One Health

Global efforts to prevent and mitigate the impacts of high pathogenicity avian influenza (HPAI) H5 on domestic animals, humans, and wildlife rely on timely and transparent information that is both accurate and interpretable across countries and sectors. International epidemiological and genomic databases, such as the World Animal Health Information System (WAHIS), the Global Animal Disease Information System (EMPRES-i+), the Global Initiative on Sharing All Influenza Data (GISAID), and the National Center for Technological Bioinformation Virus Portal (NCBI) provide essential information for surveillance, research, and decision-making. To evaluate how well these resources capture recent wildlife impacts, we consolidated information from these databases and complementary public sources including government reports, scientific literature, and news articles, on wildlife mortality associated with HPAI H5 in the Americas from November 2021 to July 2024. The consolidated dataset comprised 615,883 wild birds (287 spp.) and 63,409 wild mammals (39 spp.). In comparison, WAHIS represented 16,902 wild birds (261 spp.) and 6,323 wild mammals (31 spp.) while EMPRES-i+ captured a substantially smaller portion of affected host diversity for both wild birds (105 spp.) and wild mammals (27 spp.). Genomic databases (GISAID and NCBI) represented 7,027 whole genome equivalents of H5 viruses from wild birds (175 spp.) and 371 from wild mammals (26 spp.). These discrepancies indicate that international databases, while essential, provide an incomplete picture of HPAI impacts on wildlife, with significant geographic and taxonomic asymmetries attributable to differences in surveillance capacity, reporting practices, sequencing effort, and data-sharing pathways. Studies and management strategies relying on these resources without complementary validation may therefore mistake data gaps for real-world epidemiological patterns. Strengthening data reporting standards, improving validation procedures, and integrating international databases with national reports, scientific publications, and other sources will enhance the reliability of epidemiological analyses and support more effective One Health surveillance, risk assessment, and conservation action. Author summaryHigh pathogenicity avian influenza (HPAI) H5 viruses, often called bird flu viruses, can cause severe disease in birds and mammals, including humans. Because of their relevance for human health, livestock production, and wildlife conservation, international databases were established to share information on when and where these viruses are detected, which species are affected, and what virus strains are found. These databases are essential tools for governments, scientists, and conservation practitioners working to track outbreaks, understand how these viruses spread and evolve, and guide surveillance and response. In this study, we compiled and compared information on recent HPAI H5 events in wildlife in the Americas available in international databases with information from other public sources, including reports from governments, scientific literature, and news articles. We found important discrepancies in how countries and species affected were represented across sources. As a result, international databases might not fully capture the actual distribution or conservation impact of HPAI H5 on wildlife. Our findings also show why decision-makers and scientists should interpret database-derived patterns carefully. We provide recommendations to improve international databases to address these gaps and better inform One Health risk assessment and wildlife conservation actions.

Evidence suggests that increased local temperatures are associated with higher prevalence of antimicrobial resistance (AMR) in environmental bacteria. This study investigates the association between local climate and the proportion of antimicrobial-resistant Escherichia coli isolated from 2,766 farm environment samples from 53 English dairy farms. To do this, a non-linear Bayesian model that specifically accounts for decreased test sensitivity at low E. coli abundance was developed and used to estimate the proportion of isolates resistant to four antimicrobials (amoxicillin, cephalexin, streptomycin and tetracycline) from colony count data. Mean 7-day temperature and relative humidity at the farm location was modelled using a generalised additive model formulation. A higher proportion of E. coli isolates were resistant to cephalexin and streptomycin in samples collected from adult cow collecting yards, than heifer housing sheds. In contrast, a greater proportion of E. coli isolates from heifer housing sheds were resistant to amoxicillin and tetracycline. Evidence that local temperature is associated with an increase in the proportion of E. coli isolates resistant to streptomycin (20{degrees}C increase associated with a 5.0-fold increase; 95% CI: 1.03-33.0) and tetracycline (2.6-fold increase; 90% CI: 1.1-5.2) was observed. Additionally, relative humidity was associated with an increase in the proportion of isolates resistant to amoxicillin streptomycin and tetracycline. The influence of weather on the proportion of antimicrobial-resistant E. coli varied between samples collected from adult animals in collecting yards and heifers in housing sheds. These findings highlight the importance of considering weather conditions, sample characterises and seasonality when designing on-farm AMR surveillance systems. ImportanceUnderstanding how environmental conditions are associated with variability in AMR prevalence is critical for developing robust livestock AMR surveillance and anticipating the potential effects of climate change. The non-linear Bayesian modelling approach developed here adjusts for E. coli abundance associated variability in test sensitivity, enabling the influence of risk factors associated with the proportion of antimicrobial-resistant E. coli within samples to be more accurately estimated. Applying this approach to 2,766 faecal samples from 53 dairy farms in Southwest England indicated that the proportion of antimicrobial-resistant E. coli generally increased under warmer and wetter conditions. These findings suggest that environmental conditions can influence the prevalence of AMR E. coli in dairy farm environments and demonstrate the importance of accounting for weather related variability in livestock AMR surveillance. Adjusting for these associations in livestock AMR surveillance could improve the accuracy of modelling AMR trends and strengthen the assessment of climate-associated AMR risks.

Identifying and characterizing zoonotic pathogens in wildlife is essential for understanding disease risk to humans. In Sub-Saharan Africa, many people live with bats in their houses and are exposed to their pathogens, yet little is known about the bacterial pathogens in Afrotropical bat species. Globally, Bartonella spp. (bartonellae) and hemotropic Mycoplasma spp. (hemoplasmas) are common bacterial pathogens in bats, and some lineages are known to spill over and cause infections in humans. To evaluate this disease risk, we screened three common synanthropic bat species in Kenya, and their ectoparasites, for hemoplasmas and bartonellae and assessed their relatedness to known human pathogens. Of 767 bats across 21 sites, 17.9% of bats were Bartonella spp. positive and 19.3% were hemoplasma positive. Bat ectoparasites had similar Bartonella prevalence (13.5-25.0%) and, for most bat species, ectoparasite loads were not associated with increased likelihood of Bartonella infection. We found that Bartonella lineages displayed phylogenetic overlap between different bat species and ectoparasites, suggesting pathogen sharing between species, while hemoplasma lineages corresponded strictly to host taxonomy. Finally, we found that 16S rRNA sequences from one heart-nosed bat (Cardioderma cor) were 97.85% similar to a human-associated hemoplasma found previously in Schreibers bats (Miniopterus schreibersii) in Spain. We show that synanthropic bats host bacteria of potential public health concern, highlighting the need to investigate the emerging impacts of these pathogens on human health in Kenya and elsewhere in Sub-Saharan Africa.

Background Rabies is a zoonotic neglected public health problem associated with animal bites, especially domestic carnivores claiming 59,000 deaths annually predominantly in developing countries of Africa and Asia. There is a high risk of exposure among rural communities endemic with animal rabies where adoption of prevention strategies is minimal. This study determined the prevalence of suspected rabies exposure, associated factors, and delayed post-exposure care-seeking among animal-bite human cases in Busia district, Uganda. Methods: This was a cross-sectional study that involved 332 consecutively sampled animal bite human cases that occurred within the period 2023 to 2024. Data for the bite cases from records were collected using a data abstraction tool. In addition, interviewer-administered semi-structured questionnaires were used to collect data on sociodemographic, animal-related and environmental characteristics. Approximate bite locations were collected using Global Positioning System (GPS) coordinates via Kobo collect. Analysis was carried out in STATA 17 using mixed effects modified Poisson regression for factors associated with suspected rabies exposure. Results: The median age of the bite cases was 18 (IQR: 9-36) with the male gender predominantly affected. The prevalence of suspected rabies exposure was 53.6% (95% Confidence interval - CI: 46.8-60.3). Factors associated were urban versus (vs) rural residence (adjusted prevalence ratio-aPR: 1.04, 95%CI: 1.00-1.08), being bitten by a stray animal (aPR: 1.28, 95% CI: 1.22-1.35) and wild animal (aPR: 1.22, 95% CI: 1.14-1.30) vs domestic animal, vaccination status of the biting animal i.e. vaccinated vs unvaccinated (aPR: 0.76, 95% CI: 0.69-0.85), provoked vs unprovoked bites (aPR: 0.82, 95% CI: 0.79-0.86), and distance to nearest river ([&ge;]5km) vs <5km (aPR: 0.93, 95% CI: 0.87-0.99). The prevalence of delayed post-exposure seeking was 23.0% (95% CI: 16.5-31.1) among the suspected rabies exposures. Conclusion: The study reveals a high prevalence of suspected rabies exposure. Factors associated are multidimensional i.e. are of human, animal and environmental origin. The one health paradigm should be emphasized during routine surveillance of rabies-related cases. The study observed that 1 in 5 bite cases delayed to seek care post bite exposure. We recommend collaborations between sectors, routine vaccination and awareness campaigns, and monitoring of wild carnivore populations and environmental dynamics in rabies-related surveillance.

BackgroundBeef feedlots are increasing concerns that antibiotic use in beef cattle selects for antibiotic resistance, but limitations of primary studies and previous syntheses make it difficult to confirm a consistent effect. We conducted a rigorous systematic review and meta-analysis to summarise: 1) the effect during and after antibiotic administration; 2) its moderation by time since administration started/ended. MethodsEligible studies longitudinally compared beef cattle administered antibiotics to those that were not, measuring resistance determinants in faeces and/or environments. Information sources included Web of Science, CAB Abstracts, and Medline (last searches: 05/03/25). Risk of bias was assessed using RoB 2 and ROBINS-I. Meta-analysis was conducted where feasible, using individual participant data where necessary. ResultsThe 33 included studies were mostly small trials of North American feedlot cattle, all with high risks of bias. Meta-analysis of 11 studies of tylosin, ceftiofur, and chlortetracycline indicated positive effects on absolute abundance of resistance both during (SMDH = 0.4; 95% CI = 0.11 to 0.69, p = <0.01) and after (SMDH = 0.52; 95% CI = 0.33 to 0.71, p = <0.01) antibiotic administration. Log-transformed time was positively associated with effect size during (Slope = 0.63; 95% CI = 0.1 to 1.16, p = 0.02), and negatively associated after (Slope = -0.65; 95% CI = -1.24 to -0.06, p = 0.03) DiscussionAvailable evidence indicates time-dependent selection for antibiotic resistance in beef cattle, warranting further regulation to limit human health risks. Simultaneously, uncertainty about precise effect sizes warrants further research. FundingBBSRC Registrationhttps://doi.org/10.17605/OSF.IO/RXQHT

Background Foodborne diseases cause substantial global morbidity and mortality, yet remain largely unattended. To support countries to address this public health concern, the World Health Assembly Resolution 73.5 called for strengthening global food safety efforts and led to the development of the WHO Global Strategy for Food Safety 2022-2030, adopted at the 75th WHA (2022). To this end, the World Health Organization (WHO) reconvened the Foodborne Disease Burden Epidemiology Reference Group (FERG) to advise and support the work to generate updated global, regional, and national estimates of the foodborne disease burden for the reference period 2000-2021. Methods We developed an incidence-based framework expanding coverage to 42 foodborne hazards. Standardized systematic reviews, Global Health Estimates and Global Burden of Disease envelopes, and United Nations population data informed the evidence base. Missing epidemiological data were imputed using Bayesian hierarchical meta-regression models. Disease models mapped acute and chronic health outcomes, applying updated disability weights, life tables, and probabilistic Monte Carlo calculations to estimate incidence, mortality, Years Lived with Disability, Years of Life Lost and Disability-Adjusted Life Years for all 194 WHO Member States. Transparency and analysis reproducibility were ensured through availed open-source R packages and standardized workflows. Results The computational framework provides annual, country-level estimates with improved internal consistency and an expanded hazard scope compared with the WHO 2015 edition. Advances include refined modelling, enhanced uncertainty propagation, and broader inclusion of microbial, parasitic, and chemical hazards. Persistent data gaps---especially in high-burden regions---were filled through extensive imputation. Conclusions The computational framework for the WHO 2026 edition delivers the most comprehensive and transparent assessment of the global burden of foodborne diseases to date. Despite remaining limitations, it enables routine monitoring, supports evaluation of global food safety efforts, and highlights priorities for strengthening national data systems.

West Nile virus (WNV) and Usutu virus (USUV) are neurotropic Orthoflaviviruses sharing a similar enzootic transmission cycle primarily involving Culex pipiens mosquitoes as vectors and birds as amplifying hosts. First identified in Africa, both viruses established endemicity across Europe over the past two decades, most likely introduced and spread by migratory bird species along Mediterranean flyways. In avian species, infection outcomes range from subclinical to fatal neuroinvasive disease, varying by viral strain, host immunity, and species susceptibility. Southern France emerges as a key hotspot for the circulation of these viruses, supported by diverse avian habitats conducive to year-round viral maintenance. This study investigated the prevalence of WNV and USUV in more than 2500 sedentary and migratory wild birds from these regions during 2024-2025 using molecular surveillance. Samples were collected using mist net and bird boxes, across multiple passerine and non-passerine taxa, spanning wetlands, urban fringes, and agricultural zones. Our analyses revealed widespread viral circulation across diverse species, mainly among passerines such as great tits, house sparrows, and barn swallows with USUV detected at higher rates than WNV in both study years. Overall prevalence was markedly higher in 2024 than in 2025, potentially reflecting climatic or ecological drivers. Migratory individuals likely seed viral introductions during seasonal passages, whereas resident populations sustain local enzootic cycles, facilitating overwintering persistence. These results highlight the pivotal role of mixed avifauna in arbovirus dynamics within Mediterranean Europe and emphasize the necessity for integrated, year-round surveillance targeting high-risk species and habitats. Enhanced monitoring will aid in predicting spillover risks and informing vector control strategies to mitigate zoonotic threats.

Background: Dengue is a major public health problem in Brazil, and Minas Gerais is one of the states with the highest burden. In January 2019, the Brumadinho dam collapse released about 12 million cubic meters of iron ore tailings into the Paraopeba River basin, causing environmental disturbance that could plausibly affect vector habitats and dengue transmission. We evaluated the spatiotemporal dynamics of dengue in Minas Gerais from 2014 to 2023 and tested whether the disaster was associated with changes in affected municipalities. Methods: We performed an ecological spatiotemporal analysis using dengue notifications from SINAN for all municipalities in Minas Gerais (2014-2023). Municipalities were classified as Paraopeba basin, regional controls, or state controls. Temporal similarity was assessed using Pearson correlation-based hierarchical clustering and non-metric multidimensional scaling (NMDS). Sources of variation were examined with PERMANOVA and principal component analysis (PCA). A linear mixed-effects model with municipality as a random effect was used to test changes after 2019, with pre/post contrasts estimated from marginal means. Results: Dengue showed strong temporal synchrony across the state, with major epidemic peaks in 2015-2016, 2019, and 2023. Health region explained 31.5% of the variation in temporal incidence profiles (p = 0.001), whereas Paraopeba basin status explained no significant variation (p = 0.998). No temporal cluster was enriched for municipalities in the Paraopeba basin. PCA identified 2023, 2019, and 2016 as the main years driving variability. In the mixed model, year was significant (p < 0.001), but Paraopeba basin status and its interaction with time were not. Incidence increased significantly after 2019 in non-exposed municipalities (p < 0.001), but not in basin municipalities (p = 0.088). Conclusions: Dengue dynamics in Minas Gerais were driven mainly by regional and state-wide epidemic processes, with no significant independent effect of the Brumadinho dam collapse on notified dengue patterns.

Artisanally produced embutidos are a culturally significant fermented meat product widely consumed in Puerto Rico, yet their microbiological safety remains largely uncharacterized. This preliminary study evaluated the effect of artisanal fermentation on microbial diversity and assessed the presence of potentially pathogenic and antimicrobial-resistant Proteobacteriain locally produced embutidos. Raw pork (locally sourced) and beef (commercially imported) were obtained from retail supermarkets and processed at a small-scale production facility under standard artisanal conditions. Surface sampling using RODAC contact plates on TSA, MAC, and SDA media was performed before and after fermentation. Fermentation reduced overall microbial diversity in both meat types. Two Gram-negative isolates recovered from pre-fermentation samples were characterized using selective and differential media (MAC, MSA, EMB) and the IMViC biochemical test series. A Salmonella specie was presumptively identified from imported beef, and an Enterobacter species from locally sourced pork. Kirby-Bauer disk diffusion testing revealed that the Salmonella isolate was resistant to five antibiotics (ampicillin, methicillin, penicillin, streptomycin, tetracycline) and showed intermediate susceptibility to chloramphenicol and gentamicin. The Enterobacter isolate was resistant to five antibiotics (ampicillin, methicillin, penicillin, streptomycin, tetracycline) and showed intermediate susceptibility to chloramphenicol and gentamicin. Both isolates met MDR criteria, highlighting the need for enhanced microbiological oversight of artisanally produced embutidos in Puerto Rico.

Leishmaniasis, a climate-sensitive zoonotic neglected tropical disease, is transmitted by Phlebotomine sand flies and closely linked to socio-economic inequities. Understanding its spatio-temporal dynamics under environmental and social change is critical for effective control. A machine learning framework (XGBoost) was developed to map the global and European distribution of leishmaniasis, incorporating climatic indicators, land cover, elevation, and socio-economic indices (Human Development Index, AROPE). For Europe, five proven vector species (Phlebotomus perniciosus, P. ariasi, P. perfiliewi, P. neglectus, and P. tobbi) were modelled alongside cutaneous and visceral leishmaniasis. Across both analyses, land use features, particularly shrubland and forest cover, had the greatest explanatory power, reflecting their role in providing microclimates and vertebrate hosts for sand flies. Climatic factors, notably mean temperature of the coldest quarter and humidity of the warmest/driest quarters, were also influential, as these facilitate sand fly survival. Socio-economic predictors consistently improved model performance, confirming the role of poverty and inequity as determinants of disease distribution. Globally, leishmaniasis risk increased by ~17% since the 1990s, with Africa, Asia, and the Americas experiencing the greatest rise. In Europe, modest continental-scale increases (CL +1.28%; VL +2.47%) masked strong sub-national heterogeneity, including northward expansion of visceral leishmaniasis and increases in cutaneous leishmaniasis in southern and eastern regions. Sand fly projections indicated expansion of warm-adapted species (P. ariasi, P. perniciosus, P. neglectus) and contraction of species preferring cooler, more humid niches (P. perfiliewi, P. tobbi). These findings highlight climate change, land use, and inequity as interacting drivers of leishmaniasis, emphasising the need for enhanced surveillance, integrated vector management, and targeted support for vulnerable populations, including refugees and migrants.

Introduction: Socioeconomic deprivation is often associated with poorer health outcomes, but some studies suggest the opposite for Lyme disease. Here we test two hypotheses to explain this: differences in (i) local landcover of high risk habitats such as woodlands (landscape hypothesis) and (ii) outdoor recreation in such habitats (behaviour hypothesis). Methods: We analysed reported Lyme disease incidence data for 824 data zones in the city of Glasgow, UK, against deprivation rank (based on indicators relating to income, employment, health, education, crime and housing). We then tested how these relate to woodland cover and indices of urban greenspace usage (per capita and per ha of greenspace). Additionally, we measured Lyme disease hazard (density of infected ticks) in 32 greenspaces and tested relationships with deprivation, woodland and greenspace usage. Results: More advantaged data zones (data zones with low deprivation rank) had higher Lyme disease incidence. These areas had more woodland and woodland cover was positively correlated with both Lyme disease incidence and hazard. Deprivation did not correlate with greenspace usage, nor did greenspace usage correlate with Lyme disease incidence. Intensely used greenspaces had lower infected tick densities, consistent with a human disturbance effect on wildlife that carry ticks. Conclusions: Differences in woodland cover, but not outdoor recreation behaviour, can help explain our finding of higher Lyme disease incidence in more advantaged areas. However, to further test the behaviour hypothesis, we need more detailed data on outdoor recreation activity per capita both locally and in rural areas, as well data on mitigation behaviours.

Infections at the animal-human or wildlife-livestock interfaces have severe health and socio-economic consequences. Combined with empirical data, mathematical models can contribute to a better understanding of the reservoirs of these infections, which is a priority for mitigating their impact by using appropriate management interventions. Taking brucellosis in the Bargy massif (French Alps) as an example of a zoonosis at the wildlife-livestock interface, we developed and calibrated a multi-host model integrating data on direct and environment-mediated cross-species contacts from field observations. Estimates of the basic reproduction number (R0) allowed to identify the population of Alpine ibex (Capra ibex) and its environment as an essential host in the reservoir, driving both pathogen maintenance (within-species R0[&ge;]1: 1.66, 95% credible interval: 1.42-2.03) and its transmission to livestock (between-species R0>0: 0.035, 0.01-0.05). Our approach can be adapted to other multi-host pathogens, which will contribute to improve the understanding and management of these complex systems.

Respiratory Syncytial Virus (RSV) is responsible for a substantial health burden worldwide, particularly among children and older adults. In 2023, novel immunoprophylactic interventions for RSV were approved, underscoring the need to monitor circulating RSV lineages and detect mutations that could compromise intervention effectiveness. Here, we implemented wastewater-based genomic RSV surveillance by integrating digital PCR and amplicon-based sequencing within Switzerland's national wastewater monitoring program. We tracked RSV subtypes and individual mutations across the 2024-2025 peak season in six Swiss cities. RSV-A and RSV-B co-circulated nationwide, and both exhibited similar epidemiological dynamics estimated from their subtype-specific effective reproduction numbers. No previously reported F protein mutations relevant to prophylaxis efficacy were identified. Genetic diversity analysis of wastewater-derived sequences reflected patterns previously reported in clinical data, with higher diversity in RSV-A than RSV-B and greater variability in the G compared to the F gene. These findings demonstrate the potential of wastewater-based RSV surveillance for monitoring RSV dynamics and diversity and establish a national baseline for RSV evolution during the first season following vaccine implementation in Switzerland.

Nature-Based Solutions are increasingly promoted to address current urban challenges. While their potential effects on vector-borne disease risks have been documented, data on Aedes albopictus, a known arbovirus vector, remain limited in France. A previous study showed that urban vegetation moderately increases the abundance of adult mosquitoes of this species, but the monitoring period lasted only six months. Using ovitraps, we monitored Ae. albopictus egg density dynamics over multiple years (2022 to 2024) and analysed its environmental predictors in various urban environments. We included lagged meteorological variables, land cover metrics, and the cumulated egg densities recorded in the previous weeks as environmental predictors. Both parametric (GLMM) and non-parametric (Random Forest) models were fitted to weekly egg counts per trap. Our findings highlight that (i) egg density dynamics were related to how vegetation classes structured the landscape, (ii) growing degree days and cumulated number of eggs recorded in specific lagged time windows were the main contributors to egg density, and (iii) the non-parametric and parametric models performed similarly in terms of prediction accuracy.

First documented detection of Vibrio paracholerae in a Costa Rican foodborne outbreak. Genomic analysis confirmed species identity, revealing limitations of conventional PCR and MALDI methods. Findings underscore the need for genomic surveillance to accurately characterize emerging enteropathogens and support public health systems.

Puumala hantavirus (PUUV, Orthohantavirus puumalaense) is one of the primary causative agents of haemorrhagic fever with renal syndrome in Europe and is maintained in natural populations of the bank vole (Clethrionomys glareolus, also known as Myodes glareolus). Despite public health relevance, we are only starting to understand the molecular properties and interplay between environmental and ecological factors of the pathogen that explain PUUV infection in bank voles. Here, we investigated PUUV occurrence, genetic structure, and environmental associations in bank voles sampled from two boreal forest areas in northern Sweden, during a complete vole population cycle (2020-2023). In total, 519 voles were screened for PUUV RNA using targeted reverse transcription PCR (RT-PCR). PUUV small (S-) segment RNA was detected in both study areas and observed infection patterns varied with sex, body weight, season and year. Specifically, we detected significant interactions between season and area and between season and body weight, with males showing consistently higher infection probabilities. Infection probability was also higher during periods of increased vole abundance and peaked in 2022. Phylogenetic analysis of partial S segment sequences demonstrated that all detected sequences clustered within the North-Scandinavian PUUV lineage, with no apparent spatial differentiation, indicating limited genetic structuring between the sampling areas. Habitat analyses at multiple spatial scales did not identify significant associations between PUUV occurrence and land-use variables, suggesting that infection dynamics were driven primarily by host demographic and temporal factors rather than broad-scale habitat composition. These findings highlight the importance of host demographics and temporal dynamics in shaping PUUV epidemiology in its reservoir, and provide additional insight into the molecular ecology of PUUV in northern Europe.

During the 2026 Bundibugyo virus disease outbreak in the Democratic Republic of the Congo and Uganda, we projected potential airline-mediated importation risk using contemporary airline network and an externally calibrated Ebola importation hazard. Effective-distance analyses identified major international hub countries, including Belgium, France, South Africa, Kenya, and the United Arab Emirates, as higher-probability gateways within 30 days. These early projections provide a reproducible framework for real-time international situational awareness, while emphasizing that importation risk does not imply local transmission risk.

BackgroundThe global rise of multidrug-resistant (MDR) bacteria represents a critical public health threat, and Romania ranks amongst the most affected countries in Europe. As conventional therapy increasingly fails, bacteriophage therapy has re-emerged as a promising alternative to antibiotics. Urban rivers, contaminated with resistant bacterial strains, represent an underexplored and accessible reservoir for the isolation of lytic phages with therapeutic potential. MethodsTwo bacteriophages, 17M_Ec17_D and 22C_Ec22_D, were isolated from the Dambovita River, Bucharest, Romania, using MDR E. coli as host bacteria. Phage characterization included plaque morphology, transmission electron microscopy, and host range assessment by spot assay against 30 MDR E. coli isolates. Whole genome sequencing was performed on Illumina MiSeq and Oxford Nanopore Technologies MinION platforms, followed by bioinformatic analysis including taxonomic classification, lifestyle prediction, and functional annotation. ResultsBoth phages formed clear plaques and were classified as Kayfunavirus (17M_Ec17_D, Podoviridae-like) and Kagunavirus (22C_Ec22_D, Siphoviridae-like) with nucleotide similarities of 89.2% and 71.4% to their closest relatives, respectively, suggesting both are candidates for novel species. Host range analysis revealed lytic activity against 13% and 10% of tested MDR isolates, with complementary infection profiles. Genomic analysis confirmed a strictly lytic lifestyle for both phages, supported by the presence of holin and spanin genes and the absence of lysogenic modules, antibiotic resistance genes, and virulence factors. ConclusionsTo the best of our knowledge, this is the first study conducted in Romania to isolate and genomically characterize lytic bacteriophages targeting MDR E. coli. The characterized phages represent safe therapeutic candidates whose complementary host ranges suggest potential application as part of phage cocktail to broaden antimicrobial coverage against MDR infections.

Citrus yellow vein clearing virus (CYVCV) is the causal agent of an emerging disease representing a potentially high-impact threat for citrus production. Despite remaining outside Europe for decades, CYVCV has now expanded towards two important European citrus producers, Italy and, more recently, Spain. The presence of this virus in the EPPO region represents a current threat with unpredictable and potentially devastating consequences for European citriculture. Therefore, urgent protective measures need to be taken to prevent CYVCV spread and minimize its impact. Diagnostics is a key measure in the management of viral diseases, highlighting the need for harmonized methods suitable for reliable routine detection of the currently known CYVCV diversity. In this study, an inclusive, efficient and highly sensitive real-time RT-qPCR for the detection of CYVCV in plant material and transmission vectors has been developed and validated according to EPPO standards. Moreover, the validated method has been successfully adapted to both PCR digital platforms, that allow high-sensitive absolute quantitative detection, essential in the diagnostics at low viral concentrations; and PCR portable tools, that can be applied in a real diagnostic context for on-site detection. This versatility combines standard validated performance, absolute sensitive quantitation and real on-site detection. The study has also addressed sampling strategies to support reliable molecular diagnostic performance. Our results represent an improvement in the detection of CYVCV to be applied in epidemiological studies and different real diagnostic contexts for the containment of this important citrus pathogen.

Background: Wastewater and environmental surveillance (WES) expanded rapidly during the COVID-19 pandemic and is increasingly proposed for routine public health use across a broader range of pathogens. Yet empirical evidence on how decision-makers judge when WES is actionable, how it integrates with existing surveillance, and how its role varies across resource and epidemiological contexts remains limited. Methods: We conducted three structured tabletop exercises (TTXs) at regional Global Wastewater Surveillance Consortium (GLOWACON) meetings in Singapore, Ethiopia, and Panama between March 2024 and May 2025, engaging more than 1,100 participants from over 60 countries spanning public health, government, research, industry, and international organisations. Standardised scenarios and decision prompts, covering respiratory, contact-transmitted, and vector-borne pathogens across multiple outbreak phases, elicited how participants prioritised, implemented, and responded to WES. Data from structured observation notes, participant worksheets, and post-exercise surveys were systematically analysed using a thematic qualitative approach to identify cross-cutting decision patterns and context-specific considerations across regions. This working paper has not been peer reviewed. Findings: Four cross-cutting decision patterns emerged. First, WES was most actionable when it addressed defined surveillance gaps, particularly during early outbreak phases when clinical testing was limited or delayed. Second, decisions to initiate, scale, or de-escalate WES depended on disease severity, the availability of actionable interventions, and the completeness of existing surveillance, not on pathogen type. Third, participants consistently treated WES as complementary to, not a substitute for, clinical and epidemiological surveillance, with its role evolving over the course of an outbreak. Fourth, implementation considerations, including sewer infrastructure, resource constraints, tourism, and mass gatherings varied substantially by setting, while governance, data-sharing, and trust concerns recurred across all three regions. Interpretation: The value of WES is determined less by pathogen-specific characteristics than by how it is embedded within decision-making frameworks in public health systems. These findings provide empirical evidence on how WES is operationalised across diverse global contexts and underscore an urgent need for clearer governance, integration, and prioritisation frameworks without which WES risks remaining an underutilised or inconsistently applied tool despite its demonstrated potential to strengthen pandemic preparedness and response. Funding: This working paper was independently initiated and conducted within the Center on AI, Security, and Technology using income from operations and gifts and grants from philanthropic supporters. A complete list of donors and funders is available at www.rand.org/CAST. RAND clients, donors, and grantors have no influence over research findings or recommendations.