Is detection of enteropathogens and human or animal faecal markers in the environment associated with subsequent child enteric infections and growth: an individual participant data meta-analysis.

BACKGROUND: Quantifying contributions of environmental faecal contamination to child diarrhoea and growth faltering can illuminate causal mechanisms behind modest health benefits in recent water, sanitation, and hygiene (WASH) trials. We aimed to assess associations between environmental detection of enteropathogens and human or animal microbial source tracking markers (MSTM) and subsequent child health outcomes. METHODS: In this individual participant data meta-analysis we searched we searched PubMed, Embase, CAB Direct Global Health, Agricultural and Environmental Science Database, Web of Science, and Scopus for WASH intervention studies with a prospective design and concurrent control that measured enteropathogens or MSTM in environmental samples, or both, and subsequently measured enteric infections, diarrhoea, or height-for-age Z-scores (HAZ) in children younger than 5 years. We excluded studies that only measured faecal indicator bacteria. The initial search was done on Jan 19, 2021, and updated on March 22, 2023. One reviewer (AM) screened abstracts, and two independent reviewers (AM and RT) examined the full texts of short-listed articles. All included studies include at least one author that also contributed as an author to the present Article. Our primary outcomes were the 7-day prevalence of caregiver-reported diarrhoea and HAZ in children. For specific enteropathogens in the environment, primary outcomes also included subsequent child infection with the same pathogen ascertained by stool testing. We estimated associations using covariate-adjusted regressions and pooled estimates across studies. FINDINGS: Data from nine published reports from five interventions studies, which included 8603 children (4302 girls and 4301 boys), were included in the meta-analysis. Environmental pathogen detection was associated with increased infection prevalence with the same pathogen and lower HAZ (ΔHAZ -0·09 [95% CI -0·17 to -0·01]) but not diarrhoea (prevalence ratio 1·22 [95% CI 0·95 to 1·58]), except during wet seasons. Detection of MSTM was not associated with diarrhoea (no pooled estimate) or HAZ (ΔHAZ -0·01 [-0·13 to 0·11] for human markers and ΔHAZ -0·02 [-0·24 to 0·21] for animal markers). Soil, children's hands, and stored drinking water were major transmission pathways. INTERPRETATION: Our findings support a causal chain from pathogens in the environment to infection to growth faltering, indicating that the lack of WASH intervention effects on child growth might stem from insufficient reductions in environmental pathogen prevalence. Studies measuring enteropathogens in the environment should subsequently measure the same pathogens in stool to further examine theories of change between WASH, faecal contamination, and health. Given that environmental pathogen detection was predictive of infection, programmes targeting specific pathogens (eg, vaccinations and elimination efforts) can environmentally monitor the pathogens of interest for population-level surveillance instead of collecting individual biospecimens. FUNDING: The Bill & Melinda Gates Foundation and the UK Foreign and Commonwealth Development Office.

Relating Antimicrobial Resistance and Virulence in Surface-Water E. coli.

The role of the environment in the emergence and spread of antimicrobial resistance (AMR) is being increasingly recognized, raising questions about the public health risks associated with environmental AMR. Yet, little is known about pathogenicity among resistant bacteria in environmental systems. Existing studies on the association between AMR and virulence are contradictory, as fitness costs and genetic co-occurrence can be opposing influences. Using Escherichia coli isolated from surface waters in eastern North Carolina, we compared virulence gene prevalence between isolates resistant and susceptible to antibiotics. We also compared the prevalence of isolates from sub-watersheds with or without commercial hog operations (CHOs). Isolates that had previously been evaluated for phenotypic AMR were paired by matching isolates resistant to any tested antibiotic with fully susceptible isolates from the same sample date and site, forming 87 pairs. These 174 isolates were evaluated by conventional PCR for seven virulence genes (bfp, fimH, cnf-1, STa (estA), EAST-1 (astA), eae, and hlyA). One gene, fimH, was found in 93.1% of isolates. Excluding fimH, at least one virulence gene was detected in 24.7% of isolates. Significant negative associations were found between resistance to at least one antibiotic and presence of at least one virulence gene, tetracycline resistance and presence of a virulence gene, resistance and STa presence, and tetracycline resistance and STa presence. No significant associations were found between CHO presence and virulence, though some sub-significant associations merit further study. This work builds our understanding of factors controlling AMR dissemination through the environment and potential health risks.

Identifying sources of antibiotic resistance genes in the environment using the microbial Find, Inform, and Test framework.

Introduction: Antimicrobial resistance (AMR) is an increasing public health concern for humans, animals, and the environment. However, the contributions of spatially distributed sources of AMR in the environment are not well defined. Methods: To identify the sources of environmental AMR, the novel microbial Find, Inform, and Test (FIT) model was applied to a panel of five antibiotic resistance-associated genes (ARGs), namely, erm(B), tet(W), qnrA, sul1, and intI1, quantified from riverbed sediment and surface water from a mixed-use region. Results: A one standard deviation increase in the modeled contributions of elevated AMR from bovine sources or land-applied waste sources [land application of biosolids, sludge, and industrial wastewater (i.e., food processing) and domestic (i.e., municipal and septage)] was associated with 34-80% and 33-77% increases in the relative abundances of the ARGs in riverbed sediment and surface water, respectively. Sources influenced environmental AMR at overland distances of up to 13 km. Discussion: Our study corroborates previous evidence of offsite migration of microbial pollution from bovine sources and newly suggests offsite migration from land-applied waste. With FIT, we estimated the distance-based influence range overland and downstream around sources to model the impact these sources may have on AMR at unsampled sites. This modeling supports targeted monitoring of AMR from sources for future exposure and risk mitigation efforts.

Greener residential environment is associated with increased bacterial diversity in outdoor ambient air.

In urban areas, exposure to greenspace has been found to be beneficial to human health. The biodiversity hypothesis proposed that exposure to diverse ambient microbes in greener areas may be one pathway leading to health benefits such as improved immune system functioning, reduced systemic inflammation, and ultimately reduced morbidity and mortality. Previous studies observed differences in ambient outdoor bacterial diversity between areas of high and low vegetated land cover but didn't focus on residential environments which are important to human health. This research examined the relationship between vegetated land and tree cover near residence and outdoor ambient air bacterial diversity and composition. We used a filter and pump system to collect ambient bacteria samples outside residences in the Raleigh-Durham-Chapel Hill metropolitan area and identified bacteria by 16S rRNA amplicon sequencing. Geospatial quantification of total vegetated land or tree cover was conducted within 500 m of each residence. Shannon's diversity index and weighted UniFrac distances were calculated to measure α (within-sample) and ß (between-sample) diversity, respectively. Linear regression for α-diversity and permutational analysis of variance (PERMANOVA) for ß-diversity were used to model relationships between vegetated land and tree cover and bacterial diversity. Data analysis included 73 ambient air samples collected near 69 residences. Analysis of ß-diversity demonstrated differences in ambient air microbiome composition between areas of high and low vegetated land (p = 0.03) and tree cover (p = 0.07). These relationships remained consistent among quintiles of vegetated land (p = 0.03) and tree cover (p = 0.008) and continuous measures of vegetated land (p = 0.03) and tree cover (p = 0.03). Increased vegetated land and tree cover were also associated with increased ambient microbiome α-diversity (p = 0.06 and p = 0.03, respectively). To our knowledge, this is the first study to demonstrate associations between vegetated land and tree cover and the ambient air microbiome's diversity and composition in the residential ecosystem.

Detection of SARS-CoV-2 RNA in wastewater and comparison to COVID-19 cases in two sewersheds, North Carolina, USA.

Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may be useful for monitoring population-wide coronavirus disease 2019 (COVID-19) infections, especially given asymptomatic infections and limitations in diagnostic testing. We aimed to detect SARS-CoV-2 RNA in wastewater and compare viral concentrations to COVID-19 case numbers in the respective counties and sewersheds. Influent 24-hour composite wastewater samples were collected from July to December 2020 from two municipal wastewater treatment plants serving different population sizes in Orange and Chatham Counties in North Carolina. After a concentration step via HA filtration, SARS-CoV-2 RNA was detected and quantified by reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) and quantitative PCR (RT-qPCR), targeting the N1 and N2 nucleocapsid genes. SARS-CoV-2 RNA was detected by RT-ddPCR in 100 % (24/24) and 79 % (19/24) of influent wastewater samples from the larger and smaller plants, respectively. In comparison, viral RNA was detected by RT-qPCR in 41.7 % (10/24) and 8.3 % (2/24) of samples from the larger and smaller plants, respectively. Positivity rates and method agreement further increased for the RT-qPCR assay when samples with positive signals below the limit of detection were counted as positive. The wastewater data from the larger plant generally correlated (⍴ ~0.5, p < 0.05) with, and even anticipated, the trends in reported COVID-19 cases, with a notable spike in measured viral RNA preceding a spike in cases when students returned to a college campus in the Orange County sewershed. Correlations were generally higher when using estimates of sewershed-level case data rather than county-level data. This work supports use of wastewater surveillance for tracking COVID-19 disease trends, especially in identifying spikes in cases. Wastewater-based epidemiology can be a valuable resource for tracking disease trends, allocating resources, and evaluating policy in the fight against current and future pandemics.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework.

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovine-dense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.

Identifying bioaugmentation candidates for bioremediation of polycyclic aromatic hydrocarbons in contaminated estuarine sediment of the Elizabeth River, VA, USA.

Estuarine sediments near former creosoting facilities along the Elizabeth River (Virginia, USA) are contaminated by polycyclic aromatic hydrocarbons (PAHs). In this study, we interrogated the bacterial community of the Elizabeth River with both culture-based and culture-independent methods to identify potential candidates for bioremediation of these contaminants. DNA-based stable isotope probing (SIP) experiments with phenanthrene and fluoranthene using sediment from the former Republic Creosoting site identified relevant PAH-degrading bacteria within the Azoarcus, Hydrogenophaga, and Croceicoccus genera. Targeted cultivation of PAH-degrading bacteria from the same site recovered 6 PAH-degrading strains, including one strain highly similar to Hydrogenophaga sequences detected in SIP experiments. Other isolates were most similar to organisms within the Novosphingobium, Sphingobium, Stenotrophomonas, and Alcaligenes genera. Lastly, we performed 16S rRNA gene amplicon microbiome analyses of sediment samples from four sites, including Republic Creosoting, with varying concentrations of PAHs. Analysis of these data showed a striking divergence of the microbial community at the highly contaminated Republic Creosoting site from less contaminated sites with the enrichment of several bacterial clades including those affiliated with the Pseudomonas genus. Sequences within the microbiome libraries similar to SIP-derived sequences were generally found at high relative abundance, while the Croceicoccus sequence was present at low to moderate relative abundance. These results suggest that Azoarcus and Hydrogenophaga strains might be good target candidates for biostimulation, while Croceicoccus spp. might be good targets for bioaugmentation in these sediments. Furthermore, this study demonstrates the value of culture-based and culture-independent methods in identifying promising bacterial candidates for use in a precision bioremediation scheme. KEY POINTS: • This study highlights the importance of using multiple strategies to identify promising bacterial candidates for use in a precision bioremediation scheme. • We used both selective cultivation techniques and DNA-based stable isotope probing to identify bacterial degraders of prominent PAHs at a historically contaminated site in the Elizabeth River, VA, USA. • Azoarcus and Hydrogenophaga strains might be good target candidates for biostimulation in Elizabeth River sediments, while Croceicoccus spp. might be good targets for bioaugmentation.

Impacts of an Urban Sanitation Intervention on Fecal Indicators and the Prevalence of Human Fecal Contamination in Mozambique.

Fecal source tracking (FST) may be useful to assess pathways of fecal contamination in domestic environments and to estimate the impacts of water, sanitation, and hygiene (WASH) interventions in low-income settings. We measured two nonspecific and two human-associated fecal indicators in water, soil, and surfaces before and after a shared latrine intervention from low-income households in Maputo, Mozambique, participating in the Maputo Sanitation (MapSan) trial. Up to a quarter of households were impacted by human fecal contamination, but trends were unaffected by improvements to shared sanitation facilities. The intervention reduced Escherichia coli gene concentrations in soil but did not impact culturable E. coli or the prevalence of human FST markers in a difference-in-differences analysis. Using a novel Bayesian hierarchical modeling approach to account for human marker diagnostic sensitivity and specificity, we revealed a high amount of uncertainty associated with human FST measurements and intervention effect estimates. The field of microbial source tracking would benefit from adding measures of diagnostic accuracy to better interpret findings, particularly when FST analyses convey insufficient information for robust inference. With improved measures, FST could help identify dominant pathways of human and animal fecal contamination in communities and guide the implementation of effective interventions to safeguard health.

Microbial Find, Inform, and Test Model for Identifying Spatially Distributed Contamination Sources: Framework Foundation and Demonstration of Ruminant Bacteroides Abundance in River Sediments.

Microbial pollution in rivers poses known ecological and health risks, yet causal and mechanistic linkages to sources remain difficult to establish. Host-associated microbial source tracking (MST) markers help to assess the microbial risks by linking hosts to contamination but do not identify the source locations. Land-use regression (LUR) models have been used to screen the source locations using spatial predictors but could be improved by characterizing transport (i.e., hauling, decay overland, and downstream). We introduce the microbial Find, Inform, and Test (FIT) framework, which expands previous LUR approaches and develops novel spatial predictor models to characterize the transported contributions. We applied FIT to characterize the sources of BoBac, a ruminant Bacteroides MST marker, quantified in riverbed sediment samples from Kewaunee County, Wisconsin. A 1 standard deviation increase in contributions from land-applied manure hauled from animal feeding operations (AFOs) was associated with a 77% (p-value <0.05) increase in the relative abundance of ruminant Bacteroides (BoBac-copies-per-16S-rRNA-copies) in the sediment. This is the first work finding an association between the upstream land-applied manure and the offsite bovine-associated fecal markers. These findings have implications for the sediment as a reservoir for microbial pollution associated with AFOs (e.g., pathogens and antibiotic-resistant bacteria). This framework and application advance statistical analysis in MST and water quality modeling more broadly.

Occurrence of male-specific and somatic coliphages and relationship with rainfall in privately-owned wells from peri­urban and rural households.

Privately-owned drinking water wells serving fewer than 25 people (private wells) are prevalent and understudied across most of the US. Private wells primarily serve rural households located outside of municipal drinking water and sewerage service coverage areas. These wells are not regulated by United States Environmental Protection Agency (EPA) under the Safe Drinking Water Act, are not regularly monitored by any public agency or utility, and generally do not undergo disinfection treatment. Coliphages are a group of viruses that infect coliform bacteria and are useful viral surrogates for fecal contamination in water systems in much the same way that fecal indicator bacteria (FIB), such as E. coli and to a lesser extent total coliforms, are used to quantify fecal contamination. Coliphages are approved by the EPA for regulatory monitoring in groundwater wells in the USA, but are not routinely used for this purpose. The present study characterizes the occurrence of male-specific and somatic coliphages, along with FIB, in private wells (n = 122) across two different counties in North Carolina. While occurrences of E. coli were rare and frequency of total coliform was generally low (~20%), male-specific and somatic coliphages were detectable in 66% and 54% of samples, respectively. Concentrations of male-specific coliphages were higher than somatics at each county and on a monthly basis. Rainfall appears to be partly influencing higher coliphage concentrations in December, January and February. This research underscores the need for increased surveillance in private wells and consideration of using coliphages in order to better characterize occurrence of fecal contamination at the time of sampling, especially during rainier months.

Transmission of Antimicrobial-Resistant Staphylococcus aureus Clonal Complex 9 between Pigs and Humans, United States.

Transmission of livestock-associated Staphylococcus aureus clonal complex 9 (LA-SA CC9) between pigs raised on industrial hog operations (IHOs) and humans in the United States is poorly understood. We analyzed whole-genome sequences from 32 international S. aureus CC9 isolates and 49 LA-SA CC9 isolates from IHO pigs and humans who work on or live near IHOs in 10 pig-producing counties in North Carolina, USA. Bioinformatic analysis of sequence data from the 81 isolates demonstrated 3 major LA-SA CC9 clades. North Carolina isolates all fell within a single clade (C3). High-resolution phylogenetic analysis of C3 revealed 2 subclades of intermingled IHO pig and human isolates differing by 0-34 single-nucleotide polymorphisms. Our findings suggest that LA-SA CC9 from pigs and humans share a common source and provide evidence of transmission of antimicrobial-resistant LA-SA CC9 between IHO pigs and humans who work on or live near IHOs in North Carolina.

Antibiotic Resistance in Recreational Waters: State of the Science.

Ambient recreational waters can act as both recipients and natural reservoirs for antimicrobial resistant (AMR) bacteria and antimicrobial resistant genes (ARGs), where they may persist and replicate. Contact with AMR bacteria and ARGs potentially puts recreators at risk, which can thus decrease their ability to fight infections. A variety of point and nonpoint sources, including contaminated wastewater effluents, runoff from animal feeding operations, and sewer overflow events, can contribute to environmental loading of AMR bacteria and ARGs. The overall goal of this article is to provide the state of the science related to recreational exposure and AMR, which has been an area of increasing interest. Specific objectives of the review include (1) a description of potential sources of antibiotics, AMR bacteria, and ARGs in recreational waters, as documented in the available literature; (2) a discussion of what is known about human recreational exposures to AMR bacteria and ARGs, using findings from health studies and exposure assessments; and (3) identification of knowledge gaps and future research needs. To better understand the dynamics related to AMR and associated recreational water risks, future research should focus on source contribution, fate and transport-across treatment and in the environment; human health risk assessment; and standardized methods.

Human Cytomegalovirus Infections Are Associated With Elevated Biomarkers of Vascular Injury.

Background: Human cytomegalovirus (HCMV) infects ~50% of adults in the United States. HCMV infections may cause vascular inflammation leading to cardiovascular disease, but the existing evidence is inconsistent. Objective: We investigated demographic predictors of HCMV infection and explored associations between HCMV infection status, the intensity of anti-HCMV Immunoglobulin G (IgG) antibody response, and biomarkers of inflammation and endothelial function which are known predictors of cardiovascular disease. Methods: We conducted a cross-sectional study of 694 adults residing in the Raleigh-Durham-Chapel Hill, NC metropolitan area. Serum samples were tested for IgG antibody response to HCMV, and for biomarkers of vascular injury including soluble intercellular adhesion molecule 1 (sICAM-1), soluble vascular cell adhesion molecule 1 (sVCAM-1), C-reactive protein (CRP), and serum amyloid A (SAA). Associations between HCMV and biomarker levels were analyzed using two approaches with HCMV serostatus modeled as a binary variable and as an ordinal variable with five categories comprised of seronegative individuals and quartiles of anti-HCMV antibody responses in seropositive individuals. Results: HCMV seroprevalence in the study population was 56%. Increased body mass index, increased age, female gender, racial/ethnic minority status, and current smoking were significantly associated with HCMV seropositivity in a multivariate regression analysis. HCMV seropositivity was also associated with 9% (95% confidence interval 4-15%) and 20% (0.3-44%) increases in median levels of sICAM-1 and CRP, respectively, after adjusting for covariates. The association between HCMV seropositivity and median levels of sVCAM-1 and SAA were positive but not statistically significant. Significant positive associations were observed between the intensity of anti-HCMV IgG responses and levels of sICAM-1 and sVCAM-1 (p-values 0.0008 and 0.04 for linear trend, respectively). To our knowledge, this is the first epidemiological study to show a relationship between anti-HCMV IgG responses and vascular injury biomarkers sICAM-1 and sVCAM-1 in the general population. Conclusion: HCMV infections are associated with vascular injury and inflammation biomarkers in adult residents of North Carolina.

Microbial Indicators of Fecal Pollution: Recent Progress and Challenges in Assessing Water Quality.

PURPOSE OF REVIEW: Fecal contamination of water is a major public health concern. This review summarizes recent developments and advancements in water quality indicators of fecal contamination. RECENT FINDINGS: This review highlights a number of trends. First, fecal indicators continue to be a valuable tool to assess water quality and have expanded to include indicators able to detect sources of fecal contamination in water. Second, molecular methods, particularly PCR-based methods, have advanced considerably in their selected targets and rigor, but have added complexity that may prohibit adoption for routine monitoring activities at this time. Third, risk modeling is beginning to better connect indicators and human health risks, with the accuracy of assessments currently tied to the timing and conditions where risk is measured. Research has advanced although challenges remain for the effective use of both traditional and alternative fecal indicators for risk characterization, source attribution and apportionment, and impact evaluation.

Risk of Antibiotic-Resistant Staphylococcus aureus Dispersion from Hog Farms: A Critical Review.

The World Health Organization has declared antibiotic resistance "one of the biggest threats to global health." Mounting evidence suggests that antibiotic use in industrial-scale hog farming is contributing to the spread of antibiotic-resistant Staphylococcus aureus. To capture available evidence on these risks, we searched peer-reviewed studies published before June 2017 and conducted a meta-analysis of these studies' estimates of the prevalence of swine-associated, antibiotic-resistant S. aureus in animals, humans, and the environment. The 166 relevant studies revealed consistent evidence of livestock-associated methicillin-resistant S. aureus (MRSA) in hog herds (55.3%) raised with antibiotics. MRSA prevalence was also substantial in slaughterhouse pigs (30.4%), industrial hog operation workers (24.4%), and veterinarians (16.8%). The prevalence of swine-associated, multidrug-resistant S. aureus (MDRSA)-with resistance to three or more antibiotics-is not as well documented. Nonetheless, sufficient studies were available to estimate MDRSA pooled prevalence in conventional hog operation workers (15.0%), workers' household members (13.0%), and community members (5.37%). Evidence also suggests that antibiotic-resistant S. aureus can be present in air, soil, water, and household surface samples gathered in or near high-intensity hog operations. An important caveat is that prevalence estimates for humans reflect colonization, not active infection, and the health risks of colonization remain poorly understood. In addition, these pooled results may not represent risks in specific locations, due to wide geographic variation. Nonetheless, these results underscore the need for additional preventive action to stem the spread of antibiotic-resistant pathogens from livestock operations and a streamlined reporting system to track this risk.

The challenge of achieving safely managed drinking water supply on San Cristobal island, Galápagos.

Achievement of United Nations Sustainable Development Goal 6.1 centers on the availability of a safely managed drinking water source for all. However, meeting the criteria for this goal is challenging on island systems and elsewhere with limited freshwater supplies. We measured microbial and chemical water quality over three years on San Cristobal Island, Galapagos, an island with limited freshwater supply, necessitating use of cisterns or roof tanks to ensure water availability in households. Our results showed that the municipal water treatment plants generally produced high quality drinking water but detection of Escherichia coli in 2-30% of post-treatment distribution samples suggests contamination and/or regrowth during distribution and storage. Linear regression revealed a modest, negative relationship between residual chlorine and microbial concentrations in drinking water samples, while 24-h antecedent rainfall only slightly increased microbial counts. Taken together, our results underscore the challenge of providing a safely managed drinking water source where limited freshwater quantities result in intermittent flow and require storage at the household level. Efforts to meet sustainable development goals for island systems will likely need to consider water availability for any treatment technologies or programs aimed at meeting water quality goals.

Human fecal contamination of water, soil, and surfaces in households sharing poor-quality sanitation facilities in Maputo, Mozambique.

Identifying the origin of fecal contamination can support more effective interventions to interrupt enteric pathogen transmission. Microbial source tracking (MST) assays may help to identify environmental routes of pathogen transmission although these assays have performed poorly in highly contaminated domestic settings, highlighting the importance of both diagnostic validation and understanding the context-specific ecological, physical, and sociodemographic factors driving the spread of fecal contamination. We assessed fecal contamination of compounds (clusters of 2-10 households that share sanitation facilities) in low-income neighborhoods of urban Maputo, Mozambique, using a set of MST assays that were validated with animal stool and latrine sludge from study compounds. We sampled five environmental compartments involved in fecal microbe transmission and exposure: compound water source, household stored water and food preparation surfaces, and soil from the entrance to the compound latrine and the entrances to each household. Each sample was analyzed by culture for the general fecal indicator Escherichia coli (cEC) and by real-time PCR for the E. coli molecular marker EC23S857, human-associated markers HF183/BacR287 and Mnif, and GFD, an avian-associated marker. We collected 366 samples from 94 households in 58 compounds. At least one microbial target (indicator organism or marker gene) was detected in 96% of samples (353/366), with both E. coli targets present in the majority of samples (78%). Human targets were frequently detected in soils (59%) and occasionally in stored water (17%) but seldom in source water or on food surfaces. The avian target GFD was rarely detected in any sample type but was most common in soils (4%). To identify risk factors of fecal contamination, we estimated associations with sociodemographic, meteorological, and physical sample characteristics for each microbial target and sample type combination using Bayesian censored regression for target concentration responses and Bayesian logistic regression for target detection status. Associations with risk factors were generally weak and often differed in direction between different targets and sample types, though relationships were somewhat more consistent for physical sample characteristics. Wet soils were associated with elevated concentrations of cEC and EC23S857 and odds of detecting HF183. Water storage container characteristics that expose the contents to potential contact with hands and other objects were weakly associated with human target detection. Our results describe a setting impacted by pervasive domestic fecal contamination, including from human sources, that was largely disconnected from the observed variation in socioeconomic and sanitary conditions. This pattern suggests that in such highly contaminated settings, transformational changes to the community environment may be required before meaningful impacts on fecal contamination can be realized.

Tracking Major Sources of Water Contamination Using Machine Learning.

Current microbial source tracking techniques that rely on grab samples analyzed by individual endpoint assays are inadequate to explain microbial sources across space and time. Modeling and predicting host sources of microbial contamination could add a useful tool for watershed management. In this study, we tested and evaluated machine learning models to predict the major sources of microbial contamination in a watershed. We examined the relationship between microbial sources, land cover, weather, and hydrologic variables in a watershed in Northern California, United States. Six models, including K-nearest neighbors (KNN), Naïve Bayes, Support vector machine (SVM), simple neural network (NN), Random Forest, and XGBoost, were built to predict major microbial sources using land cover, weather and hydrologic variables. The results showed that these models successfully predicted microbial sources classified into two categories (human and non-human), with the average accuracy ranging from 69% (Naïve Bayes) to 88% (XGBoost). The area under curve (AUC) of the receiver operating characteristic (ROC) illustrated XGBoost had the best performance (average AUC = 0.88), followed by Random Forest (average AUC = 0.84), and KNN (average AUC = 0.74). The importance index obtained from Random Forest indicated that precipitation and temperature were the two most important factors to predict the dominant microbial source. These results suggest that machine learning models, particularly XGBoost, can predict the dominant sources of microbial contamination based on the relationship of microbial contaminants with daily weather and land cover, providing a powerful tool to understand microbial sources in water.

Drinking water improvements and rates of urinary and gastrointestinal infections in Galápagos, Ecuador: Assessing household and community factors.

OBJECTIVES: The Galápagos provides an important setting to investigate the health impacts of a new drinking water treatment plant (DWTP) in a limited resource environment. We examine how household perceptions and practices affect the relationship between water quality and infections before and after DWTP. METHODS: Ethnographic data and self-reported infections were collected from 121 mothers and 168 children ages 2 to 10 from Isla San Cristóbal. Household tap water samples were tested for levels of fecal contamination. Community level infection rates were estimated using discharge records from the Ministry of Public Health. The effects of the new DWTP and fecal contamination levels on infections were tested using logistic and Poisson models. RESULTS: Perceptions of water quality and household practices influenced exposures to contaminated tap water. We found minimal change in drinking water sources with 85% of mothers sampled before the DWTP and 83% sampled after using bottled water, while >85% from the pooled sample used tap water for cooking and hygiene practices. The DWTP opening was associated with lower odds of fecal contamination in tap water, reported urinary infections, and community level rates of urinary and gastrointestinal infections. The household practice of recently washing the cistern contributed to higher contamination levels after the DWTP opened. CONCLUSIONS: To ensure access to clean water, public health works need to consider how household perceptions and practices influence tap water use and quality, in addition to infrastructure improvements. Exposures to contaminated tap water contribute to the burden of infectious disease in environments with inadequate water infrastructure.