PLOS Water

Background Bacteriological contamination of drinking water remains a major public health burden in sub-Saharan Africa, yet the full contamination chain from source to household has rarely been quantified at national scale. This study analyses water quality at both levels using the 2021 Cote d'Ivoire Demographic and Health Survey (DHS-CI 2021). Methods Cross-sectional secondary analysis of DHS-CI 2021 data. Households with paired bacteriological tests at the source (SH3227) and at the household (SH3225) were included (n = 2,541 for determinants; n = 2,528 for chain analysis). Contamination was defined as >0 CFU/100 ml. Determinants of source contamination were assessed by weighted logistic regression accounting for complex survey design. The contamination chain was described across four categories: safe throughout, recontaminated during transport/storage, decontaminated at home, and contaminated throughout. Results Weighted prevalence of source contamination was 63.6% [95% CI: 60.7-66.5%] and 77.0% [74.1-79.9%] at the household. Only 15.0% of households had safe water throughout the chain; 21.2% showed domestic recontamination and 60.8% consumed water contaminated at both levels. Key determinants of source contamination were use of an unimproved source (aOR = 8.15; 95% CI: 4.54-14.66), administrative region, travel time [≤]30 minutes (aOR = 1.92; 95% CI: 1.41-2.62), and higher wealth quintiles (protective; aOR = 0.25 for richest). Model discrimination was good (AUC = 0.809). Conclusions The vast majority of Ivorian households consume bacteriologically unsafe water, with domestic recontamination representing a distinct and significant degradation pathway even among users of improved sources. Dual interventions targeting source protection and safe household water storage are urgently needed to advance progress toward SDG 6 in Cote d'Ivoire.

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.

Women's disproportionate responsibility for unpaid domestic and care work, including water collection, remains a barrier to gender equality globally and may constrain women's ability to engage in income-generating activities. We compared women's and men's time use in rural Kenya and Honduras and assessed whether women's time spent on water collection and income-generating activities differed between communities that had or had not received an improved water source from World Vision. We also examined the measurement of time-use agency among women and men. In-person surveys were conducted in July-August 2024 with 95 participants (48 women, 47 men) in six Kenyan communities and 102 participants (53 women, 49 men) in six Honduran communities. Surveys included a 24-hour time-use recall module and items on time-use agency. Analyses compared time use by gender and by community intervention status (improved vs. not yet improved water supply), and confirmatory factor analysis assessed the validity of the time-use agency measure. Women in both study sites spent substantially more time than men on unpaid domestic and care work activities, including cooking, cleaning, laundry, and caregiving. In Kenya, women also spent significantly more time collecting water. Men spent more time sleeping (Kenya), on paid work (Honduras), unpaid agricultural work (both settings), and traveling (both settings). Across both countries, there were no significant differences between intervention and comparison communities in women's time spent on water collection or income-generating activities. In Kenya, most respondents reported high influence over their time, and six items showed strong validity for measuring instrumental time-use agency. Women's time burdens remained high even in communities that had received improved water sources, including at the household level. Our results suggest that more transformative water infrastructure, combined with interventions that address gendered social norms, may be needed to meaningfully reduce women's domestic work burden and support their economic empowerment.

Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.

Traditionally, studies have explored the impacts of individual water chemistry parameters on the persistence of Mycobacterium spp. and Legionella spp. in isolation with the underlying assumption that these associations are likely monotonic in nature. Yet chemical and microbiological changes are complex, and associations are likely highly combinatorial. In this study, we use interpretable machine learning models to disentangle the integrative and nonlinear associations between water chemistry and occurrence/abundance of Mycobacterium spp. and Legionella spp. Seasonal data from source water, point-of-entry and distribution systems of eight full-scale drinking water systems demonstrated that shifts in overall water chemistry were associated with the changes in microbial abundance during treatment and distribution. Machine learning models indicated moderate predictive ability of integrated water chemistry towards Legionella spp. abundance and towards the occurrence of both Legionella spp. and Mycobacterium spp., whereas predictive performance for Mycobacterium spp. abundance was limited. The association between nitrate and Legionella spp. abundance was disinfectant regimes dependent, while dissolved organic carbon exhibited a concentration dependent response type (i.e., positive and negative association). In chloraminated systems, Legionella spp. abundance was positively associated with ammonia and nitrate, highlighting the critical role of nitrification. Here, it appears that pH likely influences the initial colonization of Legionella spp. while ammonia governs its abundance in drinking water. Overall, this study demonstrates that integrated water chemistry and parameter-specific nonlinear effects collectively explain persistence of Mycobacterium spp. and Legionella spp. in drinking water systems. SynopsisThis study elucidates the integrative impact of water chemistry and the nonlinear responses of individual water chemistry parameters on the occurrence and abundance of Mycobacterium spp. and Legionella spp. in drinking water using interpretable machine learning. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/26351579v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@12334e4org.highwire.dtl.DTLVardef@65696borg.highwire.dtl.DTLVardef@1ec2452org.highwire.dtl.DTLVardef@44899b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Wastewater metagenomic sequencing (WW-MGS) enables simultaneous detection of hundreds of pathogens, but its use for quantitative pathogen tracking has not been robustly validated. Like wastewater PCR (WW-PCR), WW-MGS is affected by biases from variable fecal dilution and sample processing, but must additionally contend with the compositional structure of sequencing data, where a taxon's apparent abundance depends on the abundance of every other taxon in the sample. Simple summaries such as a pathogen's fraction of total reads may therefore be poorly suited to quantitative use. We retrospectively evaluated seven normalization approaches that attempt to control for these sources of bias against a baseline of total read relative abundance, using 1,425 samples from the CASPER consortium spanning 25 U.S. sites. Each approach was compared against WW-PCR and clinical data across eight total pathogens. Among the normalization strategies we evaluated, tobamovirus markers, diet-derived plant viruses abundant in human stool, performed best. Normalizing WW-MGS data by tobamovirus-genus counts improved median site concordance for 18 of 19 pathogen and comparison-source combinations. Gains were largest for year-round-circulating SARS-CoV-2 and norovirus and smaller for sharply seasonal pathogens such as influenza and respiratory syncytial virus, where baseline concordance was already high. Tobamovirus normalization rarely degraded concordance, with median gains roughly five times larger than median losses. Tobamovirus-normalized WW-MGS reached clinical concordance comparable to targeted WW-PCR, supporting its use as a quantitative trend-monitoring tool alongside pathogen-agnostic detection.

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

Effective filtration and concentration of stool specimens is an essential pre-analytical step for reducing fecal debris and improving organism recovery using microscopy-based ova and parasite (O&P) examination. This study evaluated three commercially available fecal sedimentation-based filtration/concentration systems, ParaPak SpinCon (Meridian Bioscience), Mini Parasep SF (Apacor), and the newly-available ParadeviceReingenuity), for qualitative parasite detection and workflow logistics using conventional and artificial intelligence (AI)-assisted microscopy. Forty clinical stool specimens (20 parasite-positive and 20 parasite-negative) were processed with the 3 devices, and the resultant 120 wet mount and 120 trichrome stained smear preparations were examined using conventional microscopy. Trichrome-stained slides were also scanned at 40x magnification using a Hamamatsu NanoZoomerS360 flatbed digital slide scanner and images were analyzed using the Techcyte Fusion Human Fecal Trichrome AI algorithm. Positive and indeterminate digital findings were confirmed by conventional glass slide microscopy. Slides and digital images were reviewed in a blinded manner. Concordance was assessed among the 360 initial evaluations (microscopy and AI-assisted), and discrepant parasitology results were resolved through re-review and specimen reprocessing as needed. Final qualitative agreement across slide/image evaluations using all three concentration systems was 100%. Minor discrepancies in protozoan and white/red blood cell detection/identification were noted in 5 and 7 cases, respectively, and likely reflected sampling and observer variability. While the three concentration systems produced equivalent qualitative results, the Paradevice and Mini Parasep SF offered the most streamlined workflows. These findings support the Paradevice and Mini Parasep SF as efficient, analytically equivalent systems that are compatible with traditional and AI-assisted O&P workflows.

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.

BackgroundCase-based infectious disease surveillance is subject to ascertainment bias when testing intensity varies across time and population subgroups. We previously developed a regression-based test adjustment methodology using Standardized Testing Ratios (STRs) to correct for differential testing patterns in COVID-19 surveillance data. Wastewater-based surveillance (WWS) measures viral burden in the community independently of diagnostic testing behavior, making it a valuable external validation tool for test-adjusted case estimates. MethodsWe analyzed 111 weeks of paired wastewater and case surveillance data from Ontario, Canada (July 19, 2020 to August 28, 2022). Wastewater SARS-CoV-2 signals from 107 sewersheds across 34 public health units were normalized within sewersheds and aggregated using population-weighted averages. We compared wastewater correlations with crude reported and test-adjusted case counts using Spearman rank correlations, linear regression, and negative binomial distributed lag nonlinear models (DLNM), stratified by epidemic period. ResultsTest-adjusted cases correlated substantially more strongly with wastewater signals than crude reported cases overall (Spearman {rho} = 0.849 vs. 0.679; linear R{superscript 2} = 0.609 vs. 0.191). The advantage of test adjustment was greatest during the Omicron wave, when population-level diagnostic testing contracted sharply following PCR eligibility restrictions ({rho} = 0.924 vs. 0.604; R{superscript 2} = 0.815 vs. 0.470). DLNM incorporating the wastewater signal explained substantially more variance in test-adjusted than crude reported cases (McFadden pseudo-R{superscript 2} 0.898 vs. 0.776), despite similar lag-response structure for both outcomes. ConclusionsWastewater surveillance provides compelling independent validation of a previously described test adjustment methodology for COVID-19 case surveillance. The agreement between wastewater signals and test-adjusted cases was strongest precisely when testing scarcity was most severe, supporting the use of test adjustment to recover accurate infection dynamics from case surveillance data during periods of changing testing access and policy.

BackgroundPseudomonas 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. AimThe aim of this study was to showcase the long-term survival and transmission of P. aeruginosa in a large tertiary childrens hospital in England which is crucial to develop strategies for water-safe care. MethodsEnvironmental P. aeruginosa isolates were collected from taps, sinks, showers, and baths in augmented care areas of a 330-bed tertiary childrens 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. FindingsThis retrospective study analysed nine-locus VNTR profiles of 457 P. aeruginosa isolates submitted to the UK Health Security Agency from a large tertiary childrens 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. ConclusionThese 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.

Metagenomic sequencing is increasingly applied to wastewater to characterize the diversity, dynamics, and relative abundance of human and animal viruses. Among these sequencing approaches are those that enrich viral nucleic acids from the wastewater matrix, aiming to increase the viral read fraction for analysis. However, the feasibility of scaling targeted viral sequencing to diverse sewersheds across large geographic scales is currently unknown. In this study, we apply hybrid capture metagenomic sequencing to nearly 450 weekly wastewater samples collected during the respiratory virus season in the United States and evaluate sequencing performance for generating public health-relevant data. Analysis of data from 15 wastewater treatment plants demonstrates that our approach enabled efficient capture of pathogens of interest, achieving a median viral read fraction over 19%. Importantly, relative abundance estimates of common pathogens correlated with direct quantification of viral targets using RT-ddPCR. Together, our results demonstrate that hybrid capture sequencing of wastewater is a viable tool to monitor both common and rare pathogens across geographically diverse sewersheds.

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.

Ballast water (BW) is an important vector for the global translocation of bacterial taxa, including pathogens. Legal frameworks establishing limits on the discharge of live organisms into recipient environments have been designed to reduce risks of microbial invasions, and understanding the impacts of BW management on bacterial communities is critical for assessing the effectiveness of these practices. Here we evaluate changes in bacterial communities associated with both BW treatment (BWT) and a combined management approach of BWT plus BW exchange (BWT+E). Samples were collected on two experimental voyages designed specifically to compare BW-associated biota before and after management. Microbial community structure and inferred function were assessed based on high throughput sequencing of 16S rRNA amplicons, and bacterial indicator taxa E. coli and enterococci were analyzed using targeted qPCR. As expected, both BWT alone and BWT+E dramatically changed bacterial communities, with the latter resulting in the largest overall decreases in bacterial diversity. Increases in Gammaproteobacteria, especially in the genus Pseudomonas, were particularly notable, with concomitant decreases in Alphaproteobacteria and Bacteroidia. Shifts in predicted bacterial function associated with BWT were similar for both voyages, despite significant differences in community structure, and may represent selection for r-strategists capable of active regrowth after BWT. qPCR estimates of indicator taxa were similar to those obtained through standard culture methods but may offer increased sensitivity for detecting changes associated with management. Our results indicate that BW management is effective at reducing bacterial communities but suggest that further research is needed to understand risks associated with taxa that may survive BWT.

BackgroundChildhood lead exposure is prevalent worldwide including low- and middle-income countries (LMICs). Structured screening and prevention programs to address pediatric lead exposure are largely absent in these settings. Adapted interventions are needed to close this implementation gap in an urban African context. This paper describes the protocol for the Lead Exposure Intervention Program (LEIP), which aims to adapt, pilot, and evaluate a pediatric lead exposure screening and risk-reduction protocol in Nairobi, Kenya. MethodsLEIP is a multi-phase, hybrid type 3 implementation-effectiveness study. Phase 1 is a formative one-arm study leveraging an existing mother-child cohort and stakeholder-led tools adaptation to pilot a program comprising blood lead level (BLL) screening with a lead risk survey and tailored caregiver risk reduction messaging. Phase 2 is a randomized trial in public sector clinics. In this phase, approximately 1,500 children will be screened to identify 100 with elevated BLL ([&ge;]5 {micro}g/dL) for enrollment, who will then be randomized 1:1 to receive either clinic-only risk-reduction messaging or the same clinic-based messaging plus a home visit for environmental assessment and additional tailored messaging. Follow-up at 3 and 9 months will assess caregiver recall of key messages and adoption of recommended exposure-reduction behaviors, as well as changes in child BLL. Phase 3 involves qualitative interviews with caregivers and key stakeholders to identify multi-level barriers and facilitators to intervention uptake. Quantitative and qualitative findings will be integrated to inform refinements for scale-up. DiscussionThis study represents a critical opportunity to develop and evaluate an adaptive, screening-based lead exposure intervention tailored to the urban LMIC context. By incorporating implementation science principles and stakeholder-driven design, LEIP is well-positioned to inform scalable national and regional approaches. The inclusion of both quantitative and qualitative components enhances the protocols ability to capture multilevel dynamics of uptake, fidelity, and sustainability, and generate actionable insights for future large-scale implementations. Trial RegistrationRegistered on ClinicalTrials.gov (NCT07401251)

1.We conducted field surveys over two consecutive years (2022 and 2023) of freshwater habitats in the Rio De La Concepcion (several tributaries and sites) and one site in the Rio Santa Cruz (tributary of the Gila River) in the state of Sonora, Mexico. Our primary goal was to detect the presence of the Rio Concepcion Topminnow (Poeciliopsis jackschultzi), an endangered microendemic livebearing desert fish whose external morphology is indistinguishable from several sympatric congeners. Using an environmental DNA (eDNA) metabarcoding approach ("MiFish" locus), we failed to detect evidence of P. jackschultzi, implying that it is extinct or present at abundances below our detection ability. Applying a collective evidence approach including visual/eDNA surveys and past records, we discuss the strengths and limitations of the eDNA metabarcoding approach. In the Rio De La Concepcion, we confirm the presence of the other known native and previously reported introduced teleosts, and reveal more recent introductions. In the Rio Santa Cruz site, we detect three putative non-natives (Asexual Hybrid Topminnow, Yaqui Sucker, and Mexican Roundtail Chub). We recommend further monitoring of habitats and fish taxa, and implementation of practices that improve groundwater recharge and the quality and quantity of treated wastewater in the study area.

BackgroundIn September 2021, the U.S. Centers for Disease Control and Prevention (CDC) implemented the Traveler-based Genomic Surveillance (TGS) program, a surveillance system that leverages genomic sequencing of samples from international air travelers and aviation wastewater for early detection of infectious threats. MethodsDuring September 2021-August 2024, nasal samples were collected anonymously from volunteer international travelers arriving at eight U.S. airports. During February 2023- August 2024, aviation wastewater samples were collected from arriving flights. Nasal samples were pooled and sent to a laboratory for RT-PCR testing. Genomic sequencing was conducted for SARS-CoV-2 and respiratory, gastrointestinal (wastewater), and other pathogens of public health importance. FindingsNasal samples from 694,798 travelers were grouped into 67,308 pools and tested; 13,990 (20.8%) were positive for SARS-CoV-2. Over 80% (400/495) of airplane and 96{middle dot}6% (422/437) triturator (a wastewater collection point from multiple airplanes) samples were positive for SARS-CoV-2. Sequence results were made publicly available a median of 11 days (IQR 10- 13 days) after sample collection. Predominant SARS-CoV-2 variants changed over time. Positive tests for influenza virus and respiratory syncytial virus were high in December/January, and gastrointestinal viruses were detected in wastewater during all months. Monitoring was scaled in response to reported outbreaks of COVID-19 and Mycoplasma pneumoniae in China and clade 1 monkeypox virus in central Africa. InterpretationTraveler nasal and aviation wastewater sampling can provide critical early detection of infectious pathogens before widespread U.S. community transmission. The TGS program provides a model for integrated traveler-based genomic surveillance. FundingCDC Research in ContextO_ST_ABSEvidence before this projectC_ST_ABSWe searched PubMed for relevant studies published during December 1, 2020-August 31, 2024, using the terms "traveler surveillance", "wastewater monitoring", "SARS-CoV-2 genomics", and "airport-based surveillance", without language restrictions. Previous reports have shown the feasibility of using travelers as sentinel populations for disease surveillance. Modeling studies have proposed integrating genomic data into international travel surveillance systems to enhance early pathogen detection, and evidence from Australia, Canada, and the UK suggests such programs could be scalable and effective. Early pandemic-era wastewater surveillance, particularly aviation wastewater, demonstrated that air travel hubs can be used to monitor pathogen importation. Prior efforts largely focused on SARS-CoV-2, with limited integration of multi-pathogen surveillance or side-by-side comparisons of nasal and wastewater surveillance modalities. A limited number of public health reviews have examined the broader implications of airport-based surveillance, including novel methods like airplane wastewater testing. However, empirical data on sustained, large-scale implementation of these models especially outside of regulatory or mandatory testing frameworks have been sparse. Added value of this projectThis is the first real-world implementation and scale-up of an anonymized, multi-pathogen traveler-based surveillance system across multiple U.S. international airports. We developed a scalable framework that integrated nasal swab testing, airplane and airport wastewater sampling, with genomic sequencing into a unified pathogen surveillance platform. Unlike prior efforts which primarily focused on SARS-CoV-2, this program captured respiratory and gastrointestinal viruses simultaneously and tracked genomic variation in near-real time. The program transitioned from a pilot to a multi-modality national surveillance system in under four years, engaging nearly 700,000 international travelers, and nearly 1000 aviation wastewater samples. Our findings demonstrate the feasibility of rapidly adapting this infrastructure for emerging threats and underscores the importance of sentinel surveillance in addressing global sequencing blind spots. Implications of all the available evidenceThe successful scale-up and real-time application of the TGS program illustrates that traveler-based surveillance can serve as a critical global early warning tool. Data generated from this program have filled gaps in global pathogen tracking, informed public health responses to outbreaks, and demonstrated that surveillance of international travelers can be achieved without mandatory testing. The scalability, speed, and adaptability of the program offer a viable model for global replication, especially as routine surveillance capacities decline. Our findings suggest that integration of multi-modal, voluntary traveler surveillance including sequencing and wastewater-based epidemiology should be considered a core component of pandemic preparedness and response frameworks worldwide.

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.

Fresh produce encounters pathogens at various stages of production and supply, with the harvesting process serving as one of these stages. To evaluate contamination associated with harvesting, we systematically swabbed zone 1 harvester surfaces and quantified Bacteroidales as a fecal biomarker using quantitative polymerase chain reaction (qPCR). Baseline contamination was dominated by non-detects, with occasional low-level detections (<25 copies/cm2) near the assay limit of detection (LoD). Detection occurred more frequently post-harvest (overall [~]4% pre-harvest and 10% post-harvest), while microbial loads remained low, indicating that harvesting primarily affected the likelihood of low-level contamination rather than increasing contamination abundance. Additionally, we developed and field-deployed a portable loop- mediated isothermal amplification (LAMP) assay for rapid harvester hygiene assessment and benchmarked its field performance against qPCR. Together, these results support a practical molecular tool for monitoring fecal contamination and informing cleaning and sanitization decisions.

Surface waters in urban watersheds receive episodic inputs of wastewater, runoff, and road-salt residues during spring, yet the contribution of these short hydrological windows to antibiotic resistance gene (ARG) loading remains poorly resolved. Weekly samples were collected from offshore and nearshore sites in the Detroit River, a Great Lakes transboundary connecting channel, from February to December 2025. Five clinically relevant ARGs encoding resistance to carbapenems, methicillin, and colistin, alongside the fecal marker pepper mild mottle virus (PMMoV), were quantified by qPCR and paired with ten conventional water-quality variables. blaNDM, mcr-1, and blaVIM-7 were not detected while blaKPC occurred as discrete pulses. One week (5 May) accounted for 37.2% of annual offshore blaKPC loading, and three weeks in late April to early May accounted for 72.8%, with peak concentrations reaching 5.4 x 10E3 and 7.2 x 10E3 copies/L. mecA was detected in nearly all samples without a dominant pulse. PMMoV normalization showed blaKPC did not vary seasonally (Kruskal-Wallis p = 0.198), consistent with diluted wastewater during spring precipitation events rather than an emergent source. mecA/PMMoV varied seasonally (p = 0.003) and was lowest in spring, implicating non-wastewater inputs in summer and autumn. Seven water-quality variables were significantly elevated during blaKPC pulse weeks. PCA distinguished pulse from background conditions, explaining 81.3% of variance. A random forest classifier achieved leave-one-out AUC of 0.917; ROC AUC reached 0.943 for total phosphorus, 0.924 for chloride, and 0.974 for the multivariate model. These results demonstrate that blaKPC and mecA operate through distinct source pathways and that routine water-quality monitoring can flag elevated blaKPC risk without additional sampling infrastructure.