Sanitary inspection characteristics, precipitation, and microbial water quality - A three-country study of rural boreholes in Sub-Saharan Africa

Microbial contamination of drinking water contributes to disease burdens that disproportionately impact infants and children and are largely preventable through suitable design, operation, monitoring, and management of improved water systems. The World Health Organization (WHO) has published guidance on water safety planning, water quality monitoring, and management approaches, including recommendations on sanitary inspection (SI) of water systems to detect and manage microbial hazards associated with fecal contamination. SI is a low-cost risk assessment tool for water systems based on observable risk factors (RFs) associated with potential water safety hazards. While SI has been previously studied, much of the literature has not quantitatively explored rainfall interactions with SI risk as drivers of fecal contamination. We merged remote-sensing rainfall estimates with SI and water quality data collected from 966 rural boreholes in Ethiopia, Ghana, and Burkina Faso. Logistic regressions (binary and ordinal) were used to characterize associations of total SI score, as well as individual risk factors (RFs), and classes of RFs (i.e., “Source,” “Transport,” and “Barrier” risks) with fecal indicator bacteria (FIB) occurrence, controlling for rainfall (over the past 1–15 days before sampling). We found associations (P < 0.05, OR: 3.5, 95% CI 1.05-11.66) between SI scores and E. coli risk categories controlling for fifteen-day total rainfall. Furthermore, interactions between rainfall and risk factors in the “barrier” category, and the “transport” category were associated with E. coli occurrence. Several individual RFs were also significantly associated with microbial contamination. Incorporating precipitation into models improved model fit characteristics (improved Pseudo R squared and AIC value); specifically, accounting for cumulative rainfall during the fifteen days before sampling improved model fit (increased pseudo-R 2 from 0.035 to 0.05) for E. coli contamination. These findings can inform design, construction, maintenance, and monitoring of boreholes and prompt timely remediation of defects in such systems, potentially enhancing water safety.