PLOS Water

Women shoulder the majority of water collection labor globally, yet how their water collection and water-related work experiences may change over time or by water source type remains insufficiently understood. We conducted a longitudinal, mixed-methods study in rural Kenya and Honduras to understand how women's experiences collecting water and performing water-related work varied between (a) two time points, (b) improved and unimproved water source types, and (c) water source location. Data were collected in 2023 and 2024 using interviews, observation, GPS-enabled watches, and scales to measure time and distance traveled, water weight and volume carried, and calories expended. 133 women participated in data collection (66 Kenya, 67 Honduras). We compared women's experience data by time point (2023 vs. 2024), source type (improved vs. unimproved), and source location (off-premises vs. on-premises) (t-test, Mann-Whitney U test). We also mapped participants' routes and activities to show which sources were visited, when, and for what activities. In Kenya, mean water collection time, distance, and caloric expenditure were significantly lower and water volume was significantly higher in 2024 when there were unexpected rains compared to 2023 when there was a persistent drought. When comparing source types during the 2023 drought, journeys to improved sources took significantly less time and energy and covered less distance than journeys to unimproved sources. These differences were not observed during the rainy conditions of 2024 when unimproved sources were closer and more accessible. In Honduras, water collection and water work burdens did not differ significantly by time point or source type. We found women with on-premises water access to still expend considerable time and caloric expenditure engaging in water work within their household compounds. Findings from Kenya suggest that water infrastructure improvements can reduce women's water collection burdens, though benefits may depend on and vary by season and source location. Findings from Honduras show that water labor does not end once water is in the household. Rather, substantial time and energy are expended carrying out water-related work even when sources are on premises, suggesting that efforts to assess water labor need to extend beyond collection alone. To meaningfully reduce burdens and ensure improved water sources are utilized during all seasons, initiatives need to consider source location, seasonal variability, and work beyond collection. Evaluations to assess infrastructure impacts on women's labor and well-being are needed and long overdue.

Intermittent water supplies (IWS) serve >1 billion people globally and can transmit waterborne infections. How often and for how long supply is delivered varies between and within IWS systems. The UN Sustainable Development Goals target having water available when needed for >=12 hours/day or >=4 days/week but there are scarce data on how supply frequency/duration within IWS affect health outcomes. We conducted a matched study in Hubli-Dharwad, India, a city served partially by continuous water supply (CWS) since 2007 and partially by IWS. We enrolled 2220 CWS and 2218 IWS households matched on socioeconomics and sanitation. We compared diarrhea prevalence in children <5 years and typhoid fever incidence between households with different water supply characteristics using generalized linear models with robust standard errors and adjusting for socio-demographics and sanitation. Among IWS households, the median supply frequency was every 8 days (interquartile range [IQR]=7-8), and the median supply duration was 4 hours (IQR=3-5). IWS households had 36% higher prevalence of child diarrhea (prevalence ratio [PR]=1.36, 1.00-1.84) and 78% more typhoid fever cases (cumulative incidence ratio [CIR]=1.78, 1.05-3.02) than CWS households. IWS households meeting the UN criterion and those in the top quintiles of supply frequency and duration (receiving water once every 1-6 days or for 7-24 hours per supply cycle) had similar health outcomes as CWS households. IWS households below the UN criterion had higher diarrhea prevalence (PR=1.41, 1.03-1.93) and more typhoid fever cases (CIR=1.93, 1.15-3.22) than CWS households, as well as more typhoid fever cases than IWS households meeting the criterion (CIR=3.66, 1.37-9.79). IWS households in the bottom quintiles of supply frequency and duration (receiving water once every 9-15 days or for <=3 hours per supply cycle) had 45-72% higher child diarrhea prevalence and twice as many typhoid fever cases than CWS households (p-values<0.05). These findings support global efforts to implement CWS. Our results also highlight that increasing supply frequency and duration in IWS systems in the interim can deliver health benefits, and the UN criterion of having water available when needed improves health.

In low-income countries, ESBL-producing Escherichia coli (ESBL-EC) is frequently detected in humans, animals and household environments, indicating widespread exposure to antimicrobial resistance (AMR). Established risk factors such as antibiotic use do not explain the high community carriage of AMR in all settings; identifying the dominant exposure pathways can inform interventions against AMR. We aimed to investigate (i) animal-human-environment sharing of AMR by assessing associations between the abundance of ESBL-EC in the household environment, domestic animal feces and young children's stool and (ii) household factors associated with ESBL-EC abundance in these reservoirs. We enrolled 112 households from the CRADLE trial in rural Bangladesh. We enumerated ESBL-EC in drinking water, food, child hand rinses, outdoor soil, indoor floor swabs, chicken and cow feces, and stool from children aged 6 months. We recorded indicators of sanitation, animal ownership/management, human and animal antibiotic use, and child exposure behaviors using structured questionnaires and spot checks. The highest prevalence of ESBL-EC was in child stool (95.6%) and animal feces (82.3-96.9%), followed by soil (48.2%) and floors (36.6%); < 10% of food, child hands and drinking water harbored ESBL-EC. The abundance of ESBL-EC in child stool was not associated with its abundance in any sampled matrix; the abundance in chicken but not cow feces showed positive correlations with soil, floors, child hands, and drinking water (correlation coefficients: 0.19-0.39, p-values < 0.05). Higher-quality latrines (improved, pour-flush, with slab) were associated with lower ESBL-EC abundance across matrices; unsafe animal management (animals roaming or spending the night inside the home) was associated with higher abundance. Child antibiotic use and exposure behaviors (soil ingestion, time spent on floor) were not associated with ESBL-EC abundance in child stool. We observed high AMR colonization among young children and domestic animals in rural Bangladesh not explained by traditional fecal-oral exposure pathways. Future studies should explore additional pathways and assess whether sanitation and animal management improvements can reduce AMR.

Background: Helicobacter pylori is a major global pathogen with recognized potential for waterborne transmission. Intermittent water supply affects over one billion worldwide and may promote H. pylori contamination of municipal sources. Whether water supply discontinuity contributes to population-level H. pylori burden has not been examined globally. Materials and Methods: We conducted a cross-sectional ecological analysis of 79 countries with matched utility-level water infrastructure data and country-level H. pylori prevalence estimates from a published global meta-analysis. The primary exposure was continuity of water supply (hours/day). Secondary exposures included non-revenue water percentage (NRW %), pipe breaks per utility, and operating cost coverage ratio. Unadjusted and adjusted linear regression models with heteroscedasticity-consistent standard errors were estimated, controlling for basic sanitation coverage and log-transformed population density. A sensitivity analysis used a population-based measure of water availability on demand. Results: Greater water supply continuity was independently associated with lower H. pylori prevalence in both unadjusted ({beta} = -0.987, 95% CI -1.669 to -0.305, p = 0.005) and adjusted models ({beta} = -1.125, 95% CI -1.876 to -0.375, p = 0.004). Higher NRW % and lower operating cost coverage were each associated with higher H. pylori prevalence after adjustment. Pipe breaks were not significant in regression models though the Spearman correlation was in the expected direction. Sensitivity analysis produced consistent findings. Conclusion: IWS and broader water infrastructure deterioration are associated with higher H. pylori prevalence at the country level. These findings implicate water supply continuity as a potentially relevant environmental determinant of H. pylori transmission and suggest a role for water system investment within long-term gastric cancer prevention strategies.

Environmental surveillance for human pathogen detection is crucial for safeguarding public health; however, traditional approaches are often time-consuming, equipment-intensive and workflow-complex, delaying actionable public-health decision-making. The integration of a mobile laboratory (ML) with rapid bioinformatic analysis and interactive data visualization offers a novel approach to this surveillance. The ML workflows, with a focus on metagenomic sequencing and qPCR technologies, have been specifically designed to provide real-time information in detecting epidemiological threats in environmental samples. We have adopted a minimalist strategy, avoiding complex, expensive, and energy-intensive equipment that is challenging to maintain and transport, thereby reflecting a more sustainable approach. This study details the activities and outcomes of implementing such a ML in Tanzania. During one-month ML deployment, a total of 83 samples were sequenced using long-read metagenomic sequencing, and 70 samples were analyzed by Biomeme qPCR. The deployment enabled the detection of multiple bacterial, viral, and antimicrobial resistance targets in wastewater, drinking water, surface water, and soil samples providing valuable insights into the population epidemiological information relevant to the prevention of waterborne and zoonotic infections. In addition, the ML deployment provided a rare opportunity for knowledge transfer, actively engaged local researchers, and strengthened local epidemiological capacity. After the deployment, certificates of completion were issued to twenty-five scientists from four African countries (Tanzania, Burkina Faso, Democratic Republic of Congo, and Ethiopia) and post-deployment surveys were sent out to gather their feedback. Our findings highlight the importance of combining targeted qPCR assays with metagenomic sequencing for the proper interpretation, while acknowledging the risk of false-positive detections arising from low-abundance sequencing reads, particularly when using fast taxonomic classification tools such as kraken2. Given the hardware limitations inherent to ML deployments, metagenomic pathogen detection in this context should therefore be regarded primarily as a valuable screening tool rather than a definitive diagnostic method. These observations further underscore the need for more stringent and computationally demanding bioinformatic approaches when assessing high-priority pathogens. Complementary qPCR-based assays conducted within the ML can ensure equivalent robustness to those conducted in conventional laboratory settings. This innovative approach has the potential to significantly enhance detection capabilities and support timely public health responses in resource-limited settings.

Since the COVID-19 pandemic, wastewater-based surveillance (WBS) has emerged as a key approach to assess community-level health and the evolution of pathogens. To date, most established WBS systems focus on polymerase chain reaction (PCR) based detection and targeted sequencing of known pathogens because these approaches are well-accepted and include amplification of pathogen target sequences of interest thereby enabling lower limits of detection. Metagenomic next-generation sequencing (mNGS) is a promising approach to enable pathogen detection and surveillance beyond predefined pathogen lists, but its regular application to WBS has not been yet widely adopted because many key performance characteristics are not well-understood, including limit of detection (LOD) and false positive/negative rates. This paper describes a computational analysis to estimate the operational LOD of various sequencing approaches using a simplified model of a local wastewater (WW) system involving a military base. This paper also presents findings from two types of experiments: 1) laboratory-spiked, those for which Atlantibacter subterraneus (Asub) is introduced into real-world WW samples in a laboratory setting, and 2) system-spiked, those for which Asub is introduced at a source location of a real-world WW system. Findings indicate that mNGS detection performance varies with sequencing method and the data analysis process. In addition, findings indicate that site-specific method characterization should be used when implementing mNGS for WBS because sites can have different WW system configurations, background organisms and sequencing inhibitors.

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.

Summary Background: Wastewater and environmental surveillance (WES) enables community-level monitoring of infectious diseases. Most progress has focused on sewer-based surveillance, yet nearly half of the global population relies on non-sewered sanitation. In non-sewered settings, urban drainage channels have been used for poliovirus environmental surveillance, but their potential for a multi-pathogen WES with spatially defined catchments, and comparability to sewer-based surveillance, remains under-explored. Methods: Ten drainage channel sampling points with delineated micro-catchments (0.95-3.83 km2 with 12,885-44,146 people) were selected within Kampala. A total of 255 drainage channel and 54 wastewater treatment plant (WWTP) influent samples were collected during two campaigns in March and September-October 2025. A multi-target panel was quantified by digital PCR, including enteric viruses (Norovirus GI and GII, Rotavirus), respiratory viruses (SARS-CoV-2, Influenza A and B viruses, Respiratory Syncytial Virus (RSV)), non-O1/O139 Vibrio cholerae (V. cholerae), and Pepper Mild Mottle Virus (PMMoV) as a fecal indicator. Findings: Enteric viruses, non-O1/O139 V. cholerae, and PMMoV were consistently detected across all drainage channels and WWTP influents. Concentrations were generally lower in drainage than WWTP influents, except for non-O1/O139 V. cholerae. When normalized by PMMoV, concentrations across most drainage channels were comparable to WWTP influents, although comparability varied by target and location. Both concentrations and PMMoV-normalized concentrations varied across sampling locations. Trends between campaigns varied by pathogen target and were not explained by any single micro-catchment characteristic. Influenza A virus was the most frequently detected respiratory virus (8-23% in drainage channels; 3-10% in WWTP influents), while SARS-CoV-2, Influenza B, and RSV were rarely detected. Interpretation: PMMoV-normalized concentrations across most micro-catchments were comparable to WWTP influents, with spatial heterogeneity implying neighborhood-level differences in disease prevalence. Catchment-delineated drainage surveillance has potential to offer spatially resolved public health information in non-sewered settings comparable to sewer-based wastewater monitoring. Funding: Eawag Discretionary Funding

Wastewater-based epidemiology (WBE) has the potential to fill gaps in clinical surveillance for respiratory syncytial virus (RSV) burden. Previous studies have shown RSV to be detectable in wastewater, but few have linked detections to clinical data because, in many locations, RSV is not a reportable disease. Further, studies that have linked RSV in wastewater to clinical data have not distinguished between pediatric and adult infections, as is common in studies of RSV. Using 2,662 influent wastewater samples collected from twenty-four treatment plants in four New York counties, we measured the RSV concentration in wastewater and compared levels detected to RSV hospitalizations from September 2022 to July 2024. RSV concentrations in wastewater correlated well with RSV hospitalizations ({rho} between 0.52 and 0.85, P <0.001). RSV concentrations in wastewater lagged hospitalizations for under 10-year-olds by an average of three weeks but were a leading indicator for hospitalizations in patients over 50 by up to two weeks. In predictive models, wastewater explained 88 percent of the variance in RSV hospital admissions among people over 50. Wastewater-based epidemiology of RSV is therefore a reliable surveillance method and could provide early warning for increases in RSV hospitalizations among older populations.

The emergence of the novel monkeypox virus (MPXV) clade Ib in the Democratic Republic of the Congo (DRC) and neighboring countries in late 2023 highlighted the need for rapid, scalable surveillance approaches to support outbreak detection and response. As part of the ODIN-Mpox project, wastewater surveillance (WWS) systems were established as an emergency public health measure in three Sub-Saharan African countries (DRC, Tanzania, and Burkina Faso) to evaluate the feasibility of wastewater-based monitoring for mpox and strengthen local surveillance capacity. Between January 2025 and April 2026, 117 wastewater samples were collected from selected sites and analyzed for MPXV DNA using targeted qPCR assays. Clinical mpox data were obtained from national surveillance systems and WHO reports to assess epidemiological linkages between wastewater detections and reported infections. Six wastewater samples tested positive for MPXV DNA. During the study period, DRC experienced the highest disease burden, with weekly reported cases peaking at about 3,000 in January 2025, while Tanzania reported a peak of 20 weekly cases in March 2025. No confirmed clinical cases were reported in Burkina Faso. No clear relationship was observed between reported case numbers and qPCR Ct values in positive wastewater samples. Despite the low detection frequency, the project demonstrated the operational feasibility of implementing MPXV wastewater surveillance in resource-limited settings and established laboratory capacity for environmental monitoring of emerging infectious diseases. Given the early stage of WWS implementation in the region, the study identified opportunities for further system strengthening, including optimization of sample processing and reporting workflows, improved access to laboratory supplies, and enhanced integration of environmental and clinical surveillance data streams. These findings highlight the value of WWS as a complementary component of integrated public health surveillance systems and emphasize the need for continued investment in laboratory capacity, harmonized methodologies, governance frameworks, and knowledge exchange to enhance outbreak preparedness and response in low-resource settings.

Household environments in low-resource settings can become contaminated with fecal matter from multiple sources, including humans and domestic animals. Identifying the source of fecal contamination is critical for designing targeted interventions to reduce exposure to enteric pathogens, particularly for young children who bear the majority of the enteric disease burden. Using data from 140 households with children enrolled in the ECoMiD cohort study in northwestern coastal Ecuador, we (1) characterized source-specific fecal contamination in samples from household floors and maternal and child hands, and (2) identified animal-related and Water, Sanitation and Hygiene (WASH) conditions associated with the presence and concentrations of these markers. We used five qPCR-based microbial source tracking (MST) markers to detect fecal contamination from avian (GFD), canine (DG37), swine (Pig2Bac), ruminant (Rum2Bac), and human (HF183) sources. Prevalence ratios (PR) and mean differences comparing the presence/absence and concentration, respectively, of MST markers between households with and without each animal-related or WASH condition were estimated using generalized linear models with Poisson and Gaussian distributions. Animal MST markers tracked strongly with several animal-related conditions, whereas associations between the human MST marker and household demographic and WASH conditions were more limited. Animal ownership (PR 1.53; 95% CI: 1.04-2.26) was associated with higher prevalence of animal MST markers on floors. Households reporting animal feces indoors had higher prevalence of animal MST markers on floors (PR 1.84; 95% CI: 1.17-2.89), and higher concentrations of animal MST markers on child hands (mean difference 0.27 gene copies (gc)/m2; 95% CI: 0.12-0.41) and maternal hands (mean difference 0.10 gc/m2; CI: 0.02-0.18). Animal feces left unremoved outside the home were associated with higher prevalence of animal MST markers on maternal hands (PR 2.31; 95% CI: 1.11-4.81). Mothers reporting direct contact with animals had higher concentrations of animal MST markers on their children hands (mean difference 0.12 gc/m2; 95% CI: 0.02-0.21). Higher FECEZ scores, an overall metric for animal exposure, were associated with higher prevalence of animal MST markers on maternal hands (PR 2.94; 95% CI: 1.17-7.40). For human fecal contamination, the presence of E. coli on child hands was associated with higher prevalence of human MST markers on floors (PR 1.30; 95% CI: 1.00-1.68). Our findings reinforce household floors and maternal and child hands as key reservoirs of fecal contamination and point to future potential targets worth exploring for interventions in similar high-burden settings.

Freshwater ecosystems in Scotland are increasingly threatened by multiple interacting stressors, including pollution, hydrological alteration, land use change, and climate-driven pressures. Scotland's rivers are amongst the most physically diverse and dynamic in the UK, contributing significantly to the country-s economy and natural heritage. Monitoring 125,000 km of waterways presents an issue, with limited funding and capacity of environmental agencies creating an environmental monitoring deficit at a time when robust data are essential for delivering national and global biodiversity targets. Citizen science offers a scalable, community driven approach to strengthening environmental evidence. This study evaluates the development, implementation, and outcomes of Guardians of our Rivers (GooR), a nationwide citizen science programme using macroinvertebrate-based river health assessments based on the Anglers' Riverfly Monitoring Initiative (RMI) established by the Riverfly Partnership. Between 2022 and 2025, GooR trained more than 850 volunteers, established 123 monitoring sites across Scotland, and generated over 860 surveys-surpassing the previous 16 years of aquatic invertebrate monitoring efforts. Standardised field training, full equipment provision, and structured support enabled high-quality data collection across diverse catchments. The establishment of nationally applied trigger and target thresholds created a consistent mechanism for detecting ecological deterioration and ensured that verified trigger breaches (n = 39 in 2025) resulted in formal investigation or follow-up. Analysis of national abundance patterns revealed ecological and biogeographic trends across the eight RMI taxa, confirming data sensitivity to habitat differences, water quality, and regional pressures. A detailed case study of the Lothian Esk catchment demonstrated the programme's capacity to detect seasonal macroinvertebrate dynamics and site level ecological trajectories over time. Overall, GooR illustrates how well-designed and well-supported citizen science can deliver high resolution spatiotemporal datasets, enhance early warning systems, empower communities, and make a meaningful contribution to promoting river health. Importantly, GooR forged a working partnership with Scottish Environmental Protection Agency (SEPA) that allowed communities to not only gather data but also transformed the way citizen science is recognized as contributing to freshwater conservation. Continued investment and long-term support will be essential to sustain these gains and realise the full potential of citizen-driven freshwater stewardship.

Wastewater can be used to measure biomarkers that reflect population-level dietary intake and diversity; however, how this approach may apply in a low-income country remains a knowledge gap. This study aims to evaluate whether select dietary-related metabolites can be detected in wastewater and environmental surveillance (WES) samples from both sewered and non-sewered sanitation systems in Malawi, Africa. Fourteen WES samples were collected and analyzed from two university campuses in Mzuzu and Thyolo, Malawi. Four targets were analyzed: N-methyl-2-pyridone-5-carboxamide (2PY; a biomarker of vitamin B3), 4-pyridoxic acid (4-PA; a biomarker of vitamin B6), as well as enterodiol and enterolactone (biomarkers of dietary fiber and polyphenol consumption). An 18-question survey, paired spatiotemporally with the WES measurements, assessed self-reported daily dietary intake, food insecurity, and nutrient deficiency symptoms among 500 respondents. Among the 14 WES samples, 2PY, 4-PA, and enterolactone were detected, while enterodiol was not detected above the method limit (<0.3 mg/kg). Most respondents (79%; 397/500) reported consuming foods associated with the 2PY biomarker. Many respondents (62%; 311/500) also reported consuming foods linked to the 4-PA biomarker. Fewer respondents (36%; 181/500) reported consuming foods associated with enterodiol or enterolactone, such as whole grains (e.g., millet) and other fiber-rich plant foods (e.g., beans, chickpeas, or pigeon peas). This study demonstrates the potential feasibility of monitoring dietary-related metabolites in both sewered and non-sewered sanitation systems in a low-income country to augment community-level nutrition data. 2PY, 4-PA, and enterolactone were detectable in WES samples, supporting the advancement of this emerging field in nutrition and food security research.

Disagreement between molecular and culture-based assays for Legionella pneumophila detection is widely reported, yet comparisons have largely been based on direct assay-derived concentrations or binary positive/negative outcomes. However, it remains unclear whether molecular-culture disagreement reflects concentration-level incompatibility or unaccounted methodological and physiological differences related to DNA recovery and cell culturability. In this study, we observed substantial disagreement between molecular and Legiolert assays in source and finished drinking water samples collected from eight full-scale drinking water systems across the United States. Molecular thresholds adjusted for DNA recovery and cell culturability only partially resolved these discrepancies. We therefore developed a probabilistic Monte Carlo framework that incorporates sample-specific DNA recovery and cell culturability to evaluate the quantitative consistency of culturable L. pneumophila concentrations estimated by molecular and Legiolert assays. Quantitatively consistent and inconsistent samples occurred across both binary concordant and discordant classifications, demonstrating that positive/negative agreement poorly reflects concentration-level comparability. Overall, molecular and Legiolert assays showed strong quantitative consistency once sample-specific DNA recovery and cell culturability were considered. A small proportion of persistent inconsistencies at specific sampling sites, coupled with atypical microbial indicators, suggest that sample heterogeneity likely contributed to the remaining discrepancies. These findings demonstrate that integrating DNA recovery and cell culturability enhanced quantitative consistency between molecular and Legiolert assays and supports the use of molecular methods as rapid quantitative tools to complement culture-based L. pneumophila monitoring.

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.

Introduction: Climate change disproportionately affects disadvantaged communities, yet construction workforce education rarely addresses interconnected pathways linking energy efficiency, nature exposure, and public health. Green-blue infrastructure delivers co-optimized benefits: reducing building energy consumption 15-30% while decreasing heat-related mortality by approximately 3.9% per degree Celsius of urban cooling (Gasparrini et al., 2017) -- epidemiological benchmarks that inform the dose-response functions embedded in the Ecosystem Justice Translator (EJT). This protocol describes, to our knowledge, the first randomized controlled trial evaluating a curriculum intervention designed to develop planetary health competencies and environmental justice awareness among high school students pursuing construction careers. Methods and analysis: This two-arm, parallel-group randomized controlled trial targets enrollment of N=200 high school students (ages 14-18) from construction career pathway programs in the San Francisco Bay Area (over-recruitment target N=250; 25% buffer for attrition). Students are individually randomized 1:1 to intervention (Community-Centered Design curriculum integrating the Ecosystem Justice Translator) or control (traditional Virtual Design and Construction curriculum), stratified by school site using block randomization. The 6-month intervention features the Ecosystem Justice Translator (EJT) -- a computational system using large language models to translate community health equity concerns into quantifiable investment priorities. The EJT's 51-theme health equity taxonomy was derived from validated public health frameworks (Centers for Disease Control and Prevention [CDC] Social Vulnerability Index, Environmental Protection Agency [EPA] EJScreen, Healthy People 2030). Primary outcome is Health-Integrated Equity Consciousness Index (HI-ECI), measured at baseline, 3, 6 (primary endpoint), and 12 months. Analysis uses intention-to-treat linear mixed-effects models with random intercepts for participants. The minimum required sample (n=26 per arm; G*Power, two-tailed a=0.05, 80% power, Hedges' g=0.80) is exceeded by enrolled N=200, which provides >99% power at Hedges' g=0.80 and supports multi-site confirmatory factor analysis. Ethics and dissemination: This protocol has been approved by Stanford University Institutional Review Board (IRB eProtocol #84369, approved February 13, 2026). Parental consent from a parent or guardian and written assent from each student participant are required prior to enrollment. All instruments, curriculum materials, and EJT source code will be released open-source under CC BY-NC-SA 4.0, permitting free use for educational, research, and non-profit purposes, concurrent with primary publication. Commercial licensing may be pursued separately through Stanford University Office of Technology Licensing (OTL docket S25-565). Trial registration: ClinicalTrials.gov NCT07315919. Pre-results. Protocol version 4.0, June 2026.

Background Cholera remains a recurrent public health emergency in Zamfara State, northwestern Nigeria, where communities depend predominantly on untreated and poorly protected water sources. Environmental water bodies serve as reservoirs for Vibrio cholerae, sustaining transmission cycles between outbreaks. Despite the severity of recurrent outbreaks in the region, data on the molecular characteristics and serogroup distribution of V. cholerae across different drinking water source types in Zamfara State remain critically limited. Methodology/Principal Findings A cross-sectional environmental surveillance study was conducted between 13 October and 26 November 2025 across five cholera-affected Local Government Areas (LGAs) of Zamfara State: Gusau, Bungudu, Talata Mafara, Zurmi, and Shinkafi. A total of 142 water samples were collected from five source types -- rivers, boreholes, wells, tap water, and sachet water. Presumptive isolation was performed on Thiosulfate-Citrate-Bile Salts-Sucrose (TCBS) agar following alkaline peptone water enrichment. Fifty-five presumptive isolates underwent PCR-based molecular confirmation and serotyping using three gene targets: ompW (species confirmation, 588 bp), ctxA (O1 toxigenicity marker, 302 bp), and tcpA (O139 colonisation factor, 120 bp). Presumptive V. cholerae was recovered from 55 of 142 samples (38.7%; 95% CI: 30.5-47.3%), with well water recording the highest positivity rate (69.7%; 95% CI: 51.3-83.7%). A statistically significant association was observed between water source type and presumptive V. cholerae occurrence ({chi}2 = 23.11, df = 4, p < 0.001). Molecular analysis confirmed 29 isolates (52.7%; 95% CI: 39.2-66.0%) as V. cholerae, comprising 22 O1 serotypes (75.9%), one O139 serotype (3.4%), and six non-O1/non-O139 serotypes (20.7%). Toxigenic O1 strains were detected across all five LGAs and in all five water source types, including commercially packaged sachet water. The O139 serotype was identified in a single well-water isolate from Zurmi LGA, representing the first environmental detection of this serotype in Zamfara State. Conclusions/Significance The co-circulation of toxigenic O1, O139, and non-toxigenic non-O1/non-O139 V. cholerae serogroups across five distinct drinking water source types confirms that community water environments serve as genetically diverse reservoirs sustaining cholera transmission in Zamfara State. These findings underscore the urgent need for integrated water quality surveillance, sanitation infrastructure investment, and sustained molecular monitoring of environmental V. cholerae populations.

Karst groundwater supplies in Virginia are relied on to varying degrees for domestic, agricultural, and municipal water supplies. Further, Virginian caves harbor an estimated 200 endemic invertebrate species. The microbial occupants of Virginias karst aquifers are largely undescribed; characterizing them promises to inform both the scientific description of these systems and the management of a critical water resource. Karst aquifers are heterogeneous, and much of the water moving through them cannot be reached directly; we profiled cave waters both because cave passages offer direct access to active groundwater and because cave water specifically is relied upon by endemic invertebrate species living in caves. Using 16S rRNA sequencing, we characterized aquatic microbial communities in eight Virginia caves, across Virginias four major karst regions. We identified 3,899 unique amplicon sequence variants (ASVs) and found that caves hosted diverse microbial assemblages that differed markedly among sampled sites. These baseline data provide a starting point for future work to understand how seasonal cycles, weather events, and surface disturbances affect the microbial communities present in cave waters and the cave-endemic invertebrates that depend on these waters.

In this study, we analyze viral load data from wastewater treatment plants (WWTPs) across multiple U.S. states and address the challenge of selecting an optimal subset of sites to improve COVID-19 hospitalization forecasts. Using forward (greedy) regression with a baseline ARIMA model, we identify the most informative WWTPs that enhance forecast accuracy while reducing the number of sampling locations. Our analysis, based on NWSS data, shows that the optimal number of sites typically ranges from 2-8, though some states, including NY, IL, and WI, benefit from a larger set (10-20). We also leverage a Virginia-level digital twin model specifically designed for wastewater data modeling and analysis and our results show that for different parameter settings, that forecast accuracy can be achieved with strategically chosen small number of sites, providing

Mass gatherings pose significant public health risks by facilitating the spread of infectious diseases. While wastewater-based surveillance (WBS) has been widely used to monitor pathogens in high-income settings, its use as a practical, multi-pathogen surveillance tool during mass gatherings in low- and middle-income countries remains limited. This study aimed to assess the operational feasibility, epidemiological significance, and public health utility of multi-pathogen WBS during the African Nations Championship (CHAN) football tournament in Uganda. Wastewater surveillance was conducted at Mandela National Stadium during eight match days in August 2025. Moore swabs were deployed at 38 manholes receiving wastewater from different toilet facilities across the stadium to capture representative wastewater samples. Samples were processed using Nanotrap(R) microbiome virus particles to concentrate pathogens, followed by nucleic acid extraction. Samples were analyzed for multiple enteric and respiratory pathogens, including Mpox, using quantitative PCR (qPCR). Descriptive analyses were performed to characterize pathogen detection patterns, positivity rates, and temporal distribution across surveillance sites. A total of 304 wastewater samples were collected and analyzed, of which 259 (85.2%) tested positive for at least one pathogen. Multiple pathogens were consistently detected across sampling days, with enteric pathogens predominating, particularly Shigella spp. (53.6%), Rotavirus A (35.9%) and Enterovirus (32.2%). The mpox virus was also detected in a notable proportion of samples (28.6%) across several sampling days. Respiratory pathogens, including SARS-CoV-2 (11.8%) and Influenza B (8.2%), were identified intermittently at lower frequencies. Pathogen diversity varied over time, with up to eight pathogens detected on a single day, and co-detection of multiple pathogens observed in the majority of positive samples. Cq value distributions further demonstrated variability in detected signal patterns across pathogens. Surveillance findings informed real-time public health interventions, including sanitation reinforcement, intensified hygiene promotion, environmental disinfection, and targeted risk communication, strengthened syndromic surveillance with on-site triage, and targeted environmental health assessments of food handling and wastewater infrastructure. These findings demonstrate the operational feasibility and public health utility of integrating multi-pathogen wastewater-based surveillance into mass-gathering preparedness and response frameworks in low-resource settings. By capturing diverse pathogen signals and informing targeted interventions during the CHAN football tournament, WBS can provide actionable population-level insights that can support outbreak preparedness and response. Scaling WBS within national preparedness systems could strengthen epidemic intelligence, enhance early warning capacity, and support data-driven public health decision-making during future mass gatherings and emerging infectious disease threats.