Freshwater Availability and Water Fetching Distance Affect Child Health in Sub-Saharan Africa

Currently, more than two-thirds of the population in Africa must leave their home to fetch water for drinking and domestic use. The time burden of water fetching has been suggested to influence the volume of water collected by households as well as time spent on income generating activities and child care. However, little is known about the potential health benefits of reducing water fetching distances. Data from almost 200 000 Demographic and Health Surveys carried out in 26 countries were used to assess the relationship between household walk time to water source and child health outcomes. To estimate the causal effect of decreased water fetching time on health, geographic variation in freshwater availability was employed as an instrumental variable for one-way walk time to water source in a two-stage regression model. Time spent walking to a household’s main water source was found to be a significant determinant of under-five child health. A 15-min decrease in one-way walk time to water source is associated with a 41% average relative reduction in diarrhea prevalence, improved anthropometric indicators of child nutritional status, and a 11% relative reduction in under-five child mortality. These results suggest that reducing the time cost of fetching water should be a priority for water infrastructure investments in Africa

Modeled <i>E</i>. <i>coli</i> and enterococci concentrations on hands of participants, adjusted for sampling efficiency.

<p>Modeled <i>E</i>. <i>coli</i> and enterococci concentrations on hands of participants, adjusted for sampling efficiency.</p

Fractional Transfer Efficiency Values Used in Exposure Model.

<p>^aRefers to the fomite used in the reference literature to determine transfer of Gram negative (<i>i</i>.<i>e</i>., <i>E</i>. <i>coli</i>) and Gram positive (i.e., enterococci) bacteria.</p><p>Fractional Transfer Efficiency Values Used in Exposure Model.</p

Frequency and Duration of Hand Contacts with Objects.

<p>-, did not contact.</p><p>^aNumber of contacts recorded over duration of observation and adjusted to frequency of contacts per hour (in parentheses).</p><p>^bTotal duration of contact reported in minutes: seconds format and percentage of total time in contact with each category (in parentheses).</p><p>^cNo object was in contact with the hand</p><p>Frequency and Duration of Hand Contacts with Objects.</p

Hands and Water as Vectors of Diarrheal Pathogens in Bagamoyo, Tanzania

Diarrheal disease is a leading cause of under-five childhood mortality worldwide, with at least half of these deaths occurring in sub-Saharan Africa. Transmission of diarrheal pathogens occurs through several exposure routes including drinking water and hands, but the relative importance of each route is not well understood. Using molecular methods, this study examines the relative importance of different exposure routes by measuring enteric bacteria (pathogenic <i>Escherichia coli</i>) and viruses (rotavirus, enterovirus, adenovirus) in hand rinses, stored water, and source waters in Bagamoyo, Tanzania. Viruses were most frequently found on hands, suggesting that hands are important vectors for viral illness. The occurrence of <i>E. coli</i> virulence genes (ECVG) was equivalent across all sample types, indicating that both water and hands are important for bacterial pathogen transmission. Fecal indicator bacteria and turbidity were good predictors of ECVG, whereas turbidity and human-specific <i>Bacteroidales</i> were good predictors of viruses. ECVG were more likely found in unimproved water sources, but both ECVG and viral genes were detected in improved water sources. ECVG were more likely found in stored water of households with unimproved sanitation facilities. The results provide insights into the distribution of pathogens in Tanzanian households and offer evidence that hand-washing and improved water management practices could alleviate viral and bacterial diarrhea

Student hand cleaning rates (% of toileting events) and duration captured by in-person structured observation <i>versus</i> video observation.

<p>*p<0.05.</p>φ<p>Rate-ratios (RR) and p-values reported for Poisson regression analysis of rate differences between video and in-person data, while controlling for the individual school at which the data were collected.</p

Hand cleaning rates (% of toileting events) when the subject was observed to be alone in the video frame <i>versus</i> when other students were present in the frame, as captured by video surveillance.

<p>Hand cleaning rates (% of toileting events) when the subject was observed to be alone in the video frame <i>versus</i> when other students were present in the frame, as captured by video surveillance.</p

Hand cleaning rates (% of toileting events) captured by video surveillance data (left), and by in-person observation (right).

<p>Simultaneous monitoring refers periods when in-person observation and video surveillance were conducted concurrently.</p><p>*p<0.05.</p>φ<p>Rate-ratios (RR) and p-values reported for Poisson regression analysis of rate differences between simultaneous and independent monitoring, while controlling for the individual school at which the data were collected.</p

Proportion of student toileting events followed by hand cleaning, shown by number of other people present at the hand cleaning station (visible within the camera view frame).

<p>Error bars show standard error of the mean.</p

Schematic of study design.

<p>Number of toileting events captured on video surveillance (N_V) and through in-person observation (N_P), during independent (single-method) <i>versus</i> simultaneous monitoring periods.</p