PLOS Water

Background: Population-based biomonitoring of contemporary-use pesticides remains limited in the United States, particularly in rural agricultural regions, and few studies have repeated measurements within the same individuals over time. Methods: We analyzed 28 urinary pesticide-related biomarkers among 600 adults from the population-based Survey of the Health of Wisconsin with archived urine collected during 2008-2016; 296 participants provided repeat urine and updated exposure information in 2025. Detection frequencies, co-detection, and within-person detection patterns were characterized. Generalized estimating equations were used for stacked, repeated-measures analyses of factors associated with detection of aminomethylphosphonic acid (AMPA), glyphosate, 2,4-dichlorophenoxyacetic acid (2,4-D), and any of these three. Prospective-only analyses evaluated more detailed agricultural and recent exposure measures. Results: Glyphosate, AMPA, and 2,4-D were detected in 7.7%, 6.2%, and 4.3% of retrospective specimens and 5.4%, 3.1%, and 4.1% of prospective specimens, respectively. Co-detection and persistent detection across the 9 to 17-year interval was rare. In repeated-measures models, greater fruit and vegetable intake, older age, and male sex were associated with higher 2,4-D detection. Lower household income was associated with lower AMPA detection, while afternoon/evening collection was associated with higher AMPA detection. In prospective analyses, working on field-crop agricultural land showed the strongest agricultural associations, particularly for 2,4-D and detection of any of the three pesticides. Associations were not seen with self-reported conventional versus organic produce consumption. Conclusions: Urinary pesticide detections were generally infrequent in this Wisconsin population. Diet and direct agricultural activities may be more informative exposure pathways than residing near cropland or private well drinking-water characteristics.

Wastewater-based epidemiology (WBE) has emerged as a powerful population-level surveillance tool, but its coverage is structurally concentrated in in-network urban areas, potentially leaving rural populations underrepresented. Routine human movement between sewered (in-network) and unsewered (off-network) areas may, however, cause wastewater treatment plant (WWTP) measurements to reflect infectious disease dynamics beyond sewer boundaries. We evaluated this hypothesis using daily clinical COVID-19 testing data (January 2021-April 2022) across New York State excluding New York City (NYC). We disaggregated weekly cases and tests into in-network (WWTP catchment area) and off-network (outside WWTP catchment area) components applied to two geographic frameworks: administrative counties (N = 53 mixed-coverage) and mobility-defined communities identified through Walktrap community detection applied to census tract-level movement networks (N = 32 mixed-coverage). In/off-network COVID-19 trends were strongly correlated under both frameworks. County-level statewide aggregate correlations were high (incidence r = 0.994, positivity r = 0.996), as were individual county correlations (median r = 0.909 and 0.932, respectively). Mobility-defined community-level statewide correlations were similarly strong (r = 0.990 and 0.992), with comparable unit-level medians (r = 0.877 and 0.894). The mobility-defined community framework provided better population balance between in-network and off-network strata (87.5% vs. 69.8% in balanced range) and a higher floor on representativeness (minimum r = 0.440 vs. 0.177). Population size was the dominant predictor of in-network/off-network alignment at both scales; wastewater infrastructure density and off-network signal variability provided additional explanatory power at the mobility-defined community level. WWTPs broadly represent COVID-19 dynamics in surrounding off-network populations, supporting their use as sentinel surveillance sites. Representativeness weakens in smaller, more rural communities, and mobility-defined communities provide a complementary framework for identifying where this occurs.

Wastewater surveillance (WS) offers a non-invasive means of tracking population-level circulation of infectious agents, including viruses linked to cancer. This study provides the first Australian assessment of oncogenic viruses in municipal wastewater by screening 76 influent samples collected over four months from six wastewater treatment plants in Southeast Queensland, Australia. Ten gene targets representing seven oncogenic viruses including Epstein-Barr virus (EBV), hepatitis B virus (HBV), hepatitis C virus (HCV), human herpesvirus 8 (HHV-8), human papillomavirus 16 and 18 (HPV-16 and -18), human T-lymphotropic virus type 1 (HTLV-1), and Merkel cell polyomavirus (MCPyV) were analysed using PCR-based methods. All viruses were detected in wastewater at least once, though with substantial variation in frequency. MCPyV was the most frequently detected virus, appearing in 97.3% of samples with concentrations ranging from 3.09-3.85 log10 gene copies (GC)/50 mL, indicating widespread population exposure. HBV (26.3%) and EBV (15.8%) were detected intermittently across multiple catchments, while HPV-16/18, HHV-8, HTLV-1, and HCV were detected at the lowest frequencies (<8%). This study reports the first baseline dataset for oncogenic viruses in Australian wastewater. More broadly, positive detection of all targeted oncogenic viruses including those associated with low prevalence infections in wastewater demonstrates the potential of WS to complement existing cancer surveillance systems in tracking community-level circulation of these infectious agents.

Micronutrient deficiencies are prevalent in Madagascar, where diets rely heavily on starchy staples and access to animal-source foods is limited. Small dried fish (SDF) are widely available, yet their nutritional value and health risks remain poorly documented. We combined market surveys, taxonomic identification, and micronutrient and heavy metal analyses of nine SDF types collected along National Road 7. The samples encompassed 33 fish families, were dominated by small pelagic species (Clupeidae and Engraulidae), and were appreciated by consumers. A daily portion (5 g for infants; 10 g for young children and women of childbearing age) contributed substantially to Recommended Nutrient Intakes (RNIs). Across samples and groups, SDF were rich (>30% of RNI) in selenium and, for infants and young children, in calcium. All samples were a source of (>15% of RNI), or rich in, phosphorus, whereas iron contributions were more variable but often substantial. Several samples exceeded 100% of RNIs for selenium, calcium, iron, or manganese in infants and young children, and some were also sources of magnesium and, less frequently, zinc. Vitamin A was absent from sun-dried samples but detected in a smoked freshwater type. Heavy metal concentrations varied markedly, and portions of several types led to estimated exposures to inorganic arsenic or cadmium exceeding reference values, whereas freshwater species and some pelagic types showed a more favorable nutrition-risk balance. Overall, SDF are affordable, nutrient-dense foods with strong potential to alleviate micronutrient deficiencies in Madagascar, while highlighting the need for type-specific guidance to balance nutritional benefits and contamination risks.

Context Pumping stations pose a threat to fish globally through land use change, habitat fragmentation and entrainment risk, with the catadromous and critically endangered European eel particularly impacted. Objectives/methods Establish, model, assess and understand the present-day distribution of European eel and resident fishes in 152 pumping station catchments in a once extensive wetland (The Fens) using eDNA metabarcoding (855 samples over two and half years), with specific focus on anthropogenic influences on hydrological connectivity and habitat quality. A removal survey design maximised confidence in negative results while minimising time and consumable costs. Results Eel occurrence upstream of pumping stations was low (occupancy = 28.3%) and positively associated with catchment area, fish species richness and natural hydrological connectivity (gravity drainage or flooding) and negatively associated with distance from the tidal limit. Fish species richness replaced catchment area and improved model performance, potentially acting as a biotic indicator of habitat quality and connectivity. Pumped catchments with manually operated upstream water transfers had reduced eel presence, potentially linked to the direction of water flow or the timing of operation. By contrast, fish species richness increased in these catchments during summer, suggesting displacement into unsuitable long-term habitats. Physical habitat maintenance had no detectable effect on eel occurrence or fish species richness. Conclusions This study provides the first landscape-scale assessment of European eel distribution and drivers of occurrence in pumped river catchments. The highly novel and comprehensive insights have implications for European eel conservation as well as infrastructure and catchment management, including compliance with legislation (EC Regulation No. 1100/2007).

Rinsing-dependent dental hygiene presents a significant public health challenge in water-scarce environments. This study investigated combinations of xylitol (Xyl), chitosan (Chi), glycyrrhizin (Gly), epigallocatechin gallate (EGCG), dicalcium phosphate (DCP), and nano-hydroxyapatite (nHA) on the primary bacteria behind dental caries, S. mutans. These combinations were assessed for markers of dental caries by biofilm reduction, bacterial killing, and acid buffering against S. mutans when applied to an in vitro simulated enamel model using glass bead surfaces for biofilm formation, and gene expression was subsequently examined via RT-qPCR. Separately, mineral retention was also quantified. The EGCG-DCP-Xyl film demonstrated the highest overall efficacy, achieving a significant reduction in biofilm concentration compared to the untreated control and performing similarly in magnitude to the positive toothpaste control. Dead fluorescence staining confirmed that the EGCG-DCP-Xyl film induced the highest rate of non-viable cells, followed by the Chi-Gly film and the Gly-Xyl film. During 10-day pH cycling, the EGCG-DCP-Xyl and DCP-Xyl formulations buffered pH the most, consistently maintaining mean pH levels safely above the demineralization threshold of pH 5.5. The EGCG-DCP-Xyl also optimized mineral stability with the highest retained calcium concentration, significantly outperforming the Chi-Xyl film. At the transcript level, the EGCG-DCP-Xyl film induced substantial downregulation of key virulence genes, yielding decreases in expression for glucosyltransferase B (gtfB), associated with biofilm synthesis, collagen-binding protein (cnm), associated with tissue invasion, and lactate dehydrogenase (ldh), associated with lactic acid production, compared to the untreated control, with effects comparable in magnitude to the positive toothpaste control. This research suggests that targeting bacterial pathways and mineral loss through a portable film may have potential for preventing dental caries, especially in environments where water is limited. However, additional studies are necessary to evaluate real-world effectiveness.

Microbial and biochemical properties of soil respond quickly with management practices, than chemical and physical properties. Moreover, impact of conservation agriculture (CA) on soil microbial properties is limited to microbial enumeration, but its effect on soil enzyme and microbial activity is little documented. To address these problems soil enzyme activities [dehydrogenase (DHA), {beta}-glucosidase (BGA), acid phosphatase (AcP) and alkaline phosphatase (AlP) and fluoresceine diacetate (FDA)], microbial activites ((Nitrogen fixation (NFBAct), Phosphate solubilization (PSBAct) & Cellulolytic activities (CDBAct)), microbial biomass ((Soil microbial biomass carbon (SMBC) & soil microbial biomass nitrogen (SMBN)) and available nutrient were studied to evaluate biological soil health in alluvial soil of lower Indo-Gangetic plain (IGP) under CA. Field experiment was conducted in split plot design (SPD), under 3 cropping systems (RMCp: rice-maize-cowpea; RWGg: rice-wheat- green gram; RCfBr; rice-cauliflower- bororice/summer rice). Tillage operations (CT: conventional; MT: minimum and ZT: zero tillage) was main plot and residue application as sub plot treatments [(R0 (no residue), R50 (50% residue) and R100 (100% residue)], treatments were replicated thrice. Biological soil health index (BSHI) indicated that among different degree of CA, ZT (0.464) and (MT=0.441) and R100 (0.464) treatment showed better response. Among different cropping system RMCp (0.359) & RWGg (0.343) outperformed RCfBr (0.609) cropping system with respect to (wrt) microbial and biochemical properties of the soil. Results indicated that for restoring microbial and biochemical properties of soil CA can be used as sustainable practice to restore agro-ecosystem. Keywords: Conservation agriculture, Cropping systems, Soil enzyme, Soil microbial properties, Residue application, Tillage operations.

Purpose: This study assesses the association between colorectal cancer (CRC) screening and a validated, housing-based measure of individual-level socioeconomic status (SES, called HOUSES hereafter) within rural communities and determines whether HOUSES-integrated geospatial analysis can be used to tailor interventions. Methods: We used CRC screening data from a subset of Mayo Clinic Midwest patients living in cities without ready access to routine care in the Mayo Clinic Health System in 2019 to represent rural communities. At the individual level, we assessed the association between CRC screening rates and the HOUSES index, adjusting for age, sex, race/ethnicity, comorbidity, distance from home address to clinic, and area deprivation index, using a multilevel mixed-effects logistic regression model. Additionally, we conducted geospatial analysis to examine the correlation between hotspots of 1) lower CRC screening rates and 2) lower SES of the subject population (HOUSES quartile 1). Findings: Among 34,489 individuals (median age 64.0 years, 52.4% female), those with the lowest SES (HOUSES Q1) had 37% lower odds of being CRC screening adherent than those with the highest SES (HOUSES Q4) (adj. OR [95% CI]: 0.63 [0.58-0.69]). In the 14 identified HOUSES Q1 hotspots, there was a significant correlation in counts of HOUSES Q1 and low CRC screening (correlation coefficient=0.81). Conclusion: Lower SES was significantly associated with lower CRC screening among rural populations. HOUSES-enabled geospatial analysis identified geographic hotspots with lower CRC screening rates for targeted interventions to address disparities in CRC screening in rural communities. HOUSES may be a useful digital tool for cancer preventive care and research.

Background: Community case management has been scaled up nationally in Zambia over the last decade. However, there is limited evidence on how this nationwide implementation has affected febrile patients' access to malaria diagnosis and treatment in Zambia. Methodology: This study analyzed four rounds of Malaria Indicator Survey (MIS) data (2012-2021) to evaluate: 1) proportion of all-ages individuals with fever who sought treatment from a formal provider, 2) proportion of individuals going to CHWs over time, among those who sought treatment at a formal provider, 3) time duration between fever onset and treatment seeking at a formal provider, and 4) proportion of children <5 with malaria that received Artemether-Lumefantrine (AL) treatment. Mixed-effect logit models were employed to examine determinants of treatment-seeking behavior and factors affecting AL receipt among children <5 with malaria cases. Results: The proportion of febrile patients seeking treatment remained below 60% throughout 2012-2021, and AL receipt among children with malaria cases consistently stayed below 50%. The mean interval between fever onset and initial treatment-seeking encounter decreased from 2.42 days in 2012 to 1.71 days in 2021. Among formal care seekers, CHW utilization increased from 1.5% in 2012 to 10.0% in 2018 before declining to 3.2% in 2021. Longer walking time to the nearest health facility was associated with lower odds of treatment seeking, whereas CHW density was not associated with treatment seeking or AL receipt. Children who did not went to formal providers had lower odds of AL receipt than those who sought treatment from CHWs. Conclusion: Despite nationwide CCM scale-up over the last decade, significant barriers persist in malaria patients' access to diagnosis and treatment in Zambia. Our results indicate that while CCM coverage should be maintained and further expanded, additional complementary interventions are also needed to overcome remaining access barriers.

Background: Snakebite envenoming is a major cause of preventable death and disability in the Brazilian Amazon, where long distances, sparse roads, and dependence on river transport delay access to antivenom. We developed location-allocation models to identify community health centers that could strategically expand access to antivenom in Amazonas State, Brazil. Methodology/Principal Findings: We conducted an ecological geospatial study using a 2025 WorldPop population surface, locations of existing and candidate health facilities, and a multimodal road-and-river transportation network derived from OpenStreetMap and HydroSHEDS. Population demand was represented by 7,065 populated centroids, including 1,586 within Indigenous territories. We applied a maximize-coverage algorithm with a six-hour travel-time threshold. Two models were developed: one for Amazonas excluding Manaus and one for populations living in Indigenous territories. Both models began with 77 facilities already providing antivenom and progressively added candidate community health centers until coverage gains plateaued. The plateau occurred at 110 facilities, corresponding to 33 additional centers. In the model excluding Manaus, this configuration covered 1,118,831 people, or 75.11% of the target population; 87.61% of those covered could reach care within three hours. In Indigenous territories, coverage increased from 50.55% to 69.50%, reaching 50,434 people, of whom 81.39% were within three hours of care. Validation used 3,595 snakebite notifications from the 30 highest-burden municipalities in the Brazilian Notifiable Diseases Information System during 2023-2025. The median proportion reaching care within six hours was 40.81% in observed data and 72.17% in model estimates. Conclusions/Significance: Strategically equipping 33 additional existing community health centers could substantially expand timely access to antivenom, particularly in rural and Indigenous areas. Location-allocation modeling that incorporates river transportation can support evidence-based decentralization of time-sensitive health services in geographically complex settings.

All primary healthcare centers owned by the Ugandan government in the Western Region of Uganda were submitted to a questionnaire concerning current availability of POCT from the Essential diagnostic List 2 part 1a and 1b, and the African laboratory inventory done by African Society of Laboratory Medicine and AfricaCDC. The data from the questionnaire was then linked to open source geodata provided by TomTom, and population data to calculate and visualize the accessibility of captured POCT. Findings: Availability of POCT Malaria is almost 100%, HIV 68-90%, and >30% for a majority of the POCT in the EDL-2 panel. 90% of the population in Western Region live within 1 hour by car from most of the essential POCT. Figures in the complementary web-based application visualize the accessibility of POCT for Western Uganda. Diagnostic deserts are visualized. Interpretation: Access to POCT at primary health care facilities in western Uganda has expanded substantially over the past decades. The geo-mapping tool presented here could inform policy decisions on strengthening diagnostic capacity at the national, regional, and provincial level. Funding: Swedish Research Council and Infravis All supplementary materials and a preprint of this submission are available on our OSF repository https://osf.io/j7puk/.

Background: Transmission pathways of enteric pathogens have been broadly characterized; however, the degree to which different pathogens exploit different transmission routes and how these patterns vary across age remain poorly understood. We quantified the relative contribution of within-household (infection sources internal to the household) and community-to-household (infection sources external to the household) transmission for Shigella and Campylobacter. Methods: We conducted paired longitudinal cohort studies in urban Bangladesh and rural Tanzania, each enrolling 100 households with a child under the age of one year. Stool samples were collected from participants' households monthly and during diarrheal episodes for one year. We estimated daily infection trajectories for each participant for Shigella and Campylobacter. We used these data in a household transmission model, estimating within-household and community-to-household transmission rates by pathogen, age group, and study site, using forward selection to identify interactions. Findings: Overall, 8.8% of Campylobacter and 7.6% of Shigella infections were symptomatic. The incidence of Shigella and Campylobacter was 2.3 and 1.4 times higher, respectively, in Bangladesh compared to Tanzania. Crude associations suggest that Campylobacter had greater community-to-household versus within-household transmission compared to Shigella, but these patterns were better explained by interactions with age. Specifically, children <5 years had higher transmission rates for Campylobacter than Shigella, and, for both pathogens, higher community-to-household than within-household transmission rates. Those [&ge;]5 years had higher Shigella transmission. Interpretation: Apparent pathogen-specific differences in transmission patterns for Shigella and Campylobacter were driven by effect modification by age. Intervention design should consider age-specific transmission patterns along with pathogen biology.

Background Carbapenem-resistant bacteria are a major global public health threat, classified as critical priority pathogens by the WHO. In Indonesia, despite a national antimicrobial resistance control programme established by the Ministry of Health in 2015, resistance rates continue to rise, including increasing carbapenem resistance among clinically important bacteria. Strengthening approaches to directly interrupt transmission is essential, yet transmission pathways remain poorly understood with limited research and policy guidance within the Indonesian context. Methods and analysis The INTERCEPT study is a UK-Indonesia multidisciplinary collaboration aiming to identify transmission routes of carbapenem-resistant bacteria across healthcare and community settings, and the mechanisms of resistance gene transfer between bacteria and mobile genetic elementss. We will conduct genomic surveillance of hospital inpatients, healthcare workers, hospital environments, and surrounding communities, including wastewater systems, combined with genomic analyses and mathematical transmission modelling. A cohort of patients with bloodstream infections will be recruited to evaluate resistant bacteria, treatment practices, and clinical outcomes. Qualitative research will explore behavioural and system-level factors influencing transmission and intervention implementation. Findings will inform stakeholder workshops to co-design context-specific interventions, with pilot intervention over 9 months with pre- and post-intervention assessment to guide scalable strategies to reduce AMR transmission. Discussion The INTERCEPT study addresses carbapenem resistance in Indonesia using an integrated approach combining microbiological surveillance, genomics, modelling, and qualitative methods. Strengths include cross-sectoral analysis (patients, workers, environment) and participatory intervention design. Limitations include geographic scope restricted to Central Java, Indonesia.

Introduction Safe and timely blood availability remains a major global health challenge, especially in low- and middle-income countries. Digital tools may accelerate donor contact, but digital reachability alone does not ensure that people will notice, trust and act on urgent requests to support blood donation efforts. We examined factors associated with anticipated engagement in digitally coordinated urgent blood-donor mobilisation among digitally reachable adults in Ghana. Methods We conducted a cross-sectional online survey from September 2025 to January 2026 across Ghana's 16 regions. Participants were recruited via Facebook advertising and snowball sampling. Factors associated with urgent blood-donor mobilisability were assessed under four criteria: high future-donation willingness; high willingness to install a trusted donation app; high willingness to respond to a trusted urgent-request; and high practical flexibility to leave current activities. Descriptive analyses and multivariable logistic regression examined prevalence and associated factors. Results Among 1,067 participants, 577 (54.1%) met all four criteria. Future-donation willingness (91.8%), trusted-app installation willingness (83.2%) and trusted-request response willingness (82.7%) were common, whereas practical flexibility was lower (66.6%). In the adjusted model, high formal health-system trust (adjusted OR (AOR) 3.95, 95% CI 2.08-7.50), high digital-response readiness (AOR 2.26, 1.66-3.08), previous donation (AOR 1.47, 1.08-2.01), high donation knowledge (AOR 1.42, 1.03-1.97) and willingness to donate to strangers were positively associated with high mobilisability. Women (AOR 0.60, 0.43-0.83), participants reporting a work-schedule barrier (AOR 0.43, 0.29-0.66) and those travelling over 30 min to the nearest healthcare facility at night (AOR 0.66, 0.45-0.96) had lower adjusted odds. Conclusions Digital reachability and stated donation willingness may overestimate the population pool available for emergency donation. Digital blood-donor solutions should consider verifiable health-system requests, account for response readiness and current availability, and connect willing individuals with accessible collection options and transport support where needed.

Motivation: With the scaling frequency and intensity of extreme heat events across the globe, it is critical for public institutions to develop early detection systems and continuous monitoring of these events and their impacts. In Brazil, Rio de Janeiro was the first city to publish its heat protocol, with the Rio Heat Dashboard as a central component of this system. Implementation: The dashboard was implemented using R/Shiny and integrates climatic and health data from multiple sources. General features: The application comprises real-time heat exposure monitoring and automatic alert level classification, which is monitored daily by multiple municipal actors and supports activation of actions specified in the heat protocol. It also features a health impact module, which lists each heat event and its impact on mortality, and primary care and emergency visits. Availability: The source for full reproducibility is available through https://github.com/joaohmorais/RioHeatDashboard.

Background: The biological mechanism linking rainfall with leptospirosis transmission is well established, but rigorous quantitative evidence for the insular Caribbean remains scarce, limited mostly to descriptive reports of post-hurricane outbreaks. We aimed to quantify the association between rainfall and leptospirosis incidence in the Dominican Republic, where leptospirosis is endemic, between 2012 and 2026 using a distributed-lag approach. Methods: We conducted an ecological time-series study complemented by a province panel with fixed effects. Case data (5,412 valid cases) were obtained from the national surveillance system (SIP-0276FA51); rainfall data were obtained from 15 INDOMET rain gauge stations across 13 provinces (2000 to 2026). We calculated the cross-correlation function between lagged monthly rainfall (0 to 6 months) and case counts, fitted a negative binomial distributed-lag regression model (lags 0 to 3 months) adjusted for seasonality and trend, triangulated findings with a 13-province fixed-effects panel, compared four rainfall exposure metrics, assessed extreme-rainfall threshold sensitivity, and estimated the population attributable fraction (PAF) with a parametric bootstrap. Results: The rainfall-case association peaked at a 1-month lag (r = 0.551; 95 % CI 0.437-0.647; p < 0.001) and remained significant through 3 months. In the distributed-lag model, all four lags were independently significant, with the 1-month lag showing the strongest effect (incidence rate ratio [IRR] = 1.156 per additional 50mm; 95 % CI 1.090-1.226; p < 0.001). The province panel yielded an almost identical 1-month lag effect (IRR = 1.147; 95 % CI 1.127-1.167). Rainfall above the historical 90th percentile increased case risk the following month (rate ratio = 1.95), with effect magnitude increasing monotonically with threshold stringency. An estimated 28.2 % (95 % CI 19.0-36.6 %) of cases were attributable to rainfall above the recorded historical minimum. Conclusions: Rainfall is a robust, consistent predictor of leptospirosis incidence in the Dominican Republic, with the strongest association observed at a 1-month lag and a lag pattern broadly consistent with findings from distributed-lag studies in Thailand and the Philippines. These findings, which to our knowledge constitute the first formal quantification of this association for the insular Caribbean, provide an evidence base for rainfall-linked early-warning systems, with the strongest signal at approximately one month and elevated risk extending through three months after rainfall.

Diatoms are major contributors to marine primary production, yet current approaches for monitoring their abundance and function rely on coarse satellite chlorophyll estimates or sparse cell count and carbon fixation measurements. Molecular markers are a promising approach for high-resolution measurement of both abundance and metabolic activity through analysis of environmental DNA (eDNA) and RNA (eRNA). We present an isothermal quantitative recombinase polymerase amplification (qRPA) assay targeting rbcL gene copies and transcripts of marine diatoms, operating at low temperature and producing results in less than 15 min. We demonstrate specificity and calibration across diverse diatom taxa, then apply the assay to eDNA and eRNA samples from the Mare Chiara Long-Term Ecological Research site in the Bay of Naples, Italy, alongside microscopy, chlorophyll, physicochemical, and carbon-fixation data. Diatom rbcL DNA tracked abundance across five orders of magnitude despite seasonal shifts in community composition. Combining molecular and optical data revealed increased cellular rbcL copies and chlorophyll in low-light winter populations, suggesting enhanced photosynthetic capacity despite lower abundance. Furthermore, rbcL RNA reflected total carbon fixation rates and identified populations with differing carbon fixation activity. These results support rapid, RPA-based rbcL quantification as a robust approach for biomolecular ocean observing.

Eastern and southern Africa are highly affected by drought, and projections indicate that droughts will become more common in the coming decades. Whilst there has been research on the impact of drought on HIV, attributable to its effect on food insecurity and increased risky sexual behaviour, the link between drought and other sexually transmitted infections (STIs), particularly syphilis, remains largely unexplored. This study therefore assesses the association between drought and active syphilis, history of syphilis, and recovery from syphilis in Zambia, Uganda, and Tanzania, while examining disparities between urban and rural settings. It uses data on 75,225 people from Population-based HIV Impact Assessment surveys (2016-17), which include biomarker information, combined with rainfall data from the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) dataset to define drought in the two years prior to the survey. Multivariate logistic regression models with country-level fixed effects show that in urban areas, drought was associated with a significant increase in the probability of having active syphilis (average marginal effects (AME) = 0.5%, 95% confidence interval (CI): 0.2%-1.0%) and of having ever had syphilis (AME = 2%, 95% CI: 0.8%-4%). No significant association was found in rural areas. Exposure to drought was not associated with recovery from syphilis in either setting, though confidence intervals were wide. Our results underscore the importance of strengthening healthcare systems to make them more resilient to drought shocks in urban areas, and the need to reinforce syphilis prevention and treatment programmes in those areas when such shocks occur.

Antimicrobial resistance is a public health challenge, driving the need for rapid, cost-effective diagnostic support tools. Artificial intelligence (AI) may enable prediction of susceptibility to untested antibiotics from known susceptibility results, but prospective clinical validation is required before routine use. We evaluated an AI-based decision support method, trained on invasive isolates from the European Surveillance System (TESSy), for prediction of antibiotic susceptibility in clinical Escherichia coli urine isolates. The evaluation included 99 E. coli isolates from urine samples with diversity in age, sex, and antibiotic susceptibility. Predictions were evaluated for 14 antibiotics using patient metadata and susceptibility results for 4-8 antibiotics as input. Prediction uncertainty was handled using conformal prediction, allowing abstention when confidence was insufficient. EUCAST disk diffusion test results were used as reference and genomic sequence data was used to explore mechanisms of the AI performance. Without conformal prediction, 84% of predictions were correct when susceptibility results of six antibiotics were used to predict susceptibility to eight additional antibiotics. Across all predictions generated using susceptibility results for six antibiotics as input, the major and very major error rates were 19% and 12%, respectively. Prediction errors varied between antibiotics and were associated with certain phenotypic and genotypic resistance patterns. Conformal prediction reduced errors but increased abstentions; at confidence levels of 90%, 95%, and 97.5%, the model abstained in 9.6%, 14%, and 22% of instances. The method showed promising performance, but its clinical use remains limited and may require diagnostic data beyond susceptibility test results and demographic variables.

Public genomic repositories can support antimicrobial resistance (AMR) surveillance, but unequal sampling can bias interpretation. We characterised AMR determinants, multicountry genomic cluster overlap and surveillance gaps across Africa using an NCBI Pathogen Detection snapshot retrieved on 24 August 2026 for 55 African Union member states. Records were validated and deduplicated by BioSample, and complete AMRFinderPlus calls were summarised across five United Nations M49 subregions and eight overlapping regional economic communities (RECs). Country-pair cluster overlap was assessed using the Jaccard index, while project-based and composition-standardised sensitivity analyses evaluated repository bias. The dataset contained 86,829 unique BioSamples from 51 states; South Africa, Malawi and Kenya contributed 55.8%. Complete extended-spectrum {beta}-lactamase calls were detected in 21,513 isolates and carbapenemase calls in 4,642. blaCTX-M-15 dominated the ESBL profile, while NDM and OXA types predominated. Seventy clusters contained carbapenemase-positive isolates from at least two countries. A shared REC covered all participating countries in 38 clusters, while 32 crossed REC boundaries. Normalised country-pair overlap was low, with a maximum Jaccard index of 9.5%. Project balancing reduced the Northern African carbapenemase estimate from 32.3% to 17.9% and the Eastern African ESBL estimate from 36.9% to 12.5%. Public repositories identify determinants and clusters for investigation but do not estimate prevalence or transmission. AMR surveillance should combine national confirmation, regional institution-led investigation where countries share an REC, and continent-wide coordination through Africa CDC for cross-REC signals, supported by representative One Health sampling, standardised metadata and sustained African sequencing capacity.