Linking Quantitative Microbial Risk Assessment and Epidemiological Data: Informing Safe Drinking Water Trials in Developing Countries

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Abstract
Intervention trials are used extensively to assess household water treatment (HWT) device efficacy against diarrheal disease in developing countries. Using these data for policy, however, requires addressing issues of generalizability (relevance of one trial in other contexts) and systematic bias associated with design and conduct of a study. To illustrate how quantitative microbial risk assessment (QMRA) can address water safety and health issues, we analyzed a published randomized controlled trial (RCT) of the LifeStraw Family Filter in the Congo. The model accounted for bias due to (1) incomplete compliance with filtration, (2) unexpected antimicrobial activity by the placebo device, and (3) incomplete recall of diarrheal disease. Effectiveness was measured using the longitudinal prevalence ratio (LPR) of reported diarrhea. The Congo RCT observed an LPR of 0.84 (95% CI: 0.61, 1.14). Our model predicted LPRs, assuming a perfect placebo, ranging from 0.50 (2.5–97.5 percentile: 0.33, 0.77) to 0.86 (2.5–97.5 percentile: 0.68, 1.09) for high (but not perfect) and low (but not zero) compliance, respectively. The calibration step provided estimates of the concentrations of three pathogen types (modeled as diarrheagenic E. coli, Giardia, and rotavirus) in drinking water, consistent with the longitudinal prevalence of reported diarrhea measured in the trial, and constrained by epidemiological data from the trial. Use of a QMRA model demonstrated the importance of compliance in HWT efficacy, the need for pathogen data from source waters, the effect of quantifying biases associated with epidemiological data, and the usefulness of generalizing the effectiveness of HWT trials to other contexts.

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