully represented in the study population. Finally, the laboratory analyses required for the large multiplex panels are resource-intensive and may delay the availability of results. Study status Community engagement activities and preparatory workshops were conducted between September and October 2025. Enrollment, field data and sample collection for the nationwide population-based survey began on 18 December 2025 and are expected to be completed by 25 April 2026. Qualitative data collection, including focus group discussions and key informant interviews, is scheduled to take place between June 2026 and June 2027 as part of the mixed-methods study design. Laboratory analyses are being conducted in parallel from January to December 2026. Preliminary analyses and feedback to stakeholders are planned between November 2026 and June 2027. Final data analyses, modelling and dissemination activities will continue from 2026 through 2029. Declarations Ethics approval and consent to participate The study protocol was reviewed and endorsed by the Cambodian Interministerial Coordination Committee for One Health (IMCC-OH) and presented to national and provincial authorities prior to field implementation. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki and national regulations governing research involving human participants. Field teams, including investigators and nurses, were trained to visit selected households, explain the study objectives, obtain informed consent and conduct interviews and biological sampling according to the study protocol. All members of selected households aged 2–75 years are invited to participate during an initial face-to-face visit. Written informed consent is obtained from all adult participants. For participants under 18 years of age, written consent is obtained from a parent or legal guardian, and assent is sought from minors when appropriate. Participation was voluntary, and respondents could withdraw at any time without consequence. To support community understanding of the study, a dedicated information package including an educational comic booklet (Additional File 4) and a short explanatory video (available at: https://www.youtube.com/watch?v=dWmCdn80jaU&t=6s) was developed and presented to village leaders and participating households. These materials explain the objectives of the study, the voluntary nature of participation and participants’ rights regarding access to and correction of their personal data. Participant confidentiality is ensured through pseudonymisation procedures and secure data management systems. No identifiable personal information or precise household geolocation data will be reported in study outputs. Ethical approval was obtained from the Cambodian National Ethics Committee for Health Research (NECHR) (Approval No. 199, 2 May 2025; amendment No. 359, 22 July 2025) and from the Institutional Review Board of the Institut Pasteur in Paris (Ref. 2025-145, 8 October 2025). Animal sampling procedures follow internationally recognised animal welfare standards. Capture, handling and euthanasia procedures are performed by trained personnel and aim to minimise stress and suffering. Rodents are humanely euthanised using isoflurane inhalation, and non-target species are released immediately at the capture site. All procedures comply with national veterinary regulations and the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health [43]. Animal-related procedures were additionally reviewed by the UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) during the Wellcome Trust funding evaluation. Consent for publication Not applicable. Availability of data and materials No datasets were generated or analysed for the current manuscript as this article describes a study protocol. Data generated during the RACSMEI study will be made publicly available in accordance with institutional policies and applicable ethical and legal regulations. Competing interests The authors declare no competing interests Funding This study is funded by the Wellcome Trust Discovery Award (Grant N°. 312353/Z/24/Z). Authors’ contributions CF conceived the study, secured funding, supervised the project, led the development of the study protocol and prepared the first draft of the manuscript. TeS, EK, SB, SoC and SiC contributed to funding acquisition, project supervision and protocol development. AA contributed to the development of the protocol, prepared the first draft of the manuscript and contributed to data visualisation. SL, SaS, MC, SoS, VibH, JAPA, SiS, KS, CN, SN, KN, PK and SI contributed to the development of the study protocol, standard operating procedures and investigation design. HG contributed to protocol development and the veterinary components of the study. VitH, VS, KN, CVP, EC and NH contributed to project management and operational coordination. SL and JAPA contributed to the supervision of field implementation and to the development of the study protocol. EK, MW, SP, PR, NS, BG and SpS contributed to the design and implementation of laboratory testing and diagnostic analyses. SK, TuS, CM and RH contributed as ministerial partners supporting study implementation and alignment with national public health strategies. JP contributed to the data analysis plan. PV contributed to data visualisation. MH, LV and MR contributed to the definition and development of community engagement activities. All authors revised and approved the final manuscript. Acknowledgements The authors would like to thank the Interministerial Coordination Committee for One Health (IMCC-OH) and the Cambodian Ministry of Health, the Ministry of Agriculture, Forestry and Fisheries, and the Ministry of Environment for their support and collaboration in the development and implementation of the RACSMEI study through the national One Health coordination mechanisms. We are grateful to the provincial and district health authorities, local administrative authorities and village leaders who facilitated the implementation of the study. We also thank the field investigators, nurses, laboratory technicians and data collection teams involved in the RACSMEI survey for their commitment and dedication. Finally, we sincerely thank the participating households and community members for their time and willingness to contribute to this study. 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Front Public Health. 2023;11:1252428. doi:10.3389/fpubh.2023.1252428 PubMed PMID: 38074697; PubMed Central PMCID: PMC10701386. Tables Table 1. Primary outcome pathogens investigated in RACSMEI by host and laboratory method Pathogen group Pathogen Humans Poultry Pigs Dogs Livestock (cattle, small ruminants) Rodents Environment Arboviruses Dengue virus (DENV 1–4) S – – S – – Chikungunya virus (CHIKV) S – – S – – Zika virus (ZIKV) S – – S – – Japanese encephalitis virus (JEV) S M S, M S – – West Nile virus (WNV) S M – S – – Zoonotic & emerging viruses Avian influenza viruses (AIV) S S, M S, M – – – M Nipah virus (NiV) S – S, M – – – M Hantaviruses S – – – – S, M M Severe fever with thrombocytopenia syndrome virus (SFTSV) S – – – – – Tick-borne encephalitis virus (TBEV) S – – – – – Bacterial zoonoses Leptospira spp. S – S S S S, M M Brucella spp. S – S S S S M Coxiella burnetii S S, M S S S S Burkholderia pseudomallei S – – – – – M Parasitic infections Plasmodium spp. S – – – – – Abbreviations: S = Serology; M : Molecular testing (RT-qPCR) ; – = Not tested. Additional Declarations No competing interests reported. Supplementary Files AdditionalFile1.pdf Additional File 1. Extended pathogen panel investigated in RACSMEI This table presents the extended panel of pathogens investigated as secondary or exploratory outcomes in RACSMEI, including vaccine-preventable, elimination-targeted, emerging, and environmentally mediated pathogens. These analyses leverage the multiplex serological platform and molecular assays to inform long-term surveillance priorities and policy planning AdditionalFile2Questionnaire.pdf Additional File 2. RACSMEI Questionnaire This document presents the full RACSMEI household and individual questionnaire as provided in the Supplementary Information of the study protocol. Questions are organized by thematic modules. Skip patterns are indicated where applicable. The questionnaire was administered by trained interviewers using electronic data capture tools. AdditionalFile3RACSMEISSI.pdf Additional file 3. RACSMEI qualitative interview guides. This file contains the semi-structured interview and focus group discussion guides used in the RACSMEI study to explore community perceptions of infectious disease risks, prevention practices, care-seeking behaviours and the acceptability of public health interventions. The guides were developed to support qualitative data collection with community members, local leaders, and institutional stakeholders in selected study sites. AdditionalFile4Booklet.pdf Additional file 4 – RACSMEI participant information booklet This file contains the illustrated information booklet used during community engagement activities to explain the study objectives, procedures and participants’ rights. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 15 May, 2026 Reviewers agreed at journal 12 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 15 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Submission checks completed at journal 13 Apr, 2026 First submitted to journal 10 Apr, 2026 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-9382926\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":false,\"archivedVersions\":[],\"articleType\":\"Study protocol\",\"associatedPublications\":[],\"authors\":[{\"id\":626129803,\"identity\":\"f6127f01-6775-44d5-88f9-5b2528c6d5c0\",\"order_by\":0,\"name\":\"Andrea ANTONIOLLI\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Andrea\",\"middleName\":\"\",\"lastName\":\"ANTONIOLLI\",\"suffix\":\"\"},{\"id\":626129804,\"identity\":\"bb7641f5-feda-4f3e-ba6a-5def3c8dd269\",\"order_by\":1,\"name\":\"Erik 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SOVANN\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Saren\",\"middleName\":\"\",\"lastName\":\"SOVANN\",\"suffix\":\"\"},{\"id\":626129841,\"identity\":\"9e024a1f-0607-4159-a835-368e420b6a30\",\"order_by\":23,\"name\":\"Mélanie HUBAULT\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Malaria Consortium\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mélanie\",\"middleName\":\"\",\"lastName\":\"HUBAULT\",\"suffix\":\"\"},{\"id\":626129842,\"identity\":\"210fbb6e-8908-448d-9595-80048a2c01c3\",\"order_by\":24,\"name\":\"Lieven VERNAEVE\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Malaria Consortium\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Lieven\",\"middleName\":\"\",\"lastName\":\"VERNAEVE\",\"suffix\":\"\"},{\"id\":626129844,\"identity\":\"4b1f3cb7-14ad-4076-88e6-572a2e869529\",\"order_by\":25,\"name\":\"Mousumi RAHMAN\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Malaria Consortium\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Mousumi\",\"middleName\":\"\",\"lastName\":\"RAHMAN\",\"suffix\":\"\"},{\"id\":626129845,\"identity\":\"03b4d321-fc63-4a80-81f1-72a4dbfa2d35\",\"order_by\":26,\"name\":\"Candy NAGO\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Candy\",\"middleName\":\"\",\"lastName\":\"NAGO\",\"suffix\":\"\"},{\"id\":626129847,\"identity\":\"86d1a097-e5e5-436b-a3e1-ac51a27a415b\",\"order_by\":27,\"name\":\"Sandrine NYOTUE\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sandrine\",\"middleName\":\"\",\"lastName\":\"NYOTUE\",\"suffix\":\"\"},{\"id\":626129858,\"identity\":\"6c3015c0-2538-46a3-84da-f3050e6ab3b7\",\"order_by\":28,\"name\":\"Vouchleang SRENG\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Vouchleang\",\"middleName\":\"\",\"lastName\":\"SRENG\",\"suffix\":\"\"},{\"id\":626129859,\"identity\":\"2b5afd7d-1a5a-43d8-93fe-892a074176dd\",\"order_by\":29,\"name\":\"Vithurneat HANG\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Vithurneat\",\"middleName\":\"\",\"lastName\":\"HANG\",\"suffix\":\"\"},{\"id\":626129861,\"identity\":\"d39579a0-ed81-4e32-9f70-ad23f184a5c7\",\"order_by\":30,\"name\":\"Praveen RAHI\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Praveen\",\"middleName\":\"\",\"lastName\":\"RAHI\",\"suffix\":\"\"},{\"id\":626129864,\"identity\":\"547f7fc2-70a4-443c-aaa9-dc7de05db207\",\"order_by\":31,\"name\":\"Bertrand GUILLARD\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Bertrand\",\"middleName\":\"\",\"lastName\":\"GUILLARD\",\"suffix\":\"\"},{\"id\":626129865,\"identity\":\"f19a391f-c69e-4e0b-a639-1f75128cbe62\",\"order_by\":32,\"name\":\"Tum SOTHYRA\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ministry of Agriculture Forestry and Fisheries\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Tum\",\"middleName\":\"\",\"lastName\":\"SOTHYRA\",\"suffix\":\"\"},{\"id\":626129866,\"identity\":\"cd46eade-8747-4714-ac74-9cfad7ace6c9\",\"order_by\":33,\"name\":\"Chou MONIDARIN\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ministry of Environment\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Chou\",\"middleName\":\"\",\"lastName\":\"MONIDARIN\",\"suffix\":\"\"},{\"id\":626129867,\"identity\":\"9c6d6bd0-5ad1-42b5-836e-7c39740e29a4\",\"order_by\":34,\"name\":\"Rekol HUY\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Ministry of Health\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Rekol\",\"middleName\":\"\",\"lastName\":\"HUY\",\"suffix\":\"\"},{\"id\":626129868,\"identity\":\"97aec97e-9aec-4609-911a-e25de6fec861\",\"order_by\":35,\"name\":\"Navin SRENG\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Navin\",\"middleName\":\"\",\"lastName\":\"SRENG\",\"suffix\":\"\"},{\"id\":626129869,\"identity\":\"68a9bc69-dc97-4a2f-a1bb-5a7405d738c6\",\"order_by\":36,\"name\":\"Emilie CARLOT\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Emilie\",\"middleName\":\"\",\"lastName\":\"CARLOT\",\"suffix\":\"\"},{\"id\":626129870,\"identity\":\"27c1d66a-e36f-4bbb-83be-e08a056b0cde\",\"order_by\":37,\"name\":\"Najet HADHRI\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Najet\",\"middleName\":\"\",\"lastName\":\"HADHRI\",\"suffix\":\"\"},{\"id\":626129871,\"identity\":\"517c51e7-f98a-4431-b3ac-a62eb3439631\",\"order_by\":38,\"name\":\"Sowath LY\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Sowath\",\"middleName\":\"\",\"lastName\":\"LY\",\"suffix\":\"\"},{\"id\":626129872,\"identity\":\"ca56eeeb-487b-422c-8449-07518e14b5c6\",\"order_by\":39,\"name\":\"Simon CAUCHEMEZ\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institut Pasteur\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Simon\",\"middleName\":\"\",\"lastName\":\"CAUCHEMEZ\",\"suffix\":\"\"},{\"id\":626129873,\"identity\":\"44a14e4d-499e-4202-a885-4375aec70adf\",\"order_by\":40,\"name\":\"Claude FLAMAND\",\"email\":\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDAC5sMNIIqxHy7Cw0NAC1siRMtMEHWAJC0bDhCrhb+NsfHTjZo7sptvNz/+/KHicD4Dz9kDDB/31OLUInGMsVk659gz4213jplJHDhz2LKBty+Bccaz4zi1GMg3NkjnsB1O3HYjwYzhYNthA/vzPAbMPAeO4dbCxtj8O+ff4cTNM9I/fzj477ABAz9hLW3SuW2HEzdI5BhIHGwAauHtAWmpweeXNuvcvsPGM+6cKZM4cyzdgIHnjMHBGQcO4NTC38Z8+HbOt8Oy/bPbN3+oqLEGaskxfPDhQB1OLUj2IbGBVhwmUQsQEGPLKBgFo2AUjBAAAFlhXiDoPsWuAAAAAElFTkSuQmCC\",\"orcid\":\"\",\"institution\":\"Institut Pasteur du Cambodge\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Claude\",\"middleName\":\"\",\"lastName\":\"FLAMAND\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-10 20:38:17\",\"currentVersionCode\":1,\"declarations\":\"\",\"doi\":\"10.21203/rs.3.rs-9382926/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9382926/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":107707219,\"identity\":\"b9f580cb-b2b6-4cca-9708-8f5cd1accc5d\",\"added_by\":\"auto\",\"created_at\":\"2026-04-24 09:19:50\",\"extension\":\"jpeg\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":3878131,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eDistribution of 104 randomly selected villages for RACSMEI Project\\u003c/strong\\u003e\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig.1SelectedVillagesmap.jpeg\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/76acd7cea5aeace36e777745.jpeg\"},{\"id\":107610728,\"identity\":\"14be1f88-9dbb-43ae-83d7-a75b8b0efee6\",\"added_by\":\"auto\",\"created_at\":\"2026-04-23 08:27:04\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":108670,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eMargin of error in population estimates of seroprevalence according to sampling design.\\u003c/strong\\u003eThe margin of error was estimated for different combinations of sampled villages and households per village, assuming true seroprevalence values of 5%, 10%, 25% and 50%, \\u003cstrong\\u003eunder the assumption of an average of 3.6 individuals per included household.\\u003c/strong\\u003e The \\u003cstrong\\u003eblue cross\\u003c/strong\\u003ehighlights the expected precision at the \\u003cstrong\\u003enational level\\u003c/strong\\u003e for the selected RACSMEI sample size, whereas the \\u003cstrong\\u003ered cross\\u003c/strong\\u003e illustrates the corresponding precision at the \\u003cstrong\\u003eprovincial level\\u003c/strong\\u003e, supporting the choice of the study’s sampling strategy.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Fig2.Precisionestimates.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/359661419fd108e17fbedd18.png\"},{\"id\":107709089,\"identity\":\"82509173-736c-49bd-b84b-46f3a01c11aa\",\"added_by\":\"auto\",\"created_at\":\"2026-04-24 09:34:44\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":4303486,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/9e48985d-0abf-4df9-8d4f-7670e7209884.pdf\"},{\"id\":107610723,\"identity\":\"b96eabb8-ff97-4223-8322-90f9524ec1de\",\"added_by\":\"auto\",\"created_at\":\"2026-04-23 08:27:01\",\"extension\":\"pdf\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":118453,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 1. Extended pathogen panel investigated in RACSMEI\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis table presents the extended panel of pathogens investigated as secondary or exploratory outcomes in RACSMEI, including vaccine-preventable, elimination-targeted, emerging, and environmentally mediated pathogens. These analyses leverage the multiplex serological platform and molecular assays to inform long-term surveillance priorities and policy planning\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile1.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/8d115c0a161f581c049e3046.pdf\"},{\"id\":107610775,\"identity\":\"95368297-6e2b-4f38-978b-e7179ddc464f\",\"added_by\":\"auto\",\"created_at\":\"2026-04-23 08:27:15\",\"extension\":\"pdf\",\"order_by\":2,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":593387,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional File 2. RACSMEI Questionnaire\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis document presents the full RACSMEI household and individual questionnaire as provided in the Supplementary Information of the study protocol. Questions are organized by thematic modules. Skip patterns are indicated where applicable. The questionnaire was administered by trained interviewers using electronic data capture tools.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile2Questionnaire.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/061547efd19f7319f0dcef8e.pdf\"},{\"id\":107610730,\"identity\":\"507e72cf-ea90-4660-a7d1-10485865b77e\",\"added_by\":\"auto\",\"created_at\":\"2026-04-23 08:27:04\",\"extension\":\"pdf\",\"order_by\":3,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":544420,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional file 3. RACSMEI qualitative interview guides.\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis file contains the semi-structured interview and focus group discussion guides used in the RACSMEI study to explore community perceptions of infectious disease risks, prevention practices, care-seeking behaviours and the acceptability of public health interventions. The guides were developed to support qualitative data collection with community members, local leaders, and institutional stakeholders in selected study sites.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile3RACSMEISSI.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/accdc091d4b03a8e84af6241.pdf\"},{\"id\":107707177,\"identity\":\"4a7fba7f-c45c-435b-9a68-c92f32b84011\",\"added_by\":\"auto\",\"created_at\":\"2026-04-24 09:19:43\",\"extension\":\"pdf\",\"order_by\":4,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":8804120,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eAdditional file 4 – RACSMEI participant information\\u003c/strong\\u003e \\u003cstrong\\u003ebooklet\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis file contains the illustrated information booklet used during community engagement activities to explain the study objectives, procedures and participants’ rights.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"AdditionalFile4Booklet.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9382926/v1/dd018850113fce085104cd90.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"A Nationally Representative One Health Multi-Pathogen Serosurvey in Cambodia: Study Protocol for the RACSMEI Mixed-Methods Study\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eIn low- and middle-income countries (LMICs), controlling emerging and infectious diseases remains a major challenge, driven by limited access to diagnostics, fragmented surveillance systems and the lack of integrated population-level epidemiological data [1].\\u0026nbsp;These constraints hinder accurate assessment of disease burden, transmission dynamics and populations at risk, ultimately limiting the effectiveness of prevention and control policies. Existing research addressing these gaps is often pathogen-specific, resource-intensive or restricted to selected high-risk groups, which limits the ability to characterise infectious disease risks comprehensively at the national scale.\\u003c/p\\u003e\\n\\u003cp\\u003eIn this context, \\u003cstrong\\u003ePrecision Public Health\\u003c/strong\\u003e has emerged as a key approach to optimise resource allocation and guide targeted interventions using multi-level epidemiological data on disease burden, transmission drivers and population vulnerability\\u0026nbsp;[2–4]. To be effective, however, precision public health approaches must be grounded in \\u003cstrong\\u003eOne Health principles\\u0026nbsp;\\u003c/strong\\u003e[5–8]\\u003cstrong\\u003e,\\u003c/strong\\u003e explicitly integrating human, animal and environmental dimensions of infectious disease transmission.\\u0026nbsp;\\u003cstrong\\u003eSuch integration is particularly critical in settings where zoonotic, vector-borne and environmentally mediated pathogens circulate within shared ecological and socio-economic systems\\u003c/strong\\u003e\\u003cstrong\\u003e,\\u0026nbsp;\\u003c/strong\\u003edespite the operational challenges associated with implementing integrated surveillance frameworks\\u0026nbsp;[9,10].\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eCambodia represents a high-priority setting for implementing integrated One Health surveillance. The country’s strong reliance on agriculture and livestock production, which supports nearly\\u0026nbsp;half of Cambodian households, creates favorable conditions for zoonotic spillover at the human–animal–environment interface [11]. Vector-borne pathogens such as Japanese encephalitis virus (JEV) and dengue virus (DENV) circulate endemically\\u0026nbsp;[12–15], while avian influenza viruses (AIV) are regularly detected in domestic poultry, production systems and live-bird markets networks, with documented zoonotic transmission to humans and recurrent circulation of highly pathogenic A(H5N1) strains\\u0026nbsp;[16–20].\\u0026nbsp;These challenges are reflected in the national One Health Zoonotic Disease Prioritization process conducted in Cambodia, which identified several zoonotic pathogens of major public health concern requiring strengthened multisectoral surveillance and coordination [21]. Despite this recognized burden, nationally representative data integrating human, animal and environmental dimensions of pathogen circulation\\u0026nbsp;remain scarce.\\u003c/p\\u003e\\n\\u003cp\\u003eRecent advances\\u0026nbsp;in sero-epidemiological methods have transformed population-based surveys into powerful tools for monitoring infectious disease burden, identifying emerging threats and informing public health interventions such as vaccination strategies, biosafety measures and vector control\\u0026nbsp;[22–28]. In particular, multiplex serological platforms enable the simultaneous investigation of a wide spectrum of pathogens, including endemic, emerging, vaccine-preventable and elimination-targeted diseases within a single integrated survey [26,29–31].\\u0026nbsp;\\u003cstrong\\u003eThese technologies now allow the efficient generation of large-scale multi-pathogen exposure profiles in population-based samples\\u003c/strong\\u003e\\u003cstrong\\u003e,\\u003c/strong\\u003e providing critical insights\\u0026nbsp;into cumulative exposure, immunity gaps and heterogeneity in transmission risk across populations.\\u003c/p\\u003e\\n\\u003cp\\u003eTransmission of arboviruses (including dengue, chikungunya, Zika and JEV), zoonotic pathogens such as AIV, hantaviruses and leptospirosis, and environmentally mediated infections such as melioidosis is influenced by multiple interacting factors operating at individual (e.g. age, mobility, human behaviours), household (e.g. water storage, animal husbandry, vector control) and broader community contexts (e.g. urbanisation, vector density, biosafety infrastructure)\\u0026nbsp;[25,31–34].\\u0026nbsp;Quantifying the relative contribution of these drivers is essential to inform effective, context-adapted and equity-oriented control strategies\\u0026nbsp;[35,36].\\u003c/p\\u003e\\n\\u003cp\\u003eHowever,\\u0026nbsp;many serological studies rely on convenience samples or selected high-risk populations, often in accessible urban or rural settings\\u0026nbsp;[32,37–41].\\u0026nbsp;While informative, these designs do not provide a nationally representative picture of infection risk and immunity. In contrast, population-based sampling across randomly selected communities allows robust estimation of national and subnational seroprevalence, identification of spatial heterogeneity and transmission hotspots and a better understanding of infection risks across diverse socio-ecological contexts.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThe \\u003cstrong\\u003eRACSMEI (Risk Assessment of Community Spread of Multiple Endemic Infectious Diseases)\\u003c/strong\\u003e project was designed to address these gaps through a nationwide, integrated One Health serosurvey in Cambodia. By combining harmonised human, animal, environmental and social science data, RACSMEI aims to characterise transmission risks across a broad spectrum of pathogens and to identify key determinants of exposure at multiple scales. Through standardised methodologies, advanced laboratory platforms and close collaboration with national ministries, the project seeks to generate policy-relevant epidemiological evidence to support targeted and culturally appropriate interventions. Beyond its immediate objectives, RACSMEI provides a scalable methodological framework for integrated multi-pathogen surveillance in LMICs, contributing to strengthened national preparedness and offering a proof of concept for the operationalisation of large-scale One Health surveillance approaches.\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Objectives\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003ePrimary Objective\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp id=\\\"_Toc294256021\\\"\\u003eThe primary objective of RACSMEI is to characterise the burden, transmission dynamics and multi-level determinants of exposure to priority endemic and emerging infectious diseases in Cambodia using a nationally representative One Health approach.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eSecondary Objectives\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe secondary objectives are to:\\u003c/p\\u003e\\n\\u003cul\\u003e\\n \\u003cli\\u003eEstimate population-level exposure and infection patterns for selected zoonotic, vector-borne and environmentally mediated pathogens in human and animal populations.\\u003c/li\\u003e\\n \\u003cli\\u003eDescribe the spatial distribution and heterogeneity of pathogen circulation in order to identify high-risk areas and transmission hotspots and inform targeted public health interventions.\\u003c/li\\u003e\\n \\u003cli\\u003eIdentify transmission drivers at individual, household and community levels by integrating biomedical, behavioural, environmental and socio-demographic factors.\\u003c/li\\u003e\\n \\u003cli\\u003eReconstruct historical transmission dynamics using age-stratified serological profiles to infer past outbreaks and changes in transmission intensity.\\u003c/li\\u003e\\n \\u003cli\\u003eAssess the presence and diversity of selected pathogens in environmental matrices, including water, soil and other high-risk human-animal-environment interface sites.\\u003c/li\\u003e\\n \\u003cli\\u003eEstablish a national biobank of human, animal and environmental samples to support long-term surveillance, molecular characterisation and future research.\\u003c/li\\u003e\\n \\u003cli\\u003eExplore community perceptions of infectious disease risks, prevention practices, care-seeking behaviours and the acceptability of public health interventions.\\u003c/li\\u003e\\n \\u003cli\\u003eExtend surveillance to selected vaccine-preventable, emerging and elimination-targeted diseases to support integrated and adaptive One Health surveillance strategies.\\u003c/li\\u003e\\n\\u003c/ul\\u003e\"},{\"header\":\"Methods/design\",\"content\":\"\\u003ch2\\u003e\\u003cstrong\\u003eStudy design\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp id=\\\"_Toc213926947\\\"\\u003eRACSMEI is a nationally representative cross-sectional mixed-methods One Health study conducted across all 25 provinces of Cambodia. A stratified, multi-stage cluster sampling design was implemented to ensure representativeness across provinces and major ecological settings. Approximately 15,000 participants aged 2\\u0026ndash;75 years are enrolled from randomly selected households in 104 villages. Human participants are sampled in all selected households. Domestic animal and household-level environmental surface sampling are conducted according to a stratified protocol. Rodent trapping and vector collections are performed in a predefined subset of households per village following standardised ecological procedures. Environmental samples (water, soil and air) are additionally collected at predefined human\\u0026ndash;animal\\u0026ndash;environment interface sites within selected villages, including slaughter areas, wet markets, shared water access points and agricultural areas. Quantitative surveys are complemented by semi-structured interviews with key community and institutional stakeholders and focus group discussions to capture social and behavioural determinants of exposure, care-seeking behaviours and the acceptability of public health interventions.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStudy setting and population\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe study is conducted in 104 randomly selected villages covering urban, peri-urban and rural settings across Cambodia (Figure 1). The primary sampling units are randomly selected households, from which nationally representative estimates for the human population are derived using weighted analyses. Within these households, the study includes human participants and livestock-owning households selected according to a stratified protocol. Rodent trapping, vector collections and additional ecological investigations are conducted in a predefined subset of households and are used to support integrated transmission analyses. Qualitative data are collected from purposively selected community and institutional stakeholders within the selected villages. This integrated design enables nationally representative human estimates while incorporating ecological and stakeholder perspectives to better understand transmission dynamics across diverse socio-ecological contexts.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eSampling design and household selection\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eA multistage stratified cluster sampling design was used to obtain a nationally representative sample. In each of the 25 provinces of Cambodia, districts were randomly selected (four districts per province in 22 provinces, two in two smaller provinces and twelve in Phnom Penh). One village was randomly selected per district, yielding a total of 104 villages.\\u003c/p\\u003e\\n\\u003cp\\u003eWithin each village, 40 households were randomly selected from a complete household census conducted prior to the survey, resulting in a total sample of 4,160 households. All household members aged \\u003cstrong\\u003e2\\u0026ndash;75 years\\u003c/strong\\u003e were invited to participate. Individuals outside this age range or unable to provide informed consent (or assent for minors) were not eligible for biological sampling. The expected sample size was approximately \\u003cstrong\\u003e15,000 participants\\u003c/strong\\u003e, assuming a minimum average of 3.6 eligible individuals per household and a participation rate of 60%. Sample size calculations assumed a seroprevalence of 50%, a design effect of 2, a 95% confidence level and a margin of error of 1%. Precision estimates under alternative sampling scenarios are presented in Figure 2.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eLivestock and environment sampling\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eTo ensure representation of livestock species, households were classified during the census according to livestock ownership and assigned to mutually exclusive strata using a hierarchical approach prioritising less frequent species (small ruminants, pigs, cattle, poultry and dogs). Within each village, \\u003cstrong\\u003e20 livestock-owning households\\u003c/strong\\u003e were selected using stratified simple random sampling, while \\u003cstrong\\u003e20 households without animals\\u003c/strong\\u003e were independently selected using simple random sampling. Within livestock-owning households, \\u003cstrong\\u003edomestic animals were sampled among the species present in the household\\u003c/strong\\u003e. Sampling focused on apparently healthy animals and aimed to include a limited number of individuals per species to minimise disruption to household activities. T\\u003cstrong\\u003earget sample sizes per village were approximately 50\\u0026ndash;100 poultry, 5\\u0026ndash;15 pigs, 5\\u0026ndash;15 small ruminants, 5\\u0026ndash;15 cattle and 15\\u0026ndash;25 dogs\\u003c/strong\\u003e\\u003cstrong\\u003e,\\u0026nbsp;\\u003c/strong\\u003edepending on local livestock availability.\\u003c/p\\u003e\\n\\u003cp\\u003eEnvironmental sampling at household level consisted of five surface swabs collected in five households per village, taken inside and immediately outside participating households. In addition, nine environmental samples per village (three water, three soil and three air samples) were collected at predefined human\\u0026ndash;animal\\u0026ndash;environment interface sites, including slaughter areas, wet markets, shared water access points, waste disposal sites and agricultural areas. Rodent trapping and entomological collections were conducted in a subset of 10 households within each village according to standardised ecological protocols. These ecological samples are primarily intended to support integrated transmission analyses rather than to generate population-representative prevalence estimates.\\u003c/p\\u003e\\n\\u003ch3 id=\\\"_Toc213926949\\\"\\u003e\\u003cstrong\\u003eOutcome and pathogens detection\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eRACSMEI investigates exposure to a broad spectrum of infectious agents reflecting Cambodia\\u0026rsquo;s epidemiological priorities, using a structured outcome framework aligned with public health relevance, feasibility and policy utility. Pathogens were selected in close collaboration with national stakeholders based on endemicity, epidemic potential, zoonotic or environmental transmission, availability of preventive tools and relevance for integrated One Health surveillance. The analytical strategy distinguishes primary outcomes (priority pathogens), secondary outcomes (expanded pathogen panels) and exploratory outcomes (environmental and metagenomic detection) based on the analytical capacity of multiplex serological and molecular platforms.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003ePrimary outcomes\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003ePrimary outcomes focus on estimating population-level exposure to priority endemic and emerging pathogens, including arboviruses, zoonotic and emerging viruses, bacterial zoonoses and parasitic infections (Table 1). Seroprevalence of pathogen-specific antibodies constitutes the primary outcome measure in humans and selected animal populations. Molecular detection (RT-qPCR) is performed for pathogens with active circulation or amplification potential in relevant animal hosts and environmental samples. During household visits, venous blood samples are collected from participants (up to 10 mL in adults and children \\u0026ge;7 years; up to 5 mL in children \\u0026lt;7 years). Livestock and dogs undergo blood sampling, while poultry and pigs additionally undergo oral and rectal swabbing, and ectoparasites (ticks, fleas) are collected for speciation and metagenomic sequencing. All animal sampling is conducted by trained personnel from the Ministry of Agriculture, Forestry and Fisheries. Rodent trapping is conducted in and around 10 households per village over two consecutive nights, using a total of 50 live traps per village. Traps are placed inside and around selected households following standardised ecological protocols to capture small mammal reservoirs potentially involved in zoonotic pathogen transmission.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eEntomological investigations\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eIn addition, entomological surveys are conducted in each village in a subset of randomly selected households. Adult mosquitoes are collected outdoors for 24 hours in 10 households per village using BG-Sentinel traps and CDC light traps to assess vector density and species diversity [42]. These data will contribute to the generation of national-scale entomological risk maps and support integrated analyses of vector-borne disease transmission.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eSecondary outcomes: expanded serological profiling\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eSecondary outcomes include expanded serological profiling of vaccine-preventable, elimination-targeted, emerging, enteric and neglected tropical pathogens to inform longer-term surveillance and policy planning (Additional File 1). Exploratory environmental surveillance uses probe-enriched metagenomic sequencing of water, soil, air and surface samples to detect circulating or emerging pathogens and characterise microbial diversity at high-risk environmental interfaces.\\u003c/p\\u003e\\n\\u003ch3 id=\\\"_Toc213926951\\\"\\u003e\\u003cstrong\\u003eLaboratory procedures\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp id=\\\"_Toc213926952\\\"\\u003eHuman and animal blood samples are analyzed using a bead-based multiplex microsphere immunoassay developed by Institut Pasteur Paris, enabling simultaneous detection of antibodies against up to 100 antigens when using the Bioplex 200 multiplexing platform, and up to 500 antigens when using the Luminex INTELLIFLEX.\\u0026nbsp;Molecular diagnostics, including RT-qPCR and metagenomic sequencing, are used to detect active infections and characterise pathogen diversity in animal and environmental samples.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eData collection\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eQuantitative data are collected using standardised questionnaires covering socio-demographic characteristics, household and environmental conditions, clinical and vaccination history, and knowledge, attitudes and practices related to infectious diseases (Additional File 2). GPS coordinates are recorded to support geospatial analyses. Qualitative data are collected through semi-structured interviews (Additional File 3) and focus group discussions with community members, leaders and key stakeholders to explore risk perceptions, care-seeking pathways and the acceptability of public health interventions.\\u003c/p\\u003e\\n\\u003ch3 id=\\\"_Toc213926955\\\"\\u003e\\u003cstrong\\u003eData management\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;and analysis\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eData are collected using REDCap on encrypted tablets and stored on secure servers at the Institut Pasteur du Cambodge. Pseudonymisation is ensured through unique identifiers, and access is restricted to authorised personnel. Weighted prevalence estimates and 95% confidence intervals are calculated while accounting for the complex survey design. Multivariable regression models are used to identify individual-, household- and community-level determinants of exposure. Age-stratified serological data are analysed using mathematical transmission models to reconstruct historical transmission dynamics across demographic groups and geographic areas.\\u003c/p\\u003e\\n\\u003ch2 id=\\\"_Toc213926960\\\"\\u003e\\u003cstrong\\u003eTrial registration\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eThe study is registered on ClinicalTrials.gov (NCT07358910). The study was retrospectively registered on 14 January 2026.\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003eDissemination Plan\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eStudy findings will be shared with participating communities through dedicated public dissemination events and structured feedback sessions presenting and discussing key preliminary results. To minimise the risk of community stigmatisation, results will be reported and discussed at national and provincial levels rather than at the level of individual villages. Results will also be communicated to national authorities from the health, agriculture and environment sectors through the Interministerial One Health Coordination Committee (IMCC) to support evidence-based surveillance and control strategies.\\u003c/p\\u003e\\n\\u003cp\\u003eScientific dissemination will include publication in open-access, peer-reviewed journals to ensure broad accessibility and support the downstream use of project results, as well as presentations at national and international scientific conferences. A bilingual (Khmer and English) summary of key findings will be made publicly available online and disseminated through the project\\u0026rsquo;s annual newsletter to promote transparency and knowledge sharing.\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eThis study describes the design and early implementation of RACSMEI,\\u003cstrong\\u003e\\u0026nbsp;\\u003cstrong\\u003ewhich, to our knowledge, represents one of the first nationally representative One Health multi-pathogen serosurveys integrating human, animal and environmental data within a single population-based framework in a low- and middle-income country\\u003c/strong\\u003e.\\u003c/strong\\u003e By combining epidemiological, ecological and social science data collected at national scale, the study aims to generate comprehensive evidence on exposure patterns and transmission risks for multiple infectious diseases across diverse socio-ecological contexts. The study integrates nationally representative sampling, multiplex laboratory diagnostics and mixed-methods social science investigations, providing a unique opportunity to better characterise transmission risks at the human–animal–environment interface. Such integrated national surveys remain rare, particularly in low- and middle-income countries where surveillance systems are often fragmented across human, animal and environmental sectors.\\u0026nbsp;By combining multiplex serology, ecological investigations and social science approaches within a single nationally representative framework, RACSMEI also contributes to advancing methodological approaches for integrated multi-pathogen surveillance in resource-constrained settings.\\u003c/p\\u003e\\n\\u003cp\\u003eLarge-scale serological surveys have increasingly been used to complement routine surveillance systems by providing insights into population-level exposure to infectious diseases that are often underreported or poorly captured by passive surveillance [23–26,31,32,44,45]. National serosurveys conducted in several settings have demonstrated the value of multiplex serology for investigating exposure to multiple pathogens within a single survey framework. Such approaches have generated new epidemiological insights, including the identification of previously unrecognised hotspots of infection and the reconstruction of past circulation dynamics of several pathogens, thereby improving understanding of transmission patterns and informing targeted public health responses [24,27,31,32].\\u003c/p\\u003e\\n\\u003cp\\u003eRACSMEI builds upon these experiences while extending them to an integrated One Health surveillance framework. Previous analyses have shown that many studies claiming to adopt a One Health framework often remain limited to the human health component, with animal and environmental dimensions insufficiently integrated into study design and data collection. By explicitly incorporating animal sampling, environmental investigations and social science components alongside human serology, RACSMEI aims to provide a more comprehensive and system-level understanding of transmission dynamics.\\u003c/p\\u003e\\n\\u003cp\\u003eThe integration of animal and environmental components is particularly important for pathogens whose transmission dynamics cannot be fully understood through human data alone [7,46,47]. For several zoonotic infections, including arboviruses and other emerging pathogens, circulation in animal reservoirs or vectors may precede or exceed detectable transmission in human populations. For example, surveillance of animal hosts and vectors has contributed to early detection of circulation for pathogens such as West Nile virus or Crimean–Congo haemorrhagic fever in several settings, allowing authorities to strengthen preparedness before human cases were widely detected. Similar dynamics may occur for several pathogens included in RACSMEI, such as avian influenza viruses, Nipah virus or hantaviruses, where circulation in animal reservoirs may provide earlier or more detectable signals of transmission than human surveillance alone.\\u003c/p\\u003e\\n\\u003cp\\u003eCommunity engagement played an essential role in the feasibility and acceptability of the survey. The involvement of village leaders and community representatives during the preliminary household census helped build trust and facilitated accurate household enumeration. In parallel, semi-structured interviews with local and provincial stakeholders were conducted shortly before and during field activities. This approach helped clarify the objectives of the study, address potential concerns and strengthen coordination between survey teams, local authorities and community actors, thereby facilitating the smooth implementation of field operations.\\u003c/p\\u003e\\n\\u003cp\\u003eBeyond its immediate epidemiological objectives, RACSMEI also functioned as a capacity-building platform.\\u0026nbsp;Training activities in epidemiology, field coordination, and project management strengthened the ability of the research team to plan, implement and monitor complex multi-stakeholder activities. Participatory engagement and repeated interactions with communities and stakeholders also strengthened awareness of One Health principles and highlighted the value of integrated approaches to understanding transmission risks at the human–animal–environment interface. The integration of qualitative components further enhances the usability of findings by explicitly addressing social and behavioural determinants, such as risk perception, care-seeking pathways and acceptability of interventions, which are often critical for the effective implementation of public health policies.\\u003c/p\\u003e\\n\\u003cp\\u003eAt the national level, RACSMEI is designed to generate evidence that is directly relevant for public health decision-making in Cambodia. The stratified sampling strategy captures diverse socio-ecological contexts across urban, peri-urban and rural settings, enabling comparison of exposure patterns across regions and identification of both shared and context-specific determinants of transmission. Rather than producing isolated local estimates, the study aims to support the development of nationally relevant indicators that can inform integrated surveillance strategies and public health interventions. The establishment of a nationally representative biobank further enhances the long-term value of the study by enabling future analyses addressing emerging research and surveillance priorities without requiring additional large-scale field operations.\\u003c/p\\u003e\\n\\u003cp\\u003eBeyond Cambodia, RACSMEI provides a proof of concept for the implementation of large-scale One Health surveillance in low- and middle-income countries. While epidemiological patterns are context-specific, the integrated methodological framework, combining population-based sampling, multiplex serology, environmental investigation, stakeholder engagement and community participation, is potentially scalable and adaptable to other settings facing similar structural and epidemiological challenges. In this respect, RACSMEI contributes to the operationalisation of One Health beyond conceptual frameworks, offering practical lessons for national-level implementation. The study therefore provides an empirical foundation for strengthening integrated One Health surveillance systems and for informing data-driven public health strategies in Cambodia and other settings facing similar epidemiological and health system challenges.\\u003c/p\\u003e\"},{\"header\":\"Strengths and limitations\",\"content\":\"\\u003ch3\\u003e\\u003cstrong\\u003eStrengths\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eThis study represents the first nationwide One Health serosurvey conducted in Cambodia, integrating human, animal, environmental and social science data within a single population-based design. The nationally representative sampling strategy captures heterogeneity in socio-ecological contexts, livelihoods and geographic settings, enabling the generation of evidence that is directly relevant for national public health planning.\\u0026nbsp;A key strength of the study lies in its co-development with national authorities across the human, animal and environmental health sectors. The Ministry of Health, the Ministry of Agriculture, Forestry and Fisheries, and the Ministry of Environment were involved from the early stages of study conception and implementation through the national One Health coordination mechanisms. This multisectoral collaboration increases the likelihood that study findings will inform policy development and operational surveillance strategies. An important operational strength of the study lies in its nationwide coordination structure involving trained multidisciplinary field teams, established laboratory platforms and strong collaboration with national ministries, enabling the implementation of complex multi-sectoral surveys at national scale. By combining human serology with animal sampling, environmental investigations and qualitative research, RACSMEI aims to provide a more comprehensive assessment of transmission risks across the human–animal–environment interface.\\u0026nbsp;This integrated design responds to widely recognised challenges in the implementation of One Health approaches, where methodological fragmentation and limited cross-sector integration have often constrained the translation of interdisciplinary research into operational public health benefits, particularly in low- and middle-income countries\\u0026nbsp;[9,10,48–50]. The use of multiplex serological platforms allows the simultaneous investigation of more than 50 pathogens within a single survey, providing an efficient and scalable model for integrated infectious disease surveillance in low- and middle-income settings.\\u0026nbsp;This approach may serve as a transferable proof of concept for the design and implementation of nationally representative One Health surveillance systems in other resource-constrained settings.\\u003c/p\\u003e\\n\\u003ch3\\u003e\\u003cstrong\\u003eLimitations\\u003c/strong\\u003e\\u003c/h3\\u003e\\n\\u003cp\\u003eThe cross-sectional design limits the ability to infer causal relationships or directly assess temporal dynamics of infection. Serological cross-reactivity, particularly among flaviviruses, may complicate pathogen-specific attribution. To address this limitation, multiplex antibody signatures will be interpreted alongside confirmatory seroneutralisation assays and age-structured transmission modelling approaches. In addition, the household sampling frame was derived from administrative listings at district level and did not include foreign residents, who represent less than 1% of the national population. While this exclusion is unlikely to substantially affect national estimates, exposure patterns in this subgroup may not be fully represented in the study population. Finally, the laboratory analyses required for the large multiplex panels are resource-intensive and may delay the availability of results.\\u0026nbsp;\\u003c/p\\u003e\\u003ch2\\u003e\\u003cstrong\\u003eStudy status\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eCommunity engagement activities and preparatory workshops were conducted between September and October 2025. Enrollment, field data and sample collection for the nationwide population-based survey began on 18 December 2025 and are expected to be completed by 25 April 2026. Qualitative data collection, including focus group discussions and key informant interviews, is scheduled to take place between June 2026 and June 2027 as part of the mixed-methods study design. Laboratory analyses are being conducted in parallel from January to December 2026. Preliminary analyses and feedback to stakeholders are planned between November 2026 and June 2027. Final data analyses, modelling and dissemination activities will continue from 2026 through 2029.\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003ch2\\u003e\\u003cstrong\\u003eEthics approval and consent to participate\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eThe study protocol was reviewed and endorsed by the Cambodian Interministerial Coordination Committee for One Health (IMCC-OH) and presented to national and provincial authorities prior to field implementation.\\u0026nbsp;The study was conducted in accordance with the ethical principles of the \\u003cstrong\\u003eDeclaration of Helsinki\\u003c/strong\\u003e and national regulations governing research involving human participants. Field teams, including investigators and nurses, were trained to visit selected households, explain the study objectives, obtain informed consent and conduct interviews and biological sampling according to the study protocol. All members of selected households aged 2–75 years are invited to participate during an initial face-to-face visit. Written informed consent is obtained from all adult participants. For participants under 18 years of age, written consent is obtained from a parent or legal guardian, and assent is sought from minors when appropriate. Participation was voluntary, and respondents could withdraw at any time without consequence. To support community understanding of the study, a dedicated information package including an educational comic booklet (Additional File 4) and a short explanatory video\\u0026nbsp;(available at: https://www.youtube.com/watch?v=dWmCdn80jaU\\u0026amp;t=6s) was developed and presented to village leaders and participating households. These materials explain the objectives of the study, the voluntary nature of participation and participants’ rights regarding access to and correction of their personal data. Participant confidentiality is ensured through pseudonymisation procedures and secure data management systems. No identifiable personal information or precise household geolocation data will be reported in study outputs. Ethical approval was obtained from the Cambodian National Ethics Committee for Health Research (NECHR) (Approval No. 199, 2 May 2025; amendment No. 359, 22 July 2025) and from the Institutional Review Board of the Institut Pasteur in Paris (Ref. 2025-145, 8 October 2025). Animal sampling procedures follow internationally recognised animal welfare standards. Capture, handling and euthanasia procedures are performed by trained personnel and aim to minimise stress and suffering. Rodents are humanely euthanised using isoflurane inhalation, and non-target species are released immediately at the capture site. All procedures comply with national veterinary regulations and the \\u003cem\\u003eGuide for the Care and Use of Laboratory Animals\\u003c/em\\u003e of the National Institutes of Health [43]. Animal-related procedures were additionally reviewed by the UK National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) during the Wellcome Trust funding evaluation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eConsent for publication\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eNot applicable.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003eAvailability of data and materials\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eNo datasets were generated or analysed for the current manuscript as this article describes a study protocol. Data generated during the RACSMEI study will be made publicly available in accordance with institutional policies and applicable ethical and legal regulations.\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003eCompeting interests\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eThe authors declare no competing interests\\u003c/p\\u003e\\n\\u003ch2 id=\\\"_Toc213926969\\\"\\u003e\\u003cstrong\\u003eFunding\\u0026nbsp;\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp id=\\\"_Toc213926971\\\"\\u003eThis study is funded by the Wellcome Trust Discovery Award (Grant N°. 312353/Z/24/Z).\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003eAuthors’ contributions\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eCF conceived the study, secured funding, supervised the project, led the development of the study protocol and prepared the first draft of the manuscript.\\u003c/p\\u003e\\n\\u003cp\\u003eTeS, EK, SB, SoC and SiC contributed to funding acquisition, project supervision and protocol development.\\u003c/p\\u003e\\n\\u003cp\\u003eAA contributed to the development of the protocol, prepared the first draft of the manuscript and contributed to data visualisation.\\u003c/p\\u003e\\n\\u003cp\\u003eSL, SaS, MC, SoS, VibH, JAPA, SiS, KS, CN, SN, KN, PK and SI contributed to the development of the study protocol, standard operating procedures and investigation design.\\u003c/p\\u003e\\n\\u003cp\\u003eHG contributed to protocol development and the veterinary components of the study.\\u003c/p\\u003e\\n\\u003cp\\u003eVitH, VS, KN, CVP, EC and NH contributed to project management and operational coordination.\\u003c/p\\u003e\\n\\u003cp\\u003eSL and JAPA contributed to the supervision of field implementation and to the development of the study protocol.\\u003c/p\\u003e\\n\\u003cp\\u003eEK, MW, SP, PR, NS, BG and SpS contributed to the design and implementation of laboratory testing and diagnostic analyses.\\u003c/p\\u003e\\n\\u003cp\\u003eSK, TuS, CM and RH contributed as ministerial partners supporting study implementation and alignment with national public health strategies.\\u003c/p\\u003e\\n\\u003cp\\u003eJP contributed to the data analysis plan.\\u003c/p\\u003e\\n\\u003cp\\u003ePV contributed to data visualisation.\\u003c/p\\u003e\\n\\u003cp\\u003eMH, LV and MR contributed to the definition and development of community engagement activities.\\u003c/p\\u003e\\n\\u003cp\\u003eAll authors revised and approved the final manuscript.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003ch2\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/h2\\u003e\\n\\u003cp\\u003eThe authors would like to thank the Interministerial Coordination Committee for One Health (IMCC-OH) and the Cambodian Ministry of Health, the Ministry of Agriculture, Forestry and Fisheries, and the Ministry of Environment for their support and collaboration in the development and implementation of the RACSMEI study through the national One Health coordination mechanisms. We are grateful to the provincial and district health authorities, local administrative authorities and village leaders who facilitated the implementation of the study. We also thank the field investigators, nurses, laboratory technicians and data collection teams involved in the RACSMEI survey for their commitment and dedication. Finally, we sincerely thank the participating households and community members for their time and willingness to contribute to this study. We also thank Laure Garancher and the InkLink team for their contribution to the design and development of the illustrated community information booklet and video contents used to support community engagement and facilitate understanding of the RACSMEI study among participating households.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eJones KE, Patel NG, Levy MA, Storeygard A, Balk D, Gittleman JL, et al. Global trends in emerging infectious diseases. Nature. 2008 Feb 21;451(7181):990\\u0026ndash;3. doi:10.1038/nature06536 PubMed PMID: 18288193; PubMed Central PMCID: PMC5960580.\\u003c/li\\u003e\\n\\u003cli\\u003eDowell SF, Blazes D, Desmond-Hellmann S. Four steps to precision public health. Nature. 2016 Dec;540(7632):7632. doi:10.1038/540189a\\u003c/li\\u003e\\n\\u003cli\\u003eKhoury MJ. Precision Public Health: What Is It? [Internet]. [cited 2022 Feb 10]. Available from: https://blogs.cdc.gov/genomics/2018/05/15/precision-public-health-2/\\u003c/li\\u003e\\n\\u003cli\\u003eKee F, Taylor-Robinson D. Scientific challenges for precision public health. J Epidemiol Community Health. 2020 Apr;74(4):311\\u0026ndash;4. doi:10.1136/jech-2019-213311 PubMed PMID: 31974295; PubMed Central PMCID: PMC7079187.\\u003c/li\\u003e\\n\\u003cli\\u003eLerner H, Berg C. The concept of health in One Health and some practical implications for research and education: what is One Health? Infect Ecol Epidemiol. 2015;5:25300. doi:10.3402/iee.v5.25300 PubMed PMID: 25660757; PubMed Central PMCID: PMC4320999.\\u003c/li\\u003e\\n\\u003cli\\u003eHitziger M, Esposito R, Canali M, Aragrande M, H\\u0026auml;sler B, R\\u0026uuml;egg SR. Knowledge integration in One Health policy formulation, implementation and evaluation. Bull World Health Organ. 2018 Mar 1;96(3):211\\u0026ndash;8. doi:10.2471/BLT.17.202705 PubMed PMID: 29531420; PubMed Central PMCID: PMC5840631.\\u003c/li\\u003e\\n\\u003cli\\u003eWinkler AS, Brux CM, Carabin H, das Neves CG, H\\u0026auml;sler B, Zinsstag J, et al. The Lancet One Health Commission: harnessing our interconnectedness for equitable, sustainable, and healthy socioecological systems. Lancet. 2025 Jul 14;S0140-6736(25)00627-0. doi:10.1016/S0140-6736(25)00627-0 PubMed PMID: 40683291.\\u003c/li\\u003e\\n\\u003cli\\u003eMilazzo A, Liu J, Multani P, Steele S, Hoon E, Chaber AL. One Health implementation: A systematic scoping review using the Quadripartite One Health Joint Plan of Action. One Health. 2025 Jun;20:101008. doi:10.1016/j.onehlt.2025.101008 PubMed PMID: 40160937; PubMed Central PMCID: PMC11953970.\\u003c/li\\u003e\\n\\u003cli\\u003eAntoniolli A, Flamand C. Integrating One Health: Beyond buzzwords and silos. One Health. 2025;21:101174. doi:https://doi.org/10.1016/j.onehlt.2025.101174\\u003c/li\\u003e\\n\\u003cli\\u003eFernandes JB. Why One Health struggles: A critical analysis. One Health. 2026 Jun 1;22:101379. doi:10.1016/j.onehlt.2026.101379\\u003c/li\\u003e\\n\\u003cli\\u003eJones BA, Grace D, Kock R, Alonso S, Rushton J, Said MY, et al. Zoonosis emergence linked to agricultural intensification and environmental change. 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Lancet. 2023 Feb 18;401(10376):591\\u0026ndash;604. doi:10.1016/S0140-6736(22)01595-1 PubMed PMID: 36682371.\\u003c/li\\u003e\\n\\u003cli\\u003eFernandes J, Lemos ERS de. The multifaceted Q fever epidemiology: a call to implement One Health approach in Latin America. The Lancet Regional Health \\u0026ndash; Americas. 2023 Apr 1;20. doi:10.1016/j.lana.2023.100463\\u003c/li\\u003e\\n\\u003cli\\u003eAntoniolli A, Guis H, Picardeau M, Goarant C, Flamand C. One Health Field Approach Applied to Leptospirosis: A Systematic Review and Meta-Analysis Across Humans, Animals and the Environment. Open Forum Infect Dis. 2025 Jan;12(1):ofae757. doi:10.1093/ofid/ofae757 PubMed PMID: 39845019; PubMed Central PMCID: PMC11752865.\\u003c/li\\u003e\\n\\u003cli\\u003eAuplish A, Raj E, Booijink Y, de Balogh K, Peyre M, Taylor K, et al. Current evidence of the economic value of One Health initiatives: A systematic literature review. One Health. 2024 Jun;18:100755. doi:10.1016/j.onehlt.2024.100755 PubMed PMID: 38770400; PubMed Central PMCID: PMC11103946.\\u003c/li\\u003e\\n\\u003cli\\u003eYopa DS, Massom DM, Kiki GM, Sophie RW, Fasine S, Thiam O, et al. Barriers and enablers to the implementation of one health strategies in developing countries: a systematic review. Front Public Health. 2023;11:1252428. doi:10.3389/fpubh.2023.1252428 PubMed PMID: 38074697; PubMed Central PMCID: PMC10701386.\\u003c/li\\u003e\\n\\u003c/ol\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Tables\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eTable\\u003c/strong\\u003e\\u003cstrong\\u003e\\u0026nbsp;1. Primary outcome pathogens investigated in RACSMEI by host and laboratory method\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003ctable border=\\\"1\\\" cellspacing=\\\"0\\\" cellpadding=\\\"0\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePathogen group\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePathogen\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHumans\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePoultry\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003ePigs\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eDogs\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eLivestock (cattle, small ruminants)\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eRodents\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eEnvironment\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eArboviruses\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eDengue virus (DENV 1\\u0026ndash;4)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eChikungunya virus (CHIKV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eZika virus (ZIKV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eJapanese encephalitis virus (JEV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eWest Nile virus (WNV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eZoonotic \\u0026amp; emerging viruses\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eAvian influenza viruses (AIV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eNipah virus (NiV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eHantaviruses\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eSevere fever with thrombocytopenia syndrome virus (SFTSV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eTick-borne encephalitis virus (TBEV)\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eBacterial zoonoses\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eLeptospira spp.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eBrucella spp.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eCoxiella burnetii\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003eS, M\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003eBurkholderia pseudomallei\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eM\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 77px;\\\"\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eParasitic infections\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 102px;\\\"\\u003e\\n \\u003cp\\u003ePlasmodium spp.\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003eS\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 61px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 57px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 58px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 72px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026ndash;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd valign=\\\"top\\\" style=\\\"width: 62px;\\\"\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003eAbbreviations: S = Serology; M : Molecular testing (RT-qPCR) ; \\u0026ndash; = Not tested.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\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\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true},\"keywords\":\"One Health, Seroepidemiologic study, Population-based study, Multi-pathogen surveillance, Zoonotic diseases, Mixed-methods research, Cambodia\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9382926/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9382926/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground:\\u003c/strong\\u003e Cambodia faces a high and complex burden of zoonotic, vector-borne, vaccine-preventable and environmentally transmitted infections, driven by intensive human–animal–environment interactions. However, nationally representative data integrating human, animal and environmental dimensions of pathogen exposure remain limited. The RACSMEI (Risk Assessment of Community Spread of Multiple Endemic Infectious Diseases in a One Health Perspective) study aims to address this gap through a nationwide One Health serosurvey designed to generate policy-relevant epidemiological evidence for precision public health and integrated surveillance.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMethods/design :\\u003c/strong\\u003e RACSMEI is a nationwide, cross-sectional, mixed-methods study conducted across all 25 provinces of Cambodia. Using a stratified, multi-stage cluster sampling design, approximately 15,000 individuals aged 2–75 years will be enrolled from 4,160 households in 104 randomly selected villages. Human, animal (poultry, pigs, dogs, cattle, small ruminants, rodents) and environmental (water, soil, air, surface swabs) samples will be collected. Exposure to more than 50 endemic, emerging, vaccine-preventable and elimination-targeted pathogens will be assessed using multiplex serological assays, molecular diagnostics and metagenomics sequencing approaches. Quantitative surveys will be complemented by semi-structured interviews and focus group discussions to explore social, behavioural and health system determinants of infection risk and care-seeking behaviours. Analyses will account for the complex survey design and integrate epidemiological, environmental and social science data.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDiscussion\\u003c/strong\\u003e\\u003cbr\\u003e\\nBy combining nationally representative sampling with integrated human, animal, environmental and social science data, RACSMEI aims to generate comprehensive evidence on infectious disease exposure and transmission risks across diverse socio-ecological contexts in Cambodia. The study will provide policy-relevant insights to support One Health surveillance strategies and targeted public health interventions. The protocol was approved by the Cambodian National Ethics Committee for Health Research and the Institutional Review Board of Institut Pasteur Paris.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTrial registration\\u003c/strong\\u003e: ClinicalTrials.gov identifier: \\u003cstrong\\u003eNCT07358910. \\u003c/strong\\u003eRegistered \\u003cstrong\\u003e14 January 2026.\\u003c/strong\\u003e\\u003c/p\\u003e\",\"manuscriptTitle\":\"A Nationally Representative One Health Multi-Pathogen Serosurvey in Cambodia: Study Protocol for the RACSMEI Mixed-Methods Study\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-04-23 08:26:38\",\"doi\":\"10.21203/rs.3.rs-9382926/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0},{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-15T16:33:00+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"180587170332839588641944006782516036976\",\"date\":\"2026-05-12T15:28:18+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"209074439435019428648620094856122494174\",\"date\":\"2026-05-05T14:24:28+00:00\",\"index\":\"hide\",\"fulltext\":\"\"},{\"type\":\"reviewersInvited\",\"content\":\"\",\"date\":\"2026-04-15T20:29:55+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"editorAssigned\",\"content\":\"\",\"date\":\"2026-04-13T06:00:39+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"checksComplete\",\"content\":\"\",\"date\":\"2026-04-13T06:00:11+00:00\",\"index\":\"\",\"fulltext\":\"\"},{\"type\":\"submitted\",\"content\":\"BMC Infectious Diseases\",\"date\":\"2026-04-10T20:24:37+00:00\",\"index\":\"\",\"fulltext\":\"\"}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"bmc-infectious-diseases\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":false,\"externalIdentity\":\"infd\",\"sideBox\":\"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)\",\"snPcode\":\"\",\"submissionUrl\":\"https://www.editorialmanager.com/infd\",\"title\":\"BMC Infectious Diseases\",\"twitterHandle\":\"#bmcinfectdis\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"em\",\"reportingPortfolio\":\"BMC Series\",\"inReviewEnabled\":true,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"8ca8e71e-ae9c-4301-a910-e1fafdd0281d\",\"owner\":[],\"postedDate\":\"April 23rd, 2026\",\"published\":true,\"recentEditorialEvents\":[{\"type\":\"editorInvitedReview\",\"content\":\"\",\"date\":\"2026-05-15T16:33:00+00:00\",\"index\":66,\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"180587170332839588641944006782516036976\",\"date\":\"2026-05-12T15:28:18+00:00\",\"index\":65,\"fulltext\":\"\"},{\"type\":\"reviewerAgreed\",\"content\":\"209074439435019428648620094856122494174\",\"date\":\"2026-05-05T14:24:28+00:00\",\"index\":61,\"fulltext\":\"\"}],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"under-review\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2026-04-23T08:26:38+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-04-23 08:26:38\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9382926\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9382926\",\"identity\":\"rs-9382926\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}