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Am J Trop Med Hyg. 2016 Sep 7;95(3):709-19. doi: 10.4269/ajtmh.15-0895. Epub 2016 Jul 18.

Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia.

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Department of Epidemiology, Emory University, Atlanta, Georgia.
The Carter Center, Atlanta, Georgia.
Department of Epidemiology, Emory University, Atlanta, Georgia.
The Carter Center, Addis Ababa, Ethiopia.
The Carter Center, Addis Ababa, Ethiopia. International Trachoma Initiative, Addis Ababa, Ethiopia.
Amhara Regional Health Bureau, Bahir Dar, Ethiopia.
The Carter Center, Atlanta, Georgia. World Health Organization, Geneva, Switzerland.
The Carter Center, Atlanta, Georgia. International Trachoma Initiative, Atlanta, Georgia.
Hubert Department of Global Health, Center for Global Safe Water, Emory University, Atlanta, Georgia.
Department of Environmental Health, Emory University, Atlanta, Georgia.


This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies.

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