Identifying predictors of E. coli in rural household water in sub-Saharan Africa using elimination regression

Abstract

Exposure to fecally contaminated drinking water contributes to the global disease burden, especially in sub-Saharan Africa (SSA). We used cross-sectional data and elimination regression analysis to examine factors influencing E. coli contamination in household drinking water samples from 4499 rural households in nine countries in SSA (Malawi, Mozambique, and Zambia in Southern Africa; Ghana, Mali, and Niger in Western Africa; and Kenya, Rwanda, and Tanzania in Eastern Africa). The proportion of household water samples containing E. coli was 71%, ranging from 45% (Malawi) to 89% (Tanzania). Pooled and multi-country predictive logistic regression models showed that using an unimproved-type water source, the absence of a community water committee, and domestic animal ownership were significantly associated with household drinking water contamination. Household water treatment and storage practices, sanitation and hygiene practices, and payment for drinking water were not significantly associated with E. coli contamination in any model. The season was a significant predictor of E. coli in the pooled model; samples collected in the rainy season were 2.3 [2.0, 2.7] times as likely to be contaminated with E. coli. Practitioners and policymakers should prioritize implementing piped on-plot water services, establishing effective local water source management structures, and incorporating animal husbandry practices into water, sanitation, and hygiene interventions.