Semi-quantitative estimation of Escherichia coli levels in public drinking water sources in northern Haiti

Abstract

Prior research in Milot, Haiti, documented that public water sources are commonly fecally contaminated, as indicated by the presence of Escherichia coli. However, the degree of contamination was not assessed. In this study, the degree of fecal contamination in public drinking water sources was determined. Further, the usefulness of sanitary inspection surveys to predict fecal contamination was evaluated. A convenience sample of public water sources was tested using a semi-quantitative assay, which estimates the most probable number (MPN) of E. coli/100 mL of water. Each source was evaluated using the World Health Organization sanitary inspection score and classified as improved or unimproved. Sixty-three water sources were tested, of which 27 (43%) had <1 MPN/100 mL, 19 (30%) were contaminated from 1 to 100 MPN/100 mL, and 17 (27%) were contaminated with >100 MPN/100 mL. Some improved water sources were contaminated with >100 MPN/100 mL. The sanitary inspection score did not distinguish between sources that were and were not contaminated with E. coli. In Milot, Haiti, public water sources can be highly contaminated with E. coli. Since neither the categorization of a water source as improved or unimproved nor the sanitary inspection score can predict contamination, routine microbiological testing is justified.

Sanitary inspection, microbial water quality analysis, and water safety in handpumps in rural sub-Saharan Africa

“…It is not surprising that statistical models comparing sanitary risk score and E. coli occurrence produce no significant association, in line with the results reported by the studies that used the established models 12,13,[16][17][18] . Sanitary inspection was designed as a risk assessment and decision-making tool, and is expected to be only loosely correlated with E. coli occurrence in a given water sample at a given point in time 14 .…”

“…Statistical methods described in previous literature 14 were used to assess the relationship between sanitary inspection and E. coli occurrence: a. Logistic regression: used to analyze the relationship between the presence/absence of detectable E. coli in 100-mL sample (binary) and sanitary risk score (ordinal), and to compare presence/absence of detectable E. coli (binary) with the presence/absence of individual sanitary risk factors (binary) 18,27,30,31 . b. Ordinal logistic regression: used to compare the WHO water quality risk category (ordinal) with both sanitary risk score (ordinal) and the presence/absence of individual sanitary risk factors (binary).…”

Karst aquifers and water resource contamination in Haiti

“…The causes of deforestation are primarily land clearing for agriculture, charcoal production, and urbanization. Decreased natural filtration of surface runoff combined with inadequate sanitation infrastructure, shallow karst aquifers, and dysfunctional macro-and micro-biotic ecosystems, result in widespread contamination of surface-water and groundwater resources with human pathogens (Gerges et al 2016;Koski-Karell et al 2016;Rayner et al 2016;Reyes-Ortiz et al 2014;Wampler and Sisson 2011). Karst solution of limestone, and abundant fracturing due to brittle deformation, exacerbate this problem by providing pathways, open conduits, storage locations, and rapid transport for bacteria-laden water and organic debris.…”