One Health

BackgroundAnimal bites represent a significant public health concern due to the risk of injuries and transmission of zoonotic diseases such as Rabies, particularly in low and lower- middle-income countries (LMICs). Understanding the epidemiological characteristics of animal bite incidents is essential for improving the prevention and control strategies. This study aimed to characterize the epidemiological patterns and characteristics of animal bite cases in Sylhet, Bangladesh. Methodology/Principal findingsWe conducted a retrospective analysis of 6,565 animal bite cases reported between January 1 and December 31, 2024, in Sylhet, Bangladesh. Data on demographic characteristics, type of biting animal, site of bite, and exposure category were collected and analyzed to determine associations using correlation analyses and chi-square tests. Among the victims, 3,917 (60%) were male and 2,648 (40%) were female and young adults aged 20-39 years comprised the largest group (39% of cases). The majority of cases (88.1%) originated from urban areas within Sylhet City Corporation. Cats were the leading cause of bites (56.6%), followed by dogs (35.0%) and monkeys (7.5%), suggesting a shift from the traditional dog-dominated pattern. The most frequently affected anatomical sites were the legs (50.3%) and hands (40.9%). Most exposures were classified as World Health Organization (WHO) Category II (98.2%). Bite incidents showed moderate seasonal variation, with peaks in spring and early autumn. A significant declining temporal trend was observed for monkey bites (R = -0.59, p = 0.044), whereas cat and dog bite patterns remained relatively stable throughout the year. Significant associations were identified between bite site and age group, as well as between biting animal and demographic characteristics (p < 0.05). Conclusion/SignificanceThese findings highlight the epidemiological patterns of animal bites in Sylhet and emphasize the need for strengthened public awareness, surveillance, and preventive strategies to reduce animal bite incidents and associated zoonotic disease risks. SynnopsisO_LIA large-scale retrospective analysis of 6,565 animal bite cases revealed a cat-dominant bite pattern (56.6%), contrasting with the traditional dog-dominant paradigm in South Asia. C_LIO_LIYoung adults (20-39 years) and males (60%) were disproportionately affected, reflecting occupational and behavioral exposure risks. C_LIO_LIUrban residents (88.1%) accounted for the majority of cases, highlighting the growing public health burden of animal bites in rapidly urbanizing settings. C_LIO_LIThe most frequently affected anatomical sites were the legs (50.3%) and hands (40.9%). Bite incidents showed moderate seasonal variation, with peaks in spring and early autumn. C_LIO_LICategory II exposures (98.2%) predominated, indicating a high burden of seemingly minor injuries that may be underestimated in rabies prevention strategies. C_LI

Background Pseudomonas aeruginosa is a major cause of healthcare-associated infections in paediatric settings, where its persistence in moist environments such as hospital water and wastewater systems poses a particular risk to neonates and immunocompromised children. Aim The aim of this study was to showcase the long-term survival and transmission of P. aeruginosa in a large tertiary children's hospital in England which is crucial to develop strategies for water-safe care. Methods Environmental P. aeruginosa isolates were collected from taps, sinks, showers, and baths in augmented care areas of a 330-bed tertiary children's hospital built to NHS water-safety standards. Clinical isolates were classified as invasive (blood, cerebrospinal fluid, and bronchoalveolar lavage) or non-invasive (respiratory, urine, ear, abdominal, and rectal surveillance). Variable number tandem repeat (VNTR) profiles and metadata were extracted from PDF reports, de-identified, deduplicated, and curated using Python and R. Findings This retrospective study analysed nine-locus VNTR profiles of 457 P. aeruginosa isolates submitted to the UK Health Security Agency from a large tertiary children's hospital, identifying 56 isolate clusters (each with [&ge;]2 isolates), of which 19 (34%) contained at least one invasive isolate. The most persistent cluster (Cluster 1, n=20) spanned from July 2016 to September 2024, containing environmental and clinical (invasive and non-invasive) isolates. Conclusion These findings demonstrate long-term persistence of certain genotypes and temporal overlap between environmental and clinical isolates, highlighting the difficulty in detecting and eradicating P. aeruginosa in hospital water and wastewater systems and reinforcing the need for continuous rigorous water system controls.

Foodborne illness is a significant public health concern worldwide. Shiga toxin-producing Escherichia coli and Campylobacter species are recognized as important zoonotic bacterial pathogens contributing to human infections through the food chain, particularly via foods of animal origin. Although goat meat is in high demand in the southern region of Thailand, studies on foodborne pathogens in this livestock species remain limited. The current study aimed to (i) determine the antimicrobial susceptibility of Campylobacter spp. and STEC isolated from goats, and (ii) analyze the genetic relationships among Campylobacter spp. And E. coli O157 isolates obtained from different sources. Campylobacter jejuni and C. coli isolates were characterized based on sequences of seven housekeeping genes using the Achtman multilocus sequence typing scheme. For E. coli O157:H7, core genome multilocus sequence typing analysis was performed using whole-genome sequencing data. Genetic diversity was observed among C. jejuni, whereas a clonal population structure was detected in C. coli and E. coli O157:H7. Overlapping genetic characteristics were observed between C. jejuni isolates from goats and those previously reported in livestock and humans in Thailand. Among Campylobacter species, resistance to fluoroquinolones, including ciprofloxacin and nalidixic acid, was observed, whereas resistance to fosfomycin was most frequently detected in Shiga toxin-producing E. coli. Tetracycline-resistant isolates were identified in both Campylobacter species and Shiga toxin-producing E. coli at moderate levels. A multidrug-resistant pattern was observed only in C. coli, whereas no multidrug-resistant C. jejuni or Shiga toxin-producing E. coli isolates were detected. These findings indicate that healthy goats may serve as potential reservoirs of zoonotic pathogens and antimicrobial resistance in southern Thailand, where goat meat is frequently consumed.

The majority of emerging infectious diseases are zoonotic, having their origin in wildlife before spilling over into the human population. While small mammals are recognized as critical reservoirs for these viruses, their viral diversity remains largely uncharacterized across many African countries. We conducted molecular surveillance of synanthropic rodents and shrews in the Kibera informal settlement in Nairobi and the rural Taita Hills region of Kenya to detect and characterize potential zoonotic viruses. Tissue samples from 228 rodents and shrews were screened for six viral families using PCR assays. Rat hepatitis E virus (HEV) (Rocahepevirus ratti), a rodent-associated virus with potential for human spillover, was identified in Mus musculus and Rattus norvegicus from Kibera. NGS was conducted for the HEV positive samples, and we obtained two near-complete HEV genomes from Rattus norvegicus, which clustered within rodent-associated HEV genotypes in the phylogenetic analysis. The two sequences from the Rattus norvegicus cluster together, indicating a close genetic relationship. Paramyxoviruses belonging to the genera Jeilongvirus and Parahenipavirus were detected both from Taita and Kibera in nine different samples from Rattus norvegicus, Mus minutoides, Crocidura sp and Acomys ignitus. One paramyxovirus positive sample (Acomys ignitus) from Taita was selected for further sequencing with NGS, and a complete genome of a new jeilongvirus was assembled. Phylogenetic analysis of the detected viruses confirmed the close relation to previously known rodent-borne jeilongviruses but also revealed potentially novel jeilong- and parahenipavirus species. Our findings highlight the circulation of potentially zoonotic viruses in both urban and rural small mammals in Kenya. It emphasizes the necessity of continued genomic surveillance of zoonotic viruses to mitigate risks of their spillover into human populations. HighlightsO_LISurveillance reveals diverse rodent-borne viruses circulating in Kenya. C_LIO_LIRat-HEV was detected in Rattus norvegicus and Mus musculus from an urban low-income area. C_LIO_LIParamyxoviruses were detected across multiple rodent and shrew species, including novel Acomys ignitus jeilongvirus. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC="FIGDIR/small/719784v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@194e81eorg.highwire.dtl.DTLVardef@11342cdorg.highwire.dtl.DTLVardef@186ad97org.highwire.dtl.DTLVardef@eeb516_HPS_FORMAT_FIGEXP M_FIG C_FIG

Ticks impose major health and economic losses on the livestock sector of Pakistan, yet uncertainty-aware maps of tick burden remain scarce. We focused on the two most common disease transmitting tick species, Rhipicephalus microplus and Hyalomma anatolicum, to produce exposure-adjusted district-level abundance estimates and predictions for unsampled areas in Punjab and Khyber Pakhtunkhwa (KPK). We compiled heterogeneous tick count records and standardized them per 100,000 animals. District-level climate and physiographic covariates were summarized via principal components analysis. Bayesian spatial models were fit in R-INLA using Gaussian likelihoods and BYM2 over a hybrid adjacency matrix. Competing non-spatial and spatial models were compared, and the best model was used to generate posterior predictions and 95% credible intervals for unsampled districts. Spatial models outperformed non-spatial alternatives and calibrated well. Model robustness was confirmed through eight independent 80/20 train-test splits, showing strong generalization with consistent predictions across seeds. For unsampled areas, R. microplus exhibited a pronounced north-south gradient with high predicted means but wide intervals in the northern highlands, indicating information gaps. H. anatolicum predictions were highest and most precise in southern Punjab. Sensitivity analysis highlighted a dominant spatial component, with modest contributions from PC1 and PC2. The Bayesian spatial models using the Besag-York-Mollie framework delivered comparable, exposure-adjusted tick abundance maps while quantifying uncertainty to guide surveillance. Results suggest a need for immediate control in confirmed hotspots and recommend targeted field sampling in high-uncertainty districts. The workflow generalizes to other vectors, pathogens, and regions for evidence-based livestock health planning.

IntroductionDrowning risk begins with water exposure, yet population-water relationships have rarely been quantified at scale using environmental measures. This study explored whether satellite-derived data was associated with subnational drowning mortality and whether associations differed by country income level. MethodsWe linked Global Burden of Disease (GBD 2021) age-standardised drowning mortality rates to satellite-derived exposures for 212 subnational regions across 12 countries (2006-2021; 3,392 region-years). Exposures were extracted via Google Earth Engine and standardised. Gamma-log generalised linear mixed models included region random intercepts and year fixed effects. Income-stratified models were estimated separately. Supplementary models assessed maritime vessel activity. ResultsNear-water population percentage was the strongest correlate of drowning (IRR 1.40; 95% CI 1.33-1.47). Permanent water coverage was protective (IRR 0.80; 0.73-0.88), as were nighttime lights (IRR 0.96; 0.95-0.97) and hot days [&ge;]30{degrees}C (IRR 0.95; 0.92-0.99). Mean temperature (IRR 1.17; 1.11-1.23) and precipitation (IRR 1.03; 1.01-1.04) were positively associated. Near-water effects were consistent across income strata (LIC 1.25; MIC 1.31; HIC 1.24), while other predictors showed weak or inconsistent within-strata associations. Vessel activity was modestly associated with drowning in Global Fishing Watch models (IRR 1.05; 1.01-1.09) but not in Synthetic Aperture Radar models. DiscussionSatellite-derived indicators can characterise drowning risk at scale, with population proximity to water emerging as a robust cross-context correlate. Protective associations for permanent water suggest landscape configuration may shape risk beyond proximity alone, highlighting geospatial datas value for targeting prevention where surveillance is limited.

Tick-borne diseases are now reported from nearly every county in Illinois, and three vector tick species (Amblyomma americanum, Dermacentor variabilis, and Ixodes scapularis) are of particular concern because these are responsible for most of the tick-borne disease transmission in the state. However, active surveillance is patchy, many counties have little or no sampling, and there is no statewide, quantitative map of relative abundance that can be used to anticipate risk in unsampled areas. To address these gaps, we developed Bayesian hierarchical spatial models to estimate the county-level abundance of these three vector tick species in Illinois. Using active surveillance data from 2019-2022, we modeled county-level abundance as a function of climate, land cover, forest fragmentation, and deer habitat suitability. Spatial dependence was captured using a Besag-York-Mollie 2 (BYM2) prior implemented in INLA, along with spatial 5-fold cross-validation to assess predictive performance. A. americanum showed the highest predicted abundance in southern and central Illinois, D. variabilis was widespread but diffuse, and I. scapularis was concentrated in northern and selected central counties. Together, these models provide the first spatial, statewide, uncertainty-aware assessment of tick abundance in Illinois, highlighting priority counties where surveillance lags disease risk.

Wastewater surveillance is increasingly used for antimicrobial resistance (AMR) monitoring in urban environments, but low-resource settings often lack a piped sewerage system. Instead, coprophagous flies--flies that ingest feces--may serve as composite samplers for monitoring fecal wastes present in terrestrial environments. We evaluated whether the class 1 integron-integrase gene intI1 was associated with genetic markers of AMR and fecal source tracking markers (FST) in coprophagous flies collected from latrine entrances and food preparation areas in low-income urban Maputo, Mozambique. We quantified intI1, an enteric 16S rRNA target (for normalization), three FST markers, and 30 ARG targets using qPCR. We normalized concentrations of intI1 and each target to enteric 16S rRNA. We fit linear mixed models with a random intercept for housing compound to estimate within-fly associations between log10 relative abundance of intI1 and log10 relative abundance of each target with and without adjustment for fly taxonomic group, capture location, and standardized fly mass. We also modeled per-fly unique ARG count (i.e., number of ARG targets detected) using Poisson regression. Of 188 flies assayed, 176 passed internal controls; intI1 and enteric 16S rRNA were detected in 95% and 96% of flies, respectively. Higher relative abundance of intI1 was positively associated with ARG and FST targets, with the strongest associations observed for sulfonamide-(sul1: {beta} = 0.87; 95% CI: 0.81, 0.94; sul2: {beta} = 0.81; 95% CI: 0.73, 0.89), tetracycline- (tetA: {beta} = 0.78; 95% CI: 0.70, 0.85; tetB: {beta} = 0.69; 95% CI: 0.60, 0.79), and trimethoprim-related (dfrA17: {beta} = 0.78; 95% CI: 0.70, 0.86) genes. Associations with FST markers were weaker (i.e., human mtDNA: {beta} = 0.46; 95% CI: 0.37, 0.55; human-associated Bacteroides: {beta} = 0.34; 95% CI: 0.25, 0.43). Higher relative abundance of intI1 was also associated with a greater number of ARGs detected: each 10-fold increase in intI1 was associated with an 8% higher expected unique ARG count (aRR=1.08, 95% CI: 1.04-1.12). These findings support the need for further research across different settings exploring intI1 carried by coprophagous flies as a potential standardized screening target for AMR surveillance in unsewered terrestrial environments.

Drowning remains a major global public health challenge, yet how built environment characteristics shape population-level drowning risk remains poorly understood. This study linked satellite-derived built environment data to subnational drowning mortality estimates across 203 regions in 12 countries from 2006-2021. It found that built environment associations with drowning mortality are complex, non-linear, and shaped by development context. Urban extent was strongly protective, while built area near water showed protection overall but increased risk when combined with high population crowding. Almost all drowning mortality variance occurred between regions rather than within regions over time, indicating risk is predominantly determined by place-based characteristics. Income-stratified analyses revealed profound heterogeneity: crowding was protective in low-to middle-income settings but near-null in high-income regions, while waterfront development captured very different realities across contexts. These findings highlight the importance of tailoring drowning prevention strategies to local built environment configurations and development contexts.

Urinary tract infections (UTIs) are among the most common infectious diseases worldwide, with Escherichia coli being the predominant uropathogen. The increasing prevalence of extended-spectrum beta-lactamase (ESBL)-producing strains and their association with fluoroquinolone resistance pose a significant challenge to empirical therapy, particularly in community settings. The aim of this study was to determine the epidemiology and predictive factors associated with ESBL-producing E. coli and its concomitant fluoroquinolone resistance in community-acquired clinical isolates. A retrospective cross-sectional study was conducted analyzing 244 clinical E. coli isolates. Demographic and microbiological data were collected, including age, sex, sample type, and antibiotic susceptibility. Associations between variables and ESBL production were assessed using Pearsons chi-squared test, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Of the isolates, 165 (68%) were ESBL-producing. A significant association was observed between age group and ESBL production (p < 0.001), with the highest frequency in the 20-39 age group. Most ESBL-positive isolates were obtained from women (73%), although odds ratio (OR) analysis suggested a non-significant trend toward a higher probability in men (OR = 1.29; 95% CI: 0.72-2.31). High rates of fluoroquinolone resistance were identified among the ESBL-producing isolates, with 30% resistance to levofloxacin and 35% to ciprofloxacin (p < 0.001). Urine samples showed the highest concentration of ESBL-positive isolates, with a significant association between sample type and resistance (p < 0.001). The high prevalence of ESBL-producing E. coli and its concomitant resistance to fluoroquinolones highlight a critical challenge for the empirical treatment of urinary tract infections in Mexico, underscoring the need to strengthen antimicrobial use management and local surveillance strategies.

Emerging infectious diseases and antimicrobial resistance (AMR) have surfaced as two major public health threats over the past two decades. Consequently, integrative surveillance systems capable of detecting both emerging pathogens and resistance-carrying bacteria are crucial. With advances in next-generation sequencing, simultaneous detection of pathogens and AMR is increasingly feasible. In this study, we used short-read metatranscriptomics complemented by total 16S rRNA metagenomic long-read sequencing to analyze paired oral and plasma samples from a cohort of febrile individuals at two locations in Senegal. Oral microbiomes differed in community composition between locations, and reduced diversity and richness were significantly associated with high fever. We identified at least one known pathogen in 15.33 % (23/150) of samples, with Borrelia crocidurae as the most frequently detected pathogen. We detected both pathogenic and non-pathogenic viruses in oral (10/72) and plasma (09/78) samples. Finally, we observed a high frequency of genes associated with resistance and virulence: 10% of samples expressed at least one AMR gene (ARG), and 24% expressed virulence factor genes. Resistance to widely used beta-lactam antibiotics was the most prevalent. Our findings provide critical data on oral and plasma microbiomes in the context of acute febrile illness in Senegal while expanding understanding of circulating ARGs.

BackgroundDrowning remains a major global public health challenge. This study examined whether the timing and trajectories of urbanisation--beyond the current built environment--are associated with subnational drowning mortality. MethodsWe linked satellite-derived measures of built-environment change (GHSL), population crowding (WorldPop), surface water exposure (JRC Global Surface Water), and infrastructure proxies (VIIRS/DMSP nighttime lights) to GBD 2021 drowning mortality estimates across 203 ADM1 regions in 12 countries (2006-2021; 3,248 region-year observations). Temporal predictors captured recent expansion, development "newness" ([&le;]10-year built share), acceleration/volatility, and a crowdingxgrowth interaction. We screened predictors using LASSO (10-fold cross-validation) and fitted mixed-effects models with region random intercepts. Distributed-lag models tested temporal precedence and development age, and income-stratified models assessed heterogeneity. ResultsAdding temporal predictors improved fit beyond contemporaneous built-environment measures ({Delta}AIC=177; {Delta}BIC=147). In adjusted models, crowdingxgrowth was strongly positively associated with drowning mortality, and a higher share of recent development was associated with higher mortality. Lag models showed a development age gradient: older built environment was most protective. Associations differed by income group, with several key coefficients reversing sign across strata. DiscussionDrowning mortality appears shaped by development histories as well as present-day conditions, with risk concentrated in rapidly changing, dense settings and the newest built environments. Cross-context heterogeneity suggests mechanisms and prevention priorities are unlikely to be uniform. ConclusionsDevelopment timing and trajectories help explain subnational drowning mortality beyond current built form alone. Prevention and planning should prioritise transition-period safety strategies in newly developing and rapidly densifying areas.

There is an ongoing Oropouche Fever (OF) outbreak in Brazil since 2024. There are dengue and chikungunya prediction models available, but none to help discriminate dengue, chikungunya, and OF. Objective: This study aims to develop and validate clinical prediction models for dengue, chikungunya, OF. Methods: This study uses surveillance data from Espirito Santo state / Brazil, from 2023-2025. Epidemiological investigations and biological samples were used to conclude cases as either (a) clinical-epidemiologically confirmed, (b) laboratory confirmed, or (c) discarded. The predictors were all data related to signs, symptoms, and comorbidities available in the notification forms. The analysis was performed using random forest regression models, one for each outcome, in development and validation datasets. Results: A total of 465,280 observations were analyzed, 261,691 dengue cases (56.6%), 18,676 chikungunya cases (4.0%), 12,174 OF cases (2.6%), and 179,115 discarded cases (38.6%). All three models had good discrimination and moderate to good calibration after scaling prediction. The models retained from 26 to 16 predictors each. Leukopenia and vomiting were the most discriminatory predictors for dengue, arthritis, arthralgia, and rash were the most discriminatory for chikungunya, and epidemiological features were the most relevant for OF. The dengue, chikungunya, and OF models had ROC AUC of 0.726, 0.851, and 0.896 in the validation set, respectively. Conclusion: This research identified predictors most discriminative between dengue, chikungunya, and OF. We developed and validated predictive models, one for each condition, with moderate to very good performance available at https://pedrobrasil.shinyapps.io/INDWELL/. One may use them in diagnostic work-up and arbovirus surveillance.

Subsistence agriculture in sub-Saharan Africa faces persistent productivity challenges due to low soil fertility, limited inputs, and increasing climate variability. Agroforestry can offer a sustainable strategy for smallholder systems by enhancing soil quality and the presence of arbuscular mycorrhizal fungi (AMF) in crop roots. Using a canopy-based radial sampling design, we assessed the influence of Mangifera indica (mango) trees on soil properties and AMF communities in maize and cassava in southern Ethiopia. Illumina MiSeq sequencing identified 908 AMF operational taxonomic units (OTUs) from 7 families, dominated by Glomeraceae. While soil properties, including pH, total nitrogen (TN), organic carbon, and potassium, were significantly affected by the distance from mango trunks, this was not the case for AMF community composition and AMF richness and diversity. Host identity, rather than distance from the mango trees, was the primary driver of AMF community composition, with distinct and host-specific assemblages in mango, maize, and cassava roots. Soil nutrients influenced AMF diversity differently across hosts. In maize-mango systems, TN positively affected observed richness (Sobs) and Shannon diversity (N1), whereas Olsen P negatively affected N1 and Simpson diversity (N2). In cassava-mango systems, TN enhanced Sobs, and Olsen P positively influenced expected richness (Sexp). Overall, these findings demonstrate a decoupling between mango-induced soil fertility enhancement and crop AMF community composition and diversity, rather emphasizing the roles of host type and soil nutrients in structuring AMF communities. Without demonstrating direct benefits, we at least show that mango can be effectively integrated into smallholder maize and cassava production without compromising the AMF communities, while enhancing key soil fertility indicators. Maintaining adequate nitrogen levels while avoiding excessive phosphorus inputs may help sustain stable AMF communities in agroforestry systems.

O_LIThe management of invasive species often emphasizes removals to manage populations. However, evaluating the success of this management technique remains challenging, especially at large scales. Understanding the relationship between removal intensity and population growth is essential for determining when management achieves desired outcomes. C_LIO_LIWe used management removal data (removal resources [e.g. trapping] and relative effort [trap nights]) to estimate population density, demographic structure, and growth rates of invasive wild pigs (Sus scrofax domesticus) across a large landscape. From the management data and population estimates, we inferred population trajectories in the absence of removals and quantified the proportion of the population removed by the most widely used methods to control wild pigs. We then compared observed removal intensities and population growth rates to predict expected population trajectories immediately after management occurs. C_LIO_LIResults suggest substantial spatial and temporal variation in wild pig growth rates and variation in the effectiveness of removal efforts. Additionally, removing wild pigs at higher densities had a greater effect on limiting population growth than removals conducted at lower densities, though both are important. However, on large properties, removal intensity was often insufficient to offset population growth, indicating that management effort does not scale to large areas. C_LIO_LIThese results demonstrate how removal data and population modeling can provide robust inference on population dynamics and management effectiveness, offering a scalable framework for evaluating and improving invasive species control programs. We also discuss the current limitation of how effort is defined for different large-mammal removal techniques, and offer potential solutions for a more complete definition, such as going beyond trap nights and including constraints on personnel, equipment, and logistics. C_LI

This pilot study assessed the composition and diversity of the urinary microbiome from clinically confirmed UTI samples using 16S rRNA sequencing, whilst also exploring inter-individual variability of microbial community structure. We examined ten urine samples from patients with culture-positive UTIs. Demographic and clinical metadata, including age, sex, body mass index (BMI), diabetes status and recent antibiotic exposure was recorded per sample. Metagenomic DNA was extracted from microbial samples and sequenced to generate genus-level taxonomic profiling through 16S rRNA gene sequencing. Relative abundance tables were generated for each of the samples to identify dominant bacterial genera within each sample and summarize cohort level microbial patterns. To evaluate within-sample richness and evenness, alpha diversity indices (Shannon, Simpson, observed features and Chao1) were computed; beta diversity was measured using Bray-Curtis dissimilarity with principal coordinates analysis (PCoA) for graphical representation. The studys findings revealed the sex and moderate clinical diversity of the study sample; all samples were confirmed as having been taken from a UTI patient and exhibited a wide level of heterogeneity regarding the microbial composition of each urine sample. Overall, Pseudomonas was the dominant genus present, however, specific samples had approximately 50% of their microbiomes composed of Klebsiella, Proteus, and Escherichia species as well as approximately 25% of their total microbes were made up of Burkholderia spp., which are closely related to the genus of interest used during the course of this study. The observed alpha diversity of each sample displayed considerable variation for the included samples with a continuum of samples ranging from a single dominant microbe to a highly diverse mixed population producing a highly diverse polymicrobial population/bacterial composition, with some ratios of individual taxa to collective taxa of many samples repeatedly illustrating the exact nature of the specimen. Furthermore, a significant degree of Beta diversity was found between the patients, providing compelling evidence of identifiable differences among urinary microbiomes between patients with UTI. This pilot project provides a clear indication of the diversity and overall heterogeneity of urinary microbiota found in the UTI patients studied. In addition, the results of this study support the notion that the ecological complexities present within a urinary microbiome cannot necessarily be established through conventional culture methods, and that combined with molecular techniques such as 16S rRNA sequencing of bacterial DNA could be used to quantify and characterize the ecologic condition of urinary microbiota separate from the traditional high prevalence of identifiable uropathogens.

Canadas ambition for mineral security and its responsibilities to protect at-risk species and uphold Indigenous rights clash in the case of the Grays Bay Road and Port (GBRP) in Nunavut, an infrastructure project intended to unlock critical mineral deposits. We compiled Indigenous and Western science through a density analysis of caribou harvesting data near the proposed project site. We identified three consistently used harvesting hotspots, with the most significant hotspot lying directly in the path of the proposed GBRP project. These results indicate that the GBRP project will have significant and unmitigable negative effects on caribou conservation, food security, and Inuit harvesting rights. Prime Minister Carney claims that middle power countries must act consistently in this era of geopolitical rupture; this commitment must transfer to natural resource development reviews so that decision-making may be consistent and rooted in cross-legislation responsibilities and values, including the land claims agreements between Indigenous groups and the Government of Canada.

Background Tuberculosis (TB) remains a critical public health challenge, with two-thirds of the global TB burden in ten Asian countries. Social vulnerabilities, comorbidities, health inequity, multi-dimensional poverty, malnutrition, and barriers to healthcare access continue to fuel TB epidemic. Inability to detect asymptomatic and sub-clinical TB, combined with passive approach in service delivery and overreliance on smear microscopy, leads to delayed diagnosis, a substantial burden of undetected cases, and continuing TB transmission in the communities. In such a context, the introduction and scale-up of active case-finding approaches - including community-based TB screening using highly sensitive screening tools and novel rapid diagnostics - becomes a strategic priority to interrupt transmission. The growing availability of multiple screening and diagnostic options makes evidence-based decision-making increasingly complex. Methods To estimate the potential epidemiological impact and cost implications of scaling up TB diagnostics and community-based screening in ten high-burden Asian countries, we constructed a mathematical model and evaluated multiple intervention scenarios. We then assessed and compared four service delivery models: 1) digital ultraportable chest x-ray (UPCXR) & Xpert/Truenat in community, 2) digital UPCXR in community and Xpert/Truenat at health facilities, 3) digital UPCXR in community and near point of care (nPOC) at health facilities, 4) nPOC in community & Xpert/Truenat at health facilities - for total investment required and projected health benefits for their cost-effectiveness. Results and conclusions The modelling study indicated that strengthening health facility capacity (with enhanced TB screening, expanded molecular diagnostics, reduced loss to follow-up, private sector standard of care, leading to increased treatment coverage & quality of active disease treatment and reduced post-treatment relapse, scale-up of TB preventive treatment (TPT), and provision of nutritional support to 80% of TB patients and their household contacts) can significantly reduce TB incidence and mortality; however, community-wide mass screening remains essential to achieving TB elimination targets . Targeted screening of vulnerable populations demonstrated greater cost-effectiveness than untargeted screening approaches. Achieving the End TB goals will ultimately require an effective TB vaccine with high population-level coverage. AI-enabled digital UPCXR-based screening combined with Xpert/Truenat testing at the community level demonstrated maximum epidemiological impact potential, while the most cost-efficient model is Digital UPCXR in the community combined with nPOC testing at health facilities. An investment of USD 12.7 billion over the next five years in community-level implementation of digital UPCXR and molecular diagnostics could avert an additional 9.8 million TB cases and 1.9 million deaths across ten Asian countries over a ten-year horizon.

Bacillus paranthracis was formally defined as a species in 2017, after decades of carrying the name "emetic B. cereus" based on cereulide production and clustering within B. cereus sensu lato phylogenetic group III. Commonly associated with foodborne intoxication, reports rarely link B. paranthracis to non-foodborne clinical illness. As such, the new taxonomy and close resemblance of the name to the biothreat pathogen Bacillus anthracis cause confusion in diagnostic and public health settings. To address this issue, B. paranthracis clinical strains (n=20) from the CDC collection were tested with microbiological methods used for identification of B. anthracis and antimicrobial susceptibility testing. Some B. paranthracis phenotypes were similar to B. anthracis, however others were inconsistent across strains. Like B. anthracis: 3 strains tested capsule positive, 5 were non-hemolytic on blood agar, and 9 non-motile. All B. paranthracis strains were resistant to gamma phage lysis, which differentiated them from B. anthracis. Treatment regimens for B. paranthracis infections are not well established, as antimicrobial therapy is not indicated for emetic intoxication caused by B. paranthracis. Notably, six B. paranthracis strains had elevated minimal inhibitory concentrations to anthrax-recommended antibiotics: one for ciprofloxacin, three for doxycycline and tetracycline, and two for clindamycin. Rapid MinION sequencing was assessed for antimicrobial resistance detection prediction but had limited value when using PiMA v.1. These microbiological observations and susceptibility profiles of B. paranthracis expand our understanding of this pathogen, strengthening our ability to differentiate this bacterium from B. anthracis to improve diagnosis and patient outcomes. IMPORTANCEThis study describes in vitro characterization of 20 archived clinical strains of B. paranthracis, an opportunistic pathogen identified more frequently in recent reports. Our findings highlight phenotypic differences and similarities between B. paranthracis and B. anthracis using standard microbiological methods and drug susceptibility profiling. We also assess a rapid B. anthracis specific MinION long read genome sequencing workflow with B. paranthracis. This report highlights the overlapping morphological features shared by B. paranthracis and B. anthracis to improve future laboratory diagnosis and strengthen anthrax preparedness. This article will effectively reach an audience of public health professionals and microbiologists strengthening anthrax preparedness.

Background: Mucormycosis is a rapidly progressive and often fatal invasive fungal infection caused by moulds in the order, Mucorales. Early diagnosis is essential for effective clinical management; however, conventional diagnostic approaches such as culture and histopathology are slow, insensitive, and require specialist mycological expertise. Although molecular methods are available for disease detection, they are not widely accessible. At present, no enzyme immunoassay (EIA) exists for the detection of mucormycosis. Methods: A murine IgG1 monoclonal antibody (mAb), FH12, was generated against extracellular polysaccharides (EPSs) produced by Mucorales pathogens during active growth. The antibody was characterised for specificity, epitope stability, and antigen localisation using ELISA, immunoblotting, and immunofluorescence techniques. The mAb was incorporated into a Sandwich-ELISA and evaluated using culture filtrates, purified EPSs spiked into human serum, and tissue homogenates from a patient with cutaneous mucormycosis caused by Lichtheimia ramosa. Results: mAb FH12 demonstrated pan-Mucorales specificity and no cross-reactivity with other clinically relevant yeasts and moulds. The epitope recognised by FH12 is periodate-insensitive and moderately heat-stable. The Sandwich-ELISA detected EPS antigens in human serum with limits of detection ranging from pg/mL to low ng/mL levels, and successfully identified the EPS biomarker in patient tissue homogenates. Conclusion: The FH12-based Sandwich-ELISA shows high sensitivity and specificity, and has the potential to be used as a laboratory-based adjunct diagnostic test for the detection of mucormycosis in humans.