One Health

Introduction Nontyphoidal Salmonella enterica (NTS) is a major zoonotic enteric pathogen. Animal contact-related NTS outbreaks have increased in the United States of America (U.S.) over the last decade. Geospatial analysis can identify locations with elevated risk of NTS outbreaks where public health authorities can focus their NTS prevention and intervention efforts. Methods We analyzed NTS outbreak data reported from individual states to the Centers for Disease Control via the National Outbreak Reporting System between 2009 and 2022 across the continental contiguous U.S. A geospatial analytical framework that included disease mapping, spatial interpolation, and global and local clustering methods was applied to identify regions with high NTS outbreak rates. Results A total of 104 NTS single-state outbreaks were reported to the National Outbreak Reporting System (NORS) during the study period. The mean annual incidence rate was 0.02 NTS outbreaks per million person-years. The primary animal contact categories associated with these outbreaks were mammals (cattle, pigs, sheep, and horses), birds (backyard chickens, ducklings, and turkeys), and reptiles (turtles and lizards). Exposure settings included farms, fairgrounds, agricultural feed stores, veterinary clinics, dairy/agricultural settings, and residential settings. The local cluster detection methods consistently identified areas with significantly high NTS animal contact-related outbreak rates in the Mountain West, Midwest, and Northeast of the US. Conclusion NTS animal contact-related single-state outbreaks revealed distinct spatial clustering across the United States, with potentially higher risks in the Mountain West, Midwest, and Northeast. Diversity of animal-contact sources and exposure settings depicted complex transmission dynamics of NTS. Focused prevention and control programs in these areas are needed to mitigate the burden of NTS outbreaks.

BackgroundNontyphoidal Salmonella enterica (NTS) is a major public-health threat in the United States of America (U.S.). Evaluating associations between serovars, exposure sources, and settings in multistate outbreaks can reveal the drivers of NTS transmission and guide prioritization of targeted prevention and control strategies. MethodsWe analyzed multistate animal-contact NTS outbreaks reported to the CDC National Outbreak Reporting System during 2009-2022. We calculated incidence rates per 10 million population-years (MPY) and assessed temporal trends using Joinpoint regression. We constructed interstate co-occurrence networks linking serovars, exposure sources, settings, and states, and applied a random forest classifier to identify variables most useful for distinguishing outbreak profiles. ResultsWe identified 177 multistate outbreaks (0.06 per 10 MPY) involving 40 serovars. Incidence significantly declined from 2009 to 2013 and remained stable thereafter. Random forest rankings identified birds and reptiles as the most influential exposure sources and agricultural feed stores and residential homes as the most influential exposure settings in distinguishing outbreak profiles. Co-occurrence network analysis revealed two major communities. The first included outbreaks involving serovars Enteritidis and Infantis, bird exposure source, and agricultural feed stores or farms as exposure settings, with hubs across the Midwest, Northeast, and Southern regions. The second community involved outbreaks linked with reptiles and mammals as exposure sources, residential homes and farms as exposure settings, and serovars Hadar, Typhimurium, and Braenderup, which were concentrated in the Western and Southern regions. ConclusionsMultistate animal-contact NTS outbreaks clustered into distinct serovar-exposure, source, setting, and region patterns, suggesting different NTS outbreak transmission pathways. The persistence of NTS serovars across states, diverse animal-contact sources, and exposure settings underscores the ongoing zoonotic transmission risk at the human-animal and environmental interfaces. A region-specific One Health approach to prevent and control NTS outbreaks is suggested to reduce the health burden.

Dromedary camels are the main reservoir for Middle East respiratory syndrome coronavirus (MERS-CoV), a re-emerging infectious disease with pandemic potential. Somalia harbours approximately 32% of dromedary camels globally. We investigated current and past MERS-CoV infections among occupationally-exposed workers in slaughterhouses, dairy farms, livestock markets and a quarantine station. Sera and nasopharyngeal/oropharyngeal swabs from 770 workers were analysed for MERS-CoV antibodies by Enzyme-Linked Immunosorbent Assay (ELISA) and virus neutralization and for viral RNA by Real Star(R) MERS-CoV Reverse Transcription Polymerase Chain Reaction (RT-PCR). One farm worker with no travel history in the Qardo district, Karkar region, Puntland was sero-positive by ELISA and virus neutralization, providing the first-ever evidence of zoonotic spillover of MERS-CoV to humans in Somalia. This finding highlights the need to strengthen MERS-CoV surveillance across Somalia, along with an urgent need to strengthen national laboratory capacity and integrate MERS into diagnostic algorithms to generate accurate and reliable infection data and studies to understand the socio-cultural and potential risk factors for MERS-CoV.

BackgroundLivestock production systems in peri-urban areas are associated with high levels of interaction between humans, animals, and the environment, which may contribute to the dissemination of antimicrobial resistant bacteria. However, genomic characterization of resistant bacteria in the interconnected systems of humans, animals, and the environment in low- and middle-income countries like Cameroon is very limited. MethodsThis study was undertaken to investigate the ESBL-producing E. coli and K. pneumoniae in the peri-urban pig production systems in Yaounde, Cameroon, through the application of the One Health genomic approach. A total of 338 samples were collected from humans, pigs, and the environment. Enterobacterales were isolated using standard microbiological procedures, followed by antimicrobial susceptibility testing of the isolated bacteria using the Kirby-Bauer disk diffusion method based on the EUCAST breakpoints. Ten multidrug-resistant Enterobacterales with similar resistance profiles were sequenced to identify their sequence types, resistance determinants, plasmid replicons, and virulence determinants. ResultsEnterobacterales were found in 187 samples, comprising 38 human, 98 pig, and 51 environmental samples. E. coli (166 isolates) was the most prevalent species, followed by K. pneumoniae (100 isolates). Whole-genome sequencing revealed eight E. coli and two K. quasipneumoniae isolates from human, pig, wastewater, and farm environmental samples. The E. coli isolates represented seven sequence types, including the globally successful ST410 lineage. Notably, E. coli ST3580 was found in human and environmental samples from the Afanoyoa farm in different sampling months, while K. quasipneumoniae ST1535 was found in human and pig samples from the Etoudi farm in different months. All genomes encoded ESBL genes, with blaCTX-M-15 being the most prevalent, accompanied by other resistance genes to various antibiotic classes and several plasmid incompatibility groups. ConclusionsThese results show the circulation of genetically diverse ESBL-producing E. coli and K. pneumoniae in human, animal, and environmental reservoirs in peri-urban pig farming systems and the potential for cross-reservoir persistence of particular lineages. Improved One Health antimicrobial resistance surveillance and stewardship are critical to address antimicrobial resistance in rapidly urbanizing environments.

Bacterial zoonoses constitute a substantial fraction of emerging infectious diseases. In this study, we investigated the presence of pathogenic bacterial genera--Rickettsia, Borrelia, Orientia, Leptospira, and Coxiella--in rodents from southern India. We detected low circulation of Rickettsia (7.26%), Borrelia (6.45%), and Leptospira (0.8%), whereas Orientia and Coxiella were not detected in the rodents sampled. Notably, we observed contrasting patterns of tissue association, with rickettsiae detected exclusively in pooled organ tissues and borreliae detected only in blood, suggesting the influence of pathogen biology in detection probabilities. Our phylogenetic analyses further revealed spotted fever group rickettsiae and relapsing fever group borreliae in both synanthropic and forest-associated rats, highlighting a potential transmission risk to people and livestock in the region. By revealing the circulation of zoonotic bacteria in new host species, this study underscores the need for systematic surveillance of wildlife to better characterize bacterial diversity and its public health implications.

BackgroundTropical low- and middle-income countries are highly vulnerable to zoonoses and vector-borne diseases, with risks amplified by climatic events, environmental change, and limited surveillance capacity. Cambodia is particularly exposed due to its ecological diversity, seasonal flooding, and rapidly changing land use. Globally, however, field based One Health approaches remain under-implemented, limiting practical evidence on how to address these complex threats. MethodsThis protocol describes a longitudinal One Health study conducted in three villages of Battambang province, Cambodia, designed to investigate the prevalence and transmission dynamics of zoonotic and potentially zoonotic pathogens at the human-animal-environment interface. The study examines how vector density, diversity, and pathogen circulation are influenced by hydrological variation and seasonality, and assesses the socio-demographic, behavioral, and environmental factors shaping transmission. Integrated data will be collected through serological and molecular analyses in humans and animals, environmental sampling, and entomological surveillance, enabling cross-compartmental and spatiotemporal analyses. Expected ResultsThe study will generate integrated, cross-sectoral data to characterize pathogen exposure patterns, identify high-risk populations and practices, and inform targeted public health, veterinary, and environmental interventions. ConclusionsBy sharing this protocol, the work addresses a global methodological gap in operationalizing One Health in the field and supports the development of integrated surveillance strategies in climate-sensitive, resource-limited settings.

Mycoplasmopsis [Mycoplasma] agassizii is one of the principal pathogens associated with upper respiratory tract disease (URTD) in tortoises, yet its epidemiology in European wild chelonian populations remains poorly understood. The pathogen has been linked to population declines in some wild tortoise populations and is frequently detected in captive tortoises, where infections may persist subclinically and prolonged contact can facilitate transmission. In this context, the pet trade and the release or escape of captive individuals represent potential pathways for pathogen exchange between captive and wild populations. We assessed the presence and prevalence of M. agassizii in wild Mediterranean tortoises in Spain and compared infection patterns with captive populations. A total of 259 tortoises were sampled between 2020 and 2025, including spur thighed tortoises (Testudo graeca; 127 wild; 63 captive) and Hermanns tortoises (Testudo hermanni; 46 wild; 23 captive). Detection of M. agassizii was performed using PCR. The pathogen was detected in both species, but prevalence patterns differed markedly between captivity status and species. High prevalence was consistently observed in captive individuals of both species. In contrast, wild populations showed species-specific patterns: T. graeca exhibited very low or absent prevalence across wild populations, whereas T. hermanni showed comparatively higher prevalence in the wild. These results provide the first baseline assessment of M. agassizii occurrence in Mediterranean tortoises in Spain and highlight the importance of incorporating pathogen surveillance into conservation and management strategies for European chelonian populations.

Zoos may serve as sentinel sites for zoonotic vector-borne diseases. West Nile virus (WNV) and Usutu virus (USUV) are closely related orthoflaviviruses transmitted between Culex mosquitoes and a bird reservoir. Both viruses can also infect mammals, including humans, where they may cause symptoms and, more rarely, hospitalization and death. However, serological cross-reactivity between WNV and USUV complicates their differential diagnosis. Here, we aimed to reconstruct the dynamics of emergence of WNV in a zoo located in a newly affected area in Europe, using ELISA and Virus Neutralization Test (VNT) serological analysis of 1707 animal sera collected between 2015 and 2024. Combining this data in a model accounting for cross-reactivity with USUV, we estimated yearly forces of infection (FOI) by both viruses, and thus found that WNV likely circulated in the area one year prior to the first cases reported to the passive surveillance system. Our results also showed that, in the zoo, mammals and reptiles had a lower risk of infection than birds (relative risk of 0.14 [0.05; 0.28]), and that the exposure of birds to water (aquatic lifestyle or proximity to stagnant water) affected the risk. Finally, we estimated diagnosis parameters, including the sensitivity of the VNT (80.4% [76.5%; 84.3%]), the expected VNT titer value, and the level of serological cross-reactivity between viruses during the VNT. To conclude, our modelling framework allowed to disentangle the co-circulation of two closely related viruses, a crucial point in ensuring the reliable sentinel surveillance of these vector-borne zoonotic pathogens.

Human leptospirosis is a disease of public health importance in Thailand, but the animal species involved in the transmission cycle have not been fully uncovered. This study investigated Leptospira infection in dogs and terrestrial micromammals in rural Nan Province, Thailand, and the pathogen diversity. Sera from 95 seemingly healthy dogs and kidney samples from 399 micromammals were analyzed using real-time PCR for Leptospira detection, followed by conventional PCR and sequencing of infecting Leptospira. We investigated environmental factors associated with Leptospira infection in micromammals, using data collected during trapping. Real-time PCR revealed ongoing infection in 8.4% (8/95) of dogs and 10.0% (40/399) of terrestrial micromammals, with 12 infected species including Bandicota indica, Berylmys berdmorei, Berylmys bowersi, Mus cervicolor, Mus cookii, and Hylomys suillus. In this qPCR-positive micromammals, three pathogenic Leptospira species were identified: L. interrogans, L. weilii, and L. borgpetersenii. This represents the first confirmed detection of L. weilii in rodents in Thailand. Infected micromammals were found in agricultural and forest habitats but not in human settlements. Our study demonstrates potential complex leptospirosis epidemiology in rural Thailand, with multiple species serving as pathogenic Leptospira reservoirs across diverse habitats, and some shared pathogen diversity with human leptospirosis cases in Thailand. Free-roaming dogs may serve as bridge hosts, transmitting zoonotic Leptospira from micromammals to humans by visiting both animal habitats and human settlements. These findings emphasize the need for integrated One Health surveillance approaches to control leptospirosis in rural communities.

ObjectiveThis study aimed to compare a novel surveillance methodology to detect Porcine Reproductive and Respiratory Syndrome virus against oral fluid methodology in swine herds. Materials and methodsTwo pilot studies were conducted using two separate, high-risk commercial nurseries in central Nebraska, comparing two different surveillance sampling approaches (DARO Systems vs. oral fluid (OF)) in the detection of Porcine Reproductive and Respiratory Virus (PRRSV). Each nursery contained eight rooms with an average site inventory of 12,500 pigs. Weekly testing conducted in three of the eight rooms using DARO Systems and OF methodology to identify PRRSV until there was a positive sample, then daily testing of all rooms was conducted. Reverse Transcription-Quantitative Polymerase Chain Reaction was used for identification of positive PRRSV. ResultsSurveillance testing using novel methodology DARO Systems identified PRRSV in nurseries on average 3.91 days earlier than OF. ImplicationsDARO Systems allows for a more robust whole-herd sampling technique to rapidly and accurately detect PRRSV 3.91 days earlier than gold standard approaches. Additionally, DARO Systems allows for an unbiased, whole-herd sampling approach. This method enables producers to implement earlier disease mitigation strategies.

Salmonella spp. represents a leading cause of foodborne disease globally. Wild aquatic birds inhabiting ecosystems impacted by human activities may serve as reservoirs and dispersers of Salmonella and antimicrobial resistance genes (ARGs), posing significant public health risks. This study evaluated the prevalence, serovars, resistance genes, and genomic relationships of Salmonella in fecal samples from wild aquatic birds across three high-Andean lakes in Ecuador. Of 134 samples collected from 10 species, five (3.73%) tested positive, all from Yahuarcocha Lake, isolated from Fulica ardesiaca and Phalacrocorax brasilianus. Two serovars were identified: Salmonella Infantis (ST32, n=4) and Salmonella Newport (ST45, n=1). Three S. Infantis isolates exhibited multidrug resistance (MDR), mediated by a pESI-like plasmid carrying resistance genes against beta-lactams, aminoglycosides, tetracyclines, sulfonamides, trimethoprim, fosfomycin, and chloramphenicol. SNP-based phylogenetic analysis revealed low genetic divergence ([≤]10 SNPs) between wildlife and poultry-associated isolates, indicating a shared transmission network. These findings support a likely spillover from poultry production systems into wild bird populations, and highlight the role of wild aquatic birds as ecological sentinels and potential disseminators of MDR Salmonella across interconnected human, animal, and environmental systems. These results underscore the need to incorporate human, animal, and environmental health factors within a One Health framework.

Wildlife surveillance is critical for tracking disease emergence, characterizing pathogen diversity, and assessing spillover risks. Blood-borne pathogens are of particular interest for such efforts due to their global distribution, broad host taxa, and zoonotic potential. Despite the need to monitor blood-borne pathogens, blood collection efforts are costly for both biologists and the wildlife being sampled (i.e., time-consuming and stressful), hindering our ability to expand and enhance surveillance efforts. There is thus a pressing need for reliable methods for detecting blood-borne pathogens that minimize sampling efforts and wildlife stress. Vascular tissues can contain enough blood to detect infections while minimizing sampling effort and stress on wildlife, but it is unclear how pathogen detection and characterization from these tissues compared to blood. To evaluate the reliability of using vascular tissues for detecting blood-borne pathogens in wildlife, we collected paired samples of blood and wing biopsies from individual common vampire bats (Desmodus rotundus) and molecularly screened them for bartonellae, hemotropic mycoplasmas (hemoplasmas), and trypanosomes. The probability of detection was consistently lower in wing tissues than in blood for all pathogens, possibly due to blood vessel avoidance when collecting the former. However, we detected infection in wing tissues of at least two individual bats for each blood-borne pathogen. Paired-positive individuals mostly showed high sequence concordance between tissues, indicating frequent detection of the same infections. Estimated sample sizes needed to detect a single infection and the reported prevalences were similar (i.e., n = 10-39). Due to the lower probability of infection in wing tissues compared to blood, we suggest that using these samples to estimate infection prevalence of blood-borne pathogens is not ideal. However, our results demonstrate that vascular tissues are viable for initial pathogen assessment and discovery to help target surveillance efforts in the future.

Porcine Reproductive and Respiratory Syndrome Virus 2 (PRRSV-2) represents a major threat to the global swine industry. The epidemiological dynamics of PRRSV-2 are characterized by the recurrent annual emergence of dozens of variants. Long-distance spread of PRRSV-2 is largely driven by animal shipments. Spatiotemporal dynamics of PRRSV-2 in the USA have been explored; however, how fast variants spread to new regions after their emergence remains unclear, and this information could improve preparedness. To address this, we analyzed 14,835 sequences, retrieved from the Morrison Swine Health Monitoring Project (MSHMP), representing 156 variants sampled from 2015 to 2024, covering the five major swine-producing regions in the USA: the Upper Midwest (UM), Lower Midwest (LM), Atlantic Seaboard (AS), Northeast (NE), and Great Plains (GP). Time to spread was assessed using the time-to-dispersal event analysis and waiting time analyses. Genetic diversity was measured using Hill numbers. The UM had the highest variant richness (n=123), followed by the LM (n=47), AS (n=35), NE (n=45), and GP (n=38). Of the 62 variants that initially emerged in the UM, 17 later spread to other regions. The UM also received the highest number of variant introductions (n=24), followed by LM (n=14), NE (n=14), AS (n=4), and GP (n=7), highlighting regional differences in connectivity and risk. Our results suggest faster dispersal corridors among interior regions (e.g., GP to UM and LM to UM, [~]1.2-2.0 years) and slower for coast to interior pathways (AS to interior, [~]2-3 years). These findings may help anticipate the risk of PRRSV-2 variant introduction and provide more accurate dispersal time estimates, which are useful for improving epidemiological models and disease preparedness.

BackgroundIn 2021, the Los Angeles County (LAC) Department of Public Health suspected a leptospirosis outbreak in LAC affecting over 200 client-owned dogs. ObjectiveTo characterize the outbreak and describe microbiologic findings, risk factors, diagnostic test performance, and outcomes in dogs diagnosed with leptospirosis at two specialty practices. MethodsLeptospira culture isolates from four cases were subjected to serotyping and whole genome sequencing (WGS); WGS was also performed on one enriched genome isolate. After the outbreak, data were gathered on 59 cases through record review and compared to the background hospital population (controls, n=15,536). ResultsAll isolates were Leptospira interrogans serovar Canicola, but each was distinct based on WGS. Cases clustered in space and in time. Cases evaluated during the outbreak peak had increased odds of exposure to indoor congregate facilities (ICFs). None of 47 dogs with known leptospirosis vaccination history were completely vaccinated. Leptospira real-time PCR on blood and urine and initial serologic testing using the microscopic agglutination test and point-of-care tests were positive in 15/56 (27%), 49/54 (91%) dogs, 22/29 (76%), and 27/35 (77%) dogs respectively. Fifty-four (92%) of 59 dogs survived to discharge; some remained azotemic. No associated human cases were identified. Conclusions and Clinical ImportanceL. interrogans serovar Canicola was associated with a leptospirosis outbreak in unvaccinated dogs from LAC, which had public health implications given widespread dog ownership rates. Data analysis suggested multiple infection sources, including ICFs. Urine PCR was the most sensitive diagnostic test. Such outbreaks might be prevented through more widespread vaccination.

IntroductionIncreasing occurrence of epidemics and pandemics and concurrent emergence of different pathogens calls for multi-sectoral, multi-pathogen preparedness actions. Data on various factors that drive emergence of diverse pathogens can inform evidence-based preparedness by identifying geographies at-risk. When leveraging evidence within a One Health approach, multiple pathogens can be addressed simultaneously, thereby strengthening countries pandemic preparedness efforts. MethodsFor seventeen priority pathogens (avian influenza viruses, zoonotic coronaviruses including COVID-19, hemorrhagic fever viruses including Ebola, Henipaviruses, and arboviruses including yellow fever and Zika), we identified global evidence on animal reservoirs, vectors, environmental suitability, and reported human cases. We discriminated geospatially recorded pathogen detections from a background sample and constructed maps using these datasets to generate an evidence-based assessment of emergence risk globally. ResultsSeventeen pathogen-specific assessments were combined into a global composite map. Sub-Saharan Africa and South Asia have evidence supporting emergence risk for the greatest number of pathogens (included areas at-risk of all pathogens) and scored highest when strength-of-evidence weightings were factored. The Americas had the lowest tally of considered pathogens. Environmental suitability analyses received the highest weights, reservoir ranges the lowest. DiscussionPreparedness and readiness must consider the range of global biological threats. Our methodology is capable of incorporating changing evidence on emergence potential for multiple pathogens to identify geographies at higher risk with different pathogen combinations. Our maps can contribute to existing decision-support structures, guiding shared interventions and strategic allocation of resources for spillover prevention and pandemic preparedness, thereby enhancing local response capacities applying a multidisciplinary approach. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSUsing PubMed, we searched for "[PATHOGEN] Preparedness Map" for each of seventeen priority pathogens to explore what resources might exist to be used to guide contemporary preparedness actions. The seventeen pathogens were: avian influenza viruses (AIV,all subtypes), chikungunya virus (CHIKV), Crimean-Congo hemorrhagic fever virus (CCHF), dengue virus (DENV), Ebola virus (EBV), Hendra virus, non-specific Henipaviruses, Lassa virus (LASV), Marburg virus (MARV), Middle East respiratory syndrome coronavirus (MERS-CoV), monkeypox virus (MPXV, all clades), Nipah virus, Yersinia pestis, Rift Valley fever virus (RVF), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), yellow fever virus (YFV), and Zika virus (ZIKV). We also searched for "Emergence Preparedness Map" to try and identify a singular resource that housed all these pathogens. Searching for specific pathogens identified resources that had deployed specific approaches or types of data in answering this question, but often did not collate multiple varied evidence streams. Similarly, the more detailed resources tended to be more geographically restricted in scope. When searching for emergence resources more broadly, we identified some clusters of epidemiologically related pathogens being synthesized (for instance thinking about integrated management of vector-borne diseases), but none that spanned the full repertoire of pathogens listed. Others attempted to characterize the phenomena of emergence more broadly, but as a result lost the ability to further capitalize on pathogen-specific activities since pathogens were not a building block within a broader methodology. Added value of this studyIn evaluating the emergence potential for seventeen priority pathogens, we have collated the widest range of pathogens into a common map for synthesis. In doing so, we provide a support mechanism for actionable next steps for epidemic and pandemic preparedness at scale that leverage current knowledge. Contrasting to prior assessments, we leverage different types of data and provide a mechanism to differentially weight their inclusion. We outline a mechanism by which even for pathogens where comprehensive or detailed data is not present, the information currently available can be acknowledged and integrated, to provide immediate support for decision-making, while future enhancements are integrated when available and iterated upon. We also demonstrate how this modular methodology allows customized aggregations of pathogens where scopes of work necessitate - for instance, collating all pathogens with similar vectors where vector control actions can be undertaken. We show with examples of Marburg virus disease in Equatorial Guinea, how the maps demonstrated the prior evidence-base related to emergence of this disease in that geography and use that example to outline how these maps can indicate geographies of concern. Implications of all the available evidenceEpidemic and pandemic preparedness is multi-faceted and multi-sectoral; some actions require pathogen specific insights, while other actions will work to counter a group of pathogens simultaneously. With this methodology, we demonstrate that it is possible to integrate data from diverse formats across different transmission routes and pathogens ecological dynamics globally to produce a set of resources to support local, regional, and global evidence-based decision making. Different groupings can be called upon to support different actions - pathogen specific maps where pathogen-specific vaccination schedules need to be undertaken; tracking the full pathogen-set that any given reservoir is implicated in; determining the differential diagnosis needs for a specific health facility and corresponding population it serves as a function of the implicated local pathogens or their potential future emergence; and supporting local health facilities in developing protocols, training, and necessary equipment to effectively detect and respond to possible local cases. Finally, these maps are designed to evolve alongside advancing infectious disease intelligence, allowing for continuous enhancement and resolution of data limitations across diverse surveillance systems and national contexts.

Background: Mobile laboratory diagnostic technologies for Nipah virus outbreak prevention, mitigation and response remain limited, despite the critical need for such capacities in remote, low-resource regions where most cases occur. We aim to address this gap by implementing a workflow that includes method development, laboratory validation, and field demonstration of a mobile Nipah virus complex diagnostic solution. Methods: We developed a flexible mobile laboratory workflow incorporating PCR capacity, a novel amplicon-based sequencing protocol, and a validated Nipah virus inactivation procedure. Following development and validation, we demonstrated the feasibility of this workflow through repeated field sampling of bat colonies in Nipah virus endemic regions of Bangladesh across multiple field campaigns. Findings: We demonstrated the feasibility of this system for early outbreak response and as a potential early warning tool prior to the emergence of human cases. We detected two urine samples from flying foxes that tested positive and performed full-scale on-site analysis, including qPCR diagnostics and NGS sequencing, within 24 hours. Interpretation: As highlighted in the present study, active surveillance enables outbreak prevention by identifying bat colonies that are actively shedding viruses in real time, even in rural settings. Also, this method can provide rapid, on-site sequence data to track and better understand the genomic diversity of Nipah virus in natural reservoirs during both outbreak and non-outbreak periods. In this study we aimed to establish the foundations of a standard procedure for safe and rapid field testing of Nipah virus in remote areas.

Ethiopia experiences devastating economic losses from an ongoing endemic burden of trans-boundary animal diseases (TADs). TADs are highly transmissible infectious diseases of animals, often able to spread rapidly with significant economic and public health consequences. Contagious bovine pleuropneumonia (CBPP), foot-and-mouth disease (FMD), and lumpy skin disease (LSD) are among the global priority TADs for cattle. In this study, we used responses from a survey about cattle disease delivered to livestock keepers across Ethiopia. We used generalized additive mixed models applying neighborhood cross-validation method which accounts for spatial dependence in the data to investigate the spatially variable relationships between bioclimatic variables and distribution of CBPP, FMD, and LSD in Ethiopia. We also developed model-based risk maps of these diseases using a geostatistical kriging method to guide knowledge-based decision making. The results show the risks of CBPP vary with altitude and relative humidity, risks of FMD with temperature and relative humidity, and of LSD with temperature and precipitation. The gaussian spatial smooth terms are all significant. The maps are produced using rigorous statistical analysis with very low prediction errors and can thus be considered reliable. Our results have implications for the impacts of climate change, and the vulnerability of communities in high-risk areas. The risk maps illustrate how such maps contribute to climate-informed disease early warning systems.

1.West Nile virus (WNV) and Usutu virus (USUV) are mosquito-borne pathogens maintained in bird-mosquito cycles and increasingly cause human and equine disease in temperate regions. As most infections are asymptomatic, surveillance based on clinical and veterinary reports provides delayed signals for vector control and equine vaccination strategies. We implemented, in 2024 and 2025, an operational environmental surveillance strategy combining molecular xenomonitoring of adult mosquito excreta with water sampling from wetlands and mosquito breeding sites, coupled to a standardized multiplex reverse transcription digital PCR workflow. Viral detection was performed using a multiplex digital PCR assay with characterized limits of blank, detection, and quantification, and low-level positives were confirmed by Sanger sequencing. This multi-matrix approach detected WNV RNA in southern France as early as 1 July 2024, 40 days before the first human case and 67 days before the first equine alert, and on 9 April 2025, a full 19 weeks ahead of the first human case that year. USUV RNA was similarly detected from 5 July 2024 and 22 April 2025, providing actionable early warnings to guide targeted vector control and preparedness. Across both years, WNV and USUV were detected 29 and 8 times among 396 samples in 2024, and 90 and 14 times among 815 samples in 2025, revealing previously unrecognized, cryptic virus circulation. These results demonstrate that integrating environmental surveillance provides a sensitive, proactive framework for the early detection of emerging Culex-borne arboviruses, offering precious lead time for public one-health strategies.

Background. Climate change is intensifying extreme weather events (EWEs) with potentially profound consequences for zoonotic disease dynamics, yet the mechanisms linking EWEs to highly pathogenic avian influenza (HPAI) H5N1 outbreaks remain poorly characterized. The ongoing H5N1 panzootic, responsible for infection in over 500 avian and mammalian species, as well as nearly 1000 human cases and 477 deaths worldwide, provides a critical opportunity to evaluate how climate conditions shape spillover risk at landscape scales. Methods. We compiled a county-month dataset of confirmed H5N1 detections across the contiguous United States from 2022 to 2024 and integrated it with satellite-derived climate metrics, storm event data, and wild bird activity data. We trained and validated a gradient boosting machine classifier to predict outbreak risk and characterize predictor relationships. Results. Our model achieved strong discriminative performance (AUC-ROC = 0.856; AUC-PR = 0.237, representing a 7-fold improvement over chance) and high recall (0.726), supporting its utility as an early warning tool. Human population and temperature-related variables were the most influential predictors: cold temperature shocks and prolonged low temperatures were consistently associated with elevated outbreak risk, likely through enhanced environmental viral persistence, wild bird habitat compression, and allostatic stress-driven immunosuppression in reservoir hosts. Among storm variables, high wind coverage elevated risk, potentially via aerosol dispersal of contaminated particulates, while tornado activity showed an inverse relationship, consistent with documented avoidant behavior in migratory birds. Wild bird reservoir density showed a strong positive monotonic relationship with outbreak risk. Conclusions. Our analyses demonstrate that routinely available environmental and infection data can be used to predict HPAI outbreak risk at fine spatiotemporal scales. These findings demonstrate the divergent roles of short- versus long-term environmental exposures in HPAI spillover dynamics, as well as the potential for machine learning-based surveillance tools to inform targeted biosecurity interventions and early warning systems.

Cochliomyia hominivorax, New world Screwworm (NWS), has become a reemerging veterinary concern in the United States due to the recent northward expansion of fly detections as far as northern Mexico. Rapid, accurate and validated detection pipelines need to be developed in the case of an incursion into the United States. Confirmatory cases are evaluated by morphological identification with no paired test to verify identifications. With the frequency of submissions of non-ideal samples, particularly from fly traps, a molecular tool would be necessary for species identification. In this manuscript, we develop and assess a pipeline including three real-time PCR assays targeting the ribosomal RNA and five sets of Sanger primers targeting the mitochondrial genome that would be used as a paired tool with morphological identification. Two of the assessed real-time PCR assays are highly specific, sensitive and repeatable requiring <1 copy per reaction for detection. Four of the five Sanger primer sets were assessed, optimized and results evaluated for potential use in preliminary geographic analysis of specimens. This workflow will expedite screening of samples, provide a method to verify results using different tools and help understand genetic variations within the mitochondria for NWS outbreaks.