In low- and middle-income countries (LMICs), enteric infections and diarrheal diseases among children are widespread due to insufficient water, sanitation, and hygiene (WASH) infrastructure. Children may be exposed to enteric pathogens by ingesting soil contaminated with feces. Although previous research has detected elevated levels of fecal indicator bacteria and enteric pathogen genes in soils, no studies have yet used quantitative microbial risk assessment (QMRA) to assess the potential effect of rainfall on child enteric infections and the potential disease burden via this pathway. We collected a total of 144 soil samples between May and December 2024 in Kibera, Kenya, both before and within an hour after rainfall events from household entrances, compounds, and toilet entrances. Over 70% of soil samples were E. coli positive, with mean concentrations ranging from 51.5 MPN/g of dry soil (SD: 46.1) pre-rainfall to 39.3 MPN/g of dry soil (SD: 45.7) post-rainfall. The reduction was marginally significant (p = 0.058, Kruskal-Wallis test). A one-way ANOVA revealed no statistically significant difference in E. coli levels across sampling locations (p = 0.943) and across latrine types (urine diverting, hanging, pit latrine, and septic tank) (p = 0.46). Using QMRA with soil ingestion parameters specific to children under five years in LMIC settings and locally derived indicator-pathogen ratios for soils, we estimated annual infections and diarrheal disease burden in disability-adjusted life years (DALYs) per person per year. We estimated an annual infection risk of 100% for adenovirus, irrespective of rainfall events. Following rainfall, median annual infection risks attributable to soil ingestion were an estimated 1 in 2 for Campylobacter jejuni, 1 in 31 for Shigella spp., and 1 in 33 for Vibrio cholerae. These findings highlight the potential importance of soil ingestion as an exposure pathway, and point to the need for sanitation improvements to limit the migration of enteric pathogens to soils near living environments.

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

INTRODUCTION:Rural sanitation deficits in the USA represent an important source of non-point source pollution and may present risks to public health. We propose a controlled, before-and-after (CBA) study using a difference-in-differences analysis to measure the effect of a town-wide sanitation expansion programme on the release of pathogens to the environment. This work is expected to yield valuable insight into the potential for rural sanitation improvements to reduce pathogen releases and support public health and well-being. METHODS:We will conduct a CBA study including quantitative measurement of key enteric pathogens and faecal indicator bacteria adjacent to 30 households lacking adequate sanitation. As households connect to a new sewerage system serving the entire community, longitudinal household sampling will continue until crossover is complete. We will include 10 concurrent control sites with existing appropriate sanitation as well as 10 control sites never receiving the intervention to monitor secular trends in pathogen releases during the study period. ANALYSIS:We will compare the concentration of culturable Escherichia coli in the environment preintervention and postintervention between intervention and control groups. We will use the preintervention values of culturable E. coli in the environment to adjust the effect size for differences between the groups at baseline. We will couple pathogen measurements with quantitative microbial risk assessment to estimate the potential effect of the intervention on infection risks via key exposure pathways. A linked pre-post survey will focus on self-reported quality of life measures among households connecting to the system. ETHICS AND DISSEMINATION:Informed consent will be obtained prior to data collection, with participants informed of study details and risks. Participation is completely voluntary, and identifiable data will be securely and separately stored from all other data. Each household will be offered a summary of their site-specific data. Deidentified results will be shared with the community in a public forum and published in peer-reviewed journals. This study was approved by the Institutional Review Board for Human Subjects Research (IRB) at the University of North Carolina at Chapel Hill (IRB #24-0665).

Hospital-acquired infections driven by ESKAPEE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli) are highly prevalent. Premise plumbing, sinks and drains, disseminates these organisms into patient environments via aerosolization and subsequent surface contamination. We measured viable ESKAPEE pathogens and overall microbial communities in and around sinks in two high-burden hospitals in La Paz, Bolivia, using culture and 16S rDNA sequencing. In a prospective observational study (May-August 2025), we collected 233 surface swabs and 39 air samples across four sink-related surface categories and in room air. Samples were plated on selective media for ESKAPEE identification and quantified as colony-forming units (cfu) normalized to 100 cm2 or 6000 L. DNA was extracted, and the full 16S rDNA gene was sequenced on PacBio Revio, analysed via DADA2/QIIME2 and R. We detected viable presumptive ESKAPEE pathogens in 74.7% of surface swabs and 74.4% of air samples. Sink basins were most contaminated (mean 31 cfu/100 cm2, 95 % CI16-46); concentrations declined with distance from the drain. Klebsiella and Enterobacter spp. showed the highest mean concentration across samples; S. aureus was most frequently detected (54.4% of samples). Hospital-specific differences were evident in culture positivity (hospital A 85% vs hospital B 66.9%) and community composition (PERMANOVA P = 0.001; sample location explained 21.9% vs 11.7% of variation). 16S profiling confirmed elevated relative abundances of Klebsiella, Enterococcus, and Enterobacter in basins relative to distant surfaces and air. The hospitals studied had high levels of ESKAPEE pathogens, underscoring the need for control measures.

This Perspective calls for a transdisciplinary framework for the responsible advancement of Microbiome Engineering of the Built Environment (MEoBE). Acknowledging MEoBE's potential to improve public health, we highlight the need for early core practices and principles incorporating societal and ethical considerations. We propose integrating Responsible Research and Innovation (AIRR: anticipation, inclusion, responsiveness, reflexivity) with the National Academy of Medicine's Committee on Emerging Science, Technology, and Innovation (CESTI) principles. Although full integration requires further conceptual development, aligning these frameworks offers novel value. We argue that open dialogue and addressing risks with impacted communities will build public trust and ensure MEoBE benefits society. Ultimately, we support a responsible innovation approach that fosters ongoing engagement and adaptation while upholding core principles of justice, fairness, autonomy, and individual and collective good.

Healthcare Associated Infections (HAIs) pose a significant public health risk. Hospital sinks and associated plumbing are one likely source. This study investigates bioaerosol emissions from sink P-traps during faucet operation to assess their potential role in pathogen transmission in the hospital context. We designed an aerosol chamber system with adjustable air change rate and a functioning sink meeting hospital standards. We quantified bioaerosol and large droplet emission factors from the sink, using Escherichia coli F-amp as a model for Enterobacteriaceae such as Klebsiella pneumoniae. We cultured Andersen Cascade Impactor and BioSpot sampler aerosol samples and deposition plates using MI agar, which is selective for E. coli. Across five experiments, deposition plate counts were substantial, while air samples were close to detection limits. We estimated bioaerosol emissions factors of 1.3 & times; 10(-10) to 1.9 & times; 10(-10) CFU emitted per CFU in P-trap for aerosol particles less than 5.0 mu m in diameter. The large droplet emission factor was one order of magnitude larger, at 4.3 & times; 10(-9) +/- 2.8 & times; 10(-9) CFU per CFU. To demonstrate the application of the measured emissions data, we predicted Klebsiella pneumoniae inhalation dose (0.78 to 1.12 CFU day(-1)) and inhalation infection probability (similar to 10(-5)) for 5.5 day hospital stay with colonized plumbing (air change rate 6 h(-1)). This translates to similar to 1 infection per year for a hospital with a severe plumbing system colonization affecting similar to 2000 continuously occupied rooms. For pathogens with different dose response curves, we demonstrate how infection probability via inhalation depends on dose response.

Many rural communities in Alabama's Black Belt region lack adequate sanitation, resulting in wastewater discharges that may pose risks to residents. To understand the scope of the problem in one community, we conducted three cross-sectional surveys in a small town with limited sanitation infrastructure in 2023. We measured a range of enteric pathogens in environmental samples by multi-parallel qPCR as well as fecal indicator bacteria E. coli and Enterococcus by culture and molecular methods. We examined soil samples (n = 58) from sites near failing septic systems or suspected direct surface discharges and comparison soil (n = 10) far from potential discharges to estimate sanitation-related pathogen hazards. We examined surface water samples from community (n = 8) and localized (n = 20) sites that may have been impacted by wastewater discharges. Comparing impacted and unimpacted soil samples revealed greater fecal contamination near known or suspected discharges, compared with control samples. The mean culturable E. coli count in impacted soils was 224 MPN/g (95% CI 0-510.5 MPN/g) and in unimpacted soils was 0.5 MPN/g (95% CI 0-1.5 MPN/g). We detected several pathogens via qPCR in impacted soil and surface water, including Acanthamoeba spp., Balantidium coli, Blastocystis spp., Cryptosporidium spp., and rotavirus. In community-level surface waters, 88% of samples were positive for E. coli by culture (n = 8, mean 3.04 x 105, 95% CI 0-8.96 x 105 MPN/100 mL); 100% were positive for Enterococcus by culture (n = 4, mean 1.10 x 104, 95% CI 0-2.55 x 104 MPN/100 mL); and we detected Acanthamoeba spp., Blastocystis spp., Cryptosporidium spp., Plesiomonas shigelloides., rotavirus, and Yersinia enterocolitica, suggesting community-level wastewater discharges may degrade local surface water quality. Evidence suggests sanitation failures contribute to enteric pathogen hazards in this community.

Wastewater surveillance has been widely adopted since the COVID-19 pandemic, but non-sewered (e.g., onsite) sanitation is a common form of sanitation in cities of low- and middle-income countries. Environmental surveillance in these settings requires alternatives to wastewater. We collected 81 soil samples adjacent to public waste bins inside the sewered and non-sewered areas of Maputo and a 150-meter-wide buffer zone between the two areas, as well as from subsistence farms near the wastewater treatment plant for comparison. We cultured Escherichia coli (E. coli) and determined the prevalence of 29 unique enteric pathogens via RT-qPCR. E. coli concentrations were significantly higher (p < .001) in soils adjacent to public waste bins (mean = 5.1x105 per gram) compared to soils from farms (mean = 8.7x101 per gram). The mean number of unique pathogens was higher in soils from the non-sewered area (mean = 7.9, n = 32 samples) and the 150-meter buffer area (mean = 11, n = 10) compared to the sewered area (mean = 4.6, n = 20) and soils from farms (mean = 3.8, n = 19). Findings demonstrate that the presence of enteric pathogens in soils adjacent to public waste bins were associated with neighborhood sanitation infrastructure. In high-burden settings with poor sanitation, direct examination of soils and other environmental matrices are potentially scalable means of environmental pathogen surveillance to consider beyond conventional matrices.

Healthcare-associated infections (HAIs) are a known and growing problem worldwide, including those caused by ESKAPEE pathogens: Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter spp., and Escherichia coli. Far-UVC is a novel disinfection method that inactivates pathogenic microbes in air and on surfaces, but is safe for use in occupied spaces. We will implement a multi-site, double-blinded, clustered randomized controlled trial (cRCT) in two hospitals with a high burden of ESKAPEE pathogens. Intervention spaces will receive functioning far-UVC lamps and control arm spaces will receive visually identical lamps that do not emit UV light (shams), randomly allocated to 10 sites per arm per hospital. We will collect environmental samples (air and surface swabs) and measure ESKAPEE pathogens via culture and sequencing in longitudinal monitoring. We hypothesize that the prevalence of ESKAPEE pathogens on intervention site surfaces will be reduced, compared with control arm surfaces.

ABSTRACT Digital PCR (dPCR) is increasingly used for wastewater surveillance due to its precision, absolute quantification, and reduced sensitivity to inhibition compared to quantitative PCR (qPCR). Although the Bio-Rad QX200 and QIAGEN QIAcuity dPCR platforms are widely adopted, their performance has not been directly compared for wastewater applications. We conducted a blinded comparison of these platforms using 93 archived wastewater influent samples from North Carolina collected in 2021–2022, spanning three orders of magnitude in SARS-CoV-2 concentration (1 × 103–5 × 105 copies L−1). Samples were stratified into low, medium, and high concentration bins and analyzed in triplicate for N1 and N2 gene targets and a bovine coronavirus processing control. Both platforms demonstrated statistically equivalent quantification across all targets, with mean differences ≤0.12 log copies L−1 (R2 > 0.93). Coefficients of variation were similar (3.96%–7.61%), with no significant differences across concentration bins except for N2 in the low bin (difference: 0.87 percentage points). Measurement variability correlated strongly with wastewater treatment plant site (R2 = 0.89) rather than platform, indicating that sample matrix characteristics drive precision more than the analytical platform. Process limits of detection ranged from 2,160 to 2,680 copies L−1 for Bio-Rad QX200 and 5,650–9,700 copies L−1 for QIAGEN QIAcuity for N1 and N2, respectively. The Bio-Rad QX200 platform processed samples 32% faster (305 vs 435 minutes per 96 wells), while QIAGEN QIAcuity offered 29% lower consumables cost ($4.68 vs $6.11 per well). These findings support the interchangeable use of both platforms for wastewater surveillance, with platform selection based on laboratory-specific operational needs.IMPORTANCEAs wastewater-based epidemiology transitions from emergency response to sustained public health infrastructure, standardized molecular methods are essential for reliable data integration across surveillance networks. This study provides the first blinded comparison of two dPCR platforms widely deployed for wastewater pathogen surveillance in the United States. We demonstrate quantitative equivalence between Bio-Rad QX200 and QIAGEN QIAcuity platforms across three orders of magnitude in viral concentration, establishing that data from both platforms can be interpreted interchangeably for public health decision-making. This platform equivalence is critical as national surveillance systems aggregate data from diverse laboratories and as monitoring expands beyond SARS-CoV-2 to encompass additional respiratory viruses, antimicrobial resistance genes, and emerging pathogens. Our findings provide a methodological foundation for multi-platform surveillance networks and demonstrate that measurement variability is driven primarily by sample matrix characteristics rather than analytical platform choice.

Malfunctioning sanitation systems can increase fecal contamination and exposure risks during rainfall, yet rapid methods for assessing system performance remain limited. This study evaluated sanitation system performance in low-income urban areas of Nairobi, Kenya, usingEscherichia coli as a fecal indicator and fluorescent tracer dye to assess excreta flow. We collected 144 soil and 48 open drain water samples before and after rainfall and tested them forE. coli A fluorescent dye was introduced into sanitation systems to track leakage into surrounding environments.E. coli was detected in 75% of samples, with mean concentrations of 47 Most Probable Number per gram (MPN/g) in facility entrance soil, 45 MPN/g at household entryways, 44 MPN/g in compound soil, and 90 MPN/100 mL in open drains. Concentrations were lower immediately after rainfall, although the difference was not statistically significant (p = 0.097). Dye was detected outside sanitation systems in 56% of cases, rising to 78% following rainfall. Detection varied by system type: 83% of pit latrines, 50% of septic systems, and all direct discharge systems showed evidence of leakage. These findings reveal frequent containment failures and highlight the value of tracer dyes for identifying contamination pathways and informing targeted public health interventions.

Although wastewater surveillance for assessing community health and well-being is now mainstream, most cities in low- and middle-income countries lack conventional wastewater services. In these settings, environmental surveillance beyond conventional wastewater offers the potential to inform public health responses, design interventions intended to reduce exposures, and to evaluate infection control programs. To explore these potential use cases, we measured pathogens, source-tracking markers, and fecal indicator bacteria in wastewater treatment plant (WWTP) influent and effluent, wastewater surface discharges, impacted river water, impacted soils, open drains, stormwater, and fecal sludges from onsite sanitation in Maputo, Mozambique. We detected a wide range of pathogens by multi-parallel RT-qPCR across all matrices, revealing a nuanced picture of pathogen flows in the city and suggesting the potential for exposures beyond those typically included in studies of sanitation and health. We developed a regression model with multiple pathogens as the dependent variable and observed lower pathogen concentrations in direct wastewater discharges (mean difference -1.4 log10 per liter, 95% CI: -1.7, -1.1), WWTP effluent (-0.97 log10, 95% CI: -1.5, -0.47), water from open drains (-2.0 log10, 95% CI: -2.5, -1.6), impacted river water (-3.0 log10, 95% CI: -3.7, -2.4), and stormwater (-4.7 log10, 95% CI: -7.0, -3.3) compared to WWTP influent. We further observed that a one standard deviation increase in 7-day cumulative precipitation was associated with an increase in the pathogen concentration in all matrices (0.11 log10, [0.04, 0.19]). Despite lower concentrations of pathogens in matrices compared to WWTP influent, frequent detection of pathogens indicates clear potential to use environmental pathogen surveillance to inform public health responses in cities lacking universal conventional wastewater, with a wide range of promising applications.

Escherichia coli causes diarrhea in children and can be transmitted from animals. Characterizing the scope of human-animal strain sharing is crucial for assessing potential health risks; however, conventional methods that assess single isolates are resource-intensive and lack sensitivity. Strain-level metagenomic analyses can reveal within-host strain diversity and between-host strain sharing. In this study, we aimed to determine whether E. coli strains we previously detected among chickens in Mozambique might pose meaningful risks to local children. To achieve this, we compared E. coli strains in chicken metagenomes to E. coli strains reported by others in children's stool in the same community during the same period (2014-2022) using the Strain Genome Explorer toolkit. At least one E. coli strain was shared between 37/23,937 (0.15%) chicken-human pairs. This approach represents a novel method for assessing the scope of bacterial strain sharing between human and animal populations within a community.

Safe drinking water is critical for public health, yet microbial contamination remains a significant global challenge. We conducted a systematic review to update World Health Organization guidance on water disinfection technologies by synthesizing peer-reviewed literature from 1997 to 2021 on the performance of free chlorine, chlorine dioxide, ozone, and ultraviolet (UV) light against bacteria, viruses, and protozoa. Following PRISMA guidelines, we analyzed log10 reduction values (LRVs) and contact times (Ct) or fluence (for UV) from laboratory and field studies. We included studies from multiple databases and expert-recommended studies. Results show mean Cts for 2 LRV of non-opportunistic bacteria as 6.0 (free chlorine), 0.4 (chlorine dioxide), and 1.2 (ozone) mg/L*min, and a mean UV fluence of 8.2 mJ/cm² (all bacteria). Viruses required lower Cts, except for UV-resistant adenoviruses, while protozoa required higher Cts or fluences. Opportunistic bacteria required significantly higher Cts than non-opportunistic bacteria for free chlorine and chlorine dioxide. Temperature and pH effects were inconsistent, highlighting data variability and gaps in field studies. These findings support global guidance on water treatment and may be used alongside other context-specific data to understand the roles these technologies play in reducing waterborne exposures. We recommend standardized reporting from performance studies to enable straightforward synthesis of evidence.

While nearly three-quarters of the globe use safely managed drinking water services, water quality can deteriorate between the point of service provision and point of consumption due to intermittent supply and the need to store water at the household level. To test if water storage contributes to waterborne pathogen hazards, we estimated prevalence and concentration of enteric pathogens in piped and stored drinking water samples in Beira, Mozambique, using large-volume sampling methods. We assessed water sample concentrates for microbial contamination from bacterial, protozoan, viral, helminthic, antimicrobial resistance (AMR), and microbial source tracking targets with RT-qPCR using a custom TaqMan Array Card. We found that enteric pathogens, AMR targets, and human mtDNA were more prevalent in stored drinking water compared to household tap water. We also detected enteric pathogens— including Cryptosporidium, Giardia, pathogenic Escherichia coli, and rotavirus— directly from 13% (11/87) of piped sources connected to a well-managed, but intermittent, water supply system, albeit less frequently than in stored water. These findings suggest that without continuity in service delivery combined with effective filtration treatment in piped supplies and safe storage microbial contamination of drinking water at the point of use may continue to occur.

Enteric pathogen transmission is influenced by seasonality and meteorological conditions, yet pathogen-specific dynamics are not well understood. We investigated the relationships between (1) season, (2) heavy rainfall events, and (3) temperature and enteric pathogen infections among 12-month-old children in a low-income, urban setting. We analyzed household data and stool samples from 630 participants enrolled in the PAASIM Study in Beira, Mozambique (February 2022-November 2023) and applied generalized estimating equations with robust standard errors (modified Poisson for binary outcomes and linear regression for continuous outcomes). During the rainy season, compared to the dry season, we found a 34% lower prevalence of protozoan infections [aPR: 0.66; 95% CI: (0.51,0.86)], an 11% lower prevalence of co-infections [aPR: 0.89; 95% CI: (0.78,1.00)], and lower total number of concurrent infections per individual [ab: -0.17; 95% CI: (-0.38,0.04)], as well as relationships with some individual pathogens. Following heavy rainfall events (1-week lag), there was a 30% higher prevalence of protozoan infections [aPR: 1.30; 95% CI: (1.06,1.59)], a 22% higher prevalence of viral infections [aPR: 1.22; 95% CI: (0.95,1.57)], and a 10% higher prevalence of co-infections [aPR: 1.09; 95% CI: (0.99,1.21)]. Temperatures above the median (1-week lag), compared to below the median, were associated with a 35% lower prevalence of protozoan infections [aPR: 0.65; 95% CI: (0.49,0.86)] and a 14% lower prevalence of co-infections [aPR: 0.86; 95% CI: (0.76,0.97)]. Our results contrast many previous studies that have predominately shown a higher risk of bacterial infections and a lower risk of viral infection during periods with higher temperatures and precipitation but align with previous research suggesting a higher prevalence of some enteric infections following heavy rainfall events. Both long-term seasonal trends in enteric infections as well as the more immediate effects of extreme weather events, including heavy rainfall events, are important considerations for designing interventions.