Safe Today, Unsafe Tomorrow: Tanzanian Households Experience Variability in Drinking Water Quality.

Measuring Escherichia coli in a single-grab sample of stored drinking water is often used to characterize drinking water quality. However, if water quality exhibits variability temporally, then one-time measurement schemes may be insufficient to adequately characterize the quality of water that people consume. This study uses longitudinal data collected from 193 households in peri-urban Tanzania to assess variability in stored water quality and to characterize uncertainty with different data collection schemes. Households were visited 5 times over the course of a year. At each visit, information was collected on water management practices, and a sample of stored drinking water was collected for E. coli enumeration. Water quality was poor for households, with 80% having highly contaminated (>100 CFU per 100 mL) water during at least one visit. There was substantial variability of water quality for households, with only 3% of households having the same category (low, medium, or high) of water quality for all five visits. These data suggest a single sample would inaccurately characterize a household's drinking water quality over the course of a year and lead to misestimates of population level access to safe drinking water.

Differential Overlap in Human and Animal Fecal Microbiomes and Resistomes in Rural versus Urban Bangladesh.

Low- and middle-income countries (LMICs) bear the largest mortality burden of antibiotic-resistant infections. Small-scale animal production and free-roaming domestic animals are common in many LMICs, yet data on zoonotic exchange of gut bacteria and antibiotic resistance genes (ARGs) in low-income communities are sparse. Differences between rural and urban communities with regard to population density, antibiotic use, and cohabitation with animals likely influence the frequency of transmission of gut bacterial communities and ARGs between humans and animals. Here, we determined the similarity in gut microbiomes, using 16S rRNA gene amplicon sequencing, and resistomes, using long-read metagenomics, between humans, chickens, and goats in a rural community compared to an urban community in Bangladesh. Gut microbiomes were more similar between humans and chickens in the rural (where cohabitation is more common) than the urban community, but there was no difference for humans and goats in the rural versus the urban community. Human and goat resistomes were more similar in the urban community, and ARG abundance was higher in urban animals than rural animals. We identified substantial overlap of ARG alleles in humans and animals in both settings. Humans and chickens had more overlapping ARG alleles than humans and goats. All fecal hosts from the urban community and rural humans carried ARGs on chromosomal contigs classified as potentially pathogenic bacteria, including Escherichia coli, Campylobacter jejuni, Clostridioides difficile, and Klebsiella pneumoniae. These findings provide insight into the breadth of ARGs circulating within human and animal populations in a rural compared to urban community in Bangladesh. IMPORTANCE While the development of antibiotic resistance in animal gut microbiomes and subsequent transmission to humans has been demonstrated in intensive farming environments and high-income countries, evidence of zoonotic exchange of antibiotic resistance in LMIC communities is lacking. This research provides genomic evidence of overlap of antibiotic resistance genes between humans and animals, especially in urban communities, and highlights chickens as important reservoirs of antibiotic resistance. Chicken and human gut microbiomes were more similar in rural Bangladesh, where cohabitation is more common. Incorporation of long-read metagenomics enabled characterization of bacterial hosts of resistance genes, which has not been possible in previous culture-independent studies using only short-read sequencing. These findings highlight the importance of developing strategies for combatting antibiotic resistance that account for chickens being reservoirs of ARGs in community environments, especially in urban areas.

Exploring the determinants and indicators of poultry feces management behaviors in rural Western Uganda.

Animal ownership has reported financial and nutritional benefits but has also been associated with enteric and respiratory infections, and inadequate sanitation and hygiene can lead to children touching and ingesting animal fecal matter. We identified key indicators for poultry feces management and investigated their social determinants using data from a baseline survey of a randomized-controlled trial of a poultry management training program in rural Western Uganda. The baseline survey was conducted in the Masindi and Kiryandongo districts of Uganda in September 2019, and data collected from 609 households were used. We evaluated indicators for poultry feces management behaviors using scale development methods, including descriptive statistics, bivariate correlation analyses, and Factor Analysis of Mixed Data. We also investigated social determinants of key poultry feces management behaviors using logistic and multinomial logistic regression models. A significant increase in odds of having free-roaming poultry was found for each additional poultry owned (OR = 1.18, P < 0.001). The odds of a household having an observed enclosure for poultry increased by 5% with each incremental poultry owned (OR = 1.05, P < 0.001), and by 4% with increasing wealth with each additional point on the poverty probability index score (OR = 1.04, P < 0.001). Our results also suggest enclosures are intermittently used and constructing them without further intervention likely will not be sufficient for effectively managing animal fecal contamination. We recommend that future studies on animal feces management measure indicators for corralling and feces disposal practices and evaluate their relationship to enteric pathogen exposure and health outcomes. Insights from this work can inform the development of robust indicators of poultry feces management behaviors that can be used for monitoring and evaluation purposes.

Modeling Exposure to Fecal Contamination in Drinking Water due to Multiple Water Source Use.

The Joint Monitoring Programme estimated that 71% of people globally had access to "safely managed" drinking water in 2017. However, typical data collection practices focus only on a household's primary water source, yet some households in low- and middle-income countries (LMICs) engage in multiple water source use, including supplementing improved water supplies with unimproved water throughout the year. Monte Carlo simulations and previously published data were used to simulate exposure to fecal contamination (as measured by E. coli) along a range of supplemental unimproved source use rates (e.g., 0-100% improved water use, with the remainder made up with unimproved water). The model results revealed a statistically significant increase in annual exposure to E. coli when individuals supplement their improved water with unimproved water just 2 days annually. Additionally, our analysis identified scenarios-realistic for the data set study setting-where supplementing with unimproved water counterintuitively decreases exposure to E. coli. These results highlight the need for evaluating the temporal dynamics in water quality and availability of drinking water sources in LMICs as well as capturing the use of multiple water sources for monitoring global access to safe drinking water.

Multiple water source use in low- and middle-income countries: a systematic review.

The Joint Monitoring Programme (JMP) 2017 Update and Sustainable Development Goals (SDGs) Baselines report classified 71% of the global population as having access to 'safely managed' drinking water. Current global monitoring efforts to track access to safely managed drinking water rely on collecting information on the 'primary' source of drinking water. However, there is evidence that households often rely on multiple sources to meet their water needs in many low- and middle-income countries (LMICs). This systematic review was designed to compile the literature related to the practice of multiple water source use (MWSU) for drinking water in LMICs. A total of 5,318 studies were collected, and after abstract and full-text review, 74 articles were identified for inclusion. Studies reviewed reported from 4 to 100% of the study populations practicing MWSU. Additionally, the practice of supplemental unimproved source use was reported globally, representing households with improved primary source water also accessing unimproved water sources throughout the year. These findings expose gaps in current global water monitoring efforts, revealing potential inflation of reports of 'safe drinking water access' and unaccounted exposure to drinking water from unimproved sources.

Comparison of analytical techniques to explain variability in stored drinking water quality and microbial hand contamination of female caregivers in Tanzania.

Exposure to fecal contamination continues to be a major public health concern for low-income households in sub-Saharan Africa. Drinking water and hands are known transmission routes for pathogens in household environments. In an effort to identify explanatory variables of water and hand contamination, a variety of analytical approaches have been employed that model variation in E. coli contamination as a function of behaviors and household characteristics. Using data collected from 1217 households in Bagamoyo, Tanzania, this investigation compares the explanatory variables identified in the three different modeling methods to explain hand and water contamination: ordinary least squares regression, logistic regression, and classification tree. Although the modeling approaches varied, there were some similarities in the results, with certain explanatory variables being consistently identified as being related to hand and water contamination (e.g., water source type for the water models and activity prior to sampling for the hand models). At the same time, there were also marked differences across the models. In sum, these results suggest there are benefits to using multiple analysis methods to assess relationships in complex systems. The models were also characterized by low explanatory power, suggesting that variation in hand and water contamination is difficult to capture when analyzing one-time water and hand rinse samples. For improved model performance, future studies could explore modeling of repeat measures of water quality and hand contamination.

Fecal Contamination on Produce from Wholesale and Retail Food Markets in Dhaka, Bangladesh.

Fresh produce items can become contaminated with enteric pathogens along the supply chain at the preharvest (e.g., irrigation water, soil, fertilizer) or postharvest (e.g., vendor handling or consumer handling) stages. This study assesses the concentrations of fecal indicator bacteria Escherichia coli, enterococci (ENT), and Bacteriodales on surfaces of carrots, eggplants, red amaranth leaves, and tomatoes obtained from both a wholesale market (recently harvested) and neighborhood retail markets in Dhaka, Bangladesh. We detected E. coli in 100% of carrot and red amaranth rinses, 92% of eggplant rinses, and 46% of tomato rinses. Using a molecular microbial source tracking assay, we found that 32% of produce samples were positive for ruminant fecal contamination. Fecal indicator bacteria were more likely to be detected on produce collected in retail markets compared with that in the wholesale market; retail market produce were 1.25 times more likely to have E. coli detected (P = 0.03) and 1.24 times more likely to have ENT detected (P = 0.03) as compared with wholesale market produce. Bacteriodales was detected in higher concentrations in retail market produce samples compared with wholesale market produce samples (0.40 log10 gene copies per 100 cm2 higher, P = 0.03). Our results suggest that ruminant and general fecal contamination of produce in markets in Dhaka is common, and suggest that unsanitary conditions in markets are an important source of produce fecal contamination postharvest.

Ruminants Contribute Fecal Contamination to the Urban Household Environment in Dhaka, Bangladesh.

In Dhaka, Bangladesh, the sensitivity and specificity of three human, three ruminant, and one avian source-associated QPCR microbial source tracking assays were evaluated using fecal samples collected on site. Ruminant-associated assays performed well, whereas the avian and human assays exhibited unacceptable cross-reactions with feces from other hosts. Subsequently, child hand rinses (n = 44) and floor sponge samples (n = 44) from low-income-households in Dhaka were assayed for fecal indicator bacteria (enterococci, Bacteroidales, and Escherichia coli) and a ruminant-associated bacterial target (BacR). Mean enterococci concentrations were of 100 most probable number (MPN)/2 hands and 1000 MPN/225 cm(2) floor. Mean concentrations of Bacteroidales were 10(6) copies/2 hands and 10(5) copies/225 cm(2) floor. E. coli were detected in a quarter of hand rinse and floor samples. BacR was detected in 18% of hand rinse and 27% of floor samples. Results suggest that effective household fecal management should account not only for human sources of contamination but also for animal sources. The poor performance of the human-associated assays in the study area calls into the question the feasibility of developing a human-associated marker in urban slum environments, where domestic animals are exposed to human feces that have been disposed in pits and open drains.

Occurrence of Host-Associated Fecal Markers on Child Hands, Household Soil, and Drinking Water in Rural Bangladeshi Households.

We evaluated whether provision and promotion of improved sanitation hardware (toilets and child feces management tools) reduced rotavirus and human fecal contamination of drinking water, child hands, and soil among rural Bangladeshi compounds enrolled in a cluster-randomized trial. We also measured host-associated genetic markers of ruminant and avian feces. We found evidence of widespread ruminant and avian fecal contamination in the compound environment; non-human fecal marker occurrence scaled with animal ownership. Strategies for controlling non- human fecal waste should be considered when designing interventions to reduce exposure to fecal contamination in low-income settings. Detection of a human- associated fecal marker and rotavirus was rare and unchanged by provision and promotion of improved sanitation to intervention compounds. The sanitation intervention reduced ruminant fecal contamination in drinking water and general (non-host specific) fecal contamination in soil but overall had limited effects on reducing fecal contamination in the household environment.

Enteric pathogens in stored drinking water and on caregiver's hands in Tanzanian households with and without reported cases of child diarrhea.

BACKGROUND: Diarrhea is one of the leading causes of mortality in young children. Diarrheal pathogens are transmitted via the fecal-oral route, and for children the majority of this transmission is thought to occur within the home. However, very few studies have documented enteric pathogens within households of low-income countries. METHODS AND FINDINGS: The presence of molecular markers for three enteric viruses (enterovirus, adenovirus, and rotavirus), seven Escherichia coli virulence genes (ECVG), and human-specific Bacteroidales was assessed in hand rinses and household stored drinking water in Bagamoyo, Tanzania. Using a matched case-control study design, we examined the relationship between contamination of hands and water with these markers and child diarrhea. We found that the presence of ECVG in household stored water was associated with a significant decrease in the odds of a child within the home having diarrhea (OR = 0.51; 95% confidence interval 0.27-0.93). We also evaluated water management and hygiene behaviors. Recent hand contact with water or food was positively associated with detection of enteric pathogen markers on hands, as was relatively lower volumes of water reportedly used for daily hand washing. Enteropathogen markers in stored drinking water were more likely found among households in which the markers were also detected on hands, as well as in households with unimproved water supply and sanitation infrastructure. CONCLUSIONS: The prevalence of enteric pathogen genes and the human-specific Bacteroidales fecal marker in stored water and on hands suggests extensive environmental contamination within homes both with and without reported child diarrhea. Better stored water quality among households with diarrhea indicates caregivers with sick children may be more likely to ensure safe drinking water in the home. Interventions to increase the quantity of water available for hand washing, and to improve food hygiene, may reduce exposure to enteric pathogens in the domestic environment.

Mechanisms of post-supply contamination of drinking water in Bagamoyo, Tanzania.

Access to household water connections remains low in sub-Saharan Africa, representing a public health concern. Previous studies have shown water stored in the home to be more contaminated than water at the source; however, the mechanisms of post-supply contamination remain unclear. Using water quality measurements and structured observations of households in Bagamoyo, Tanzania, this study elucidates the causal mechanisms of the microbial contamination of drinking water after collection from a communal water source. The study identifies statistically significant loadings of fecal indicator bacteria (FIB) occurring immediately after filling the storage container at the source and after extraction of the water from the container in the home. Statistically significant loadings of FIB also occur with various water extraction methods, including decanting from the container and use of a cup or ladle. Additionally, pathogenic genes of Escherichia coli were detected in stored drinking water but not in the source from which it was collected, highlighting the potential health risks of post-supply contamination. The results of the study confirm that storage containers and extraction utensils introduce microbial contamination into stored drinking water, and suggest that further research is needed to identify methods of water extraction that prevent microbial contamination of drinking water.