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Author Notes:

Address correspondence to William E. Oswald, Department of Disease Control, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, United Kingdom. E-mail: william.oswald@lshtm.ac.uk

We would like to thank the Amhara National Regional Health Bureau and health offices, The Carter Center staff, field teams, and study supervisors.

We are especially grateful to the residents of selected communities, who gave freely of their time to participate.

We acknowledge Gonzalo Vazquez-Prokopec, Julie Clennon, Donal Bisanzio, and Cecile Janssens at Emory University for instruction and early discussions on study methods and approach.

See publication for full list of disclosures.


Research Funding:

William Oswald was supported by the Emory University Laney Graduate School, ARCS Foundation Atlanta, and the Global 2000 program of The Carter Center.

This study was supported by the Lions-Carter Center Sight-First Initiative and was made possible by the generous support of the American people through the U.S. Agency for International Development (USAID) and the ENVISION project led by RTI International in partnership with The Carter Center.


  • Science & Technology
  • Life Sciences & Biomedicine
  • Public, Environmental & Occupational Health
  • Tropical Medicine

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

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Journal Title:

American Journal of Tropical Medicine and Hygiene


Volume 95, Number 3


, Pages 709-719

Type of Work:

Article | Final Publisher PDF


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. Modelpredicted 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.

Copyright information:

© 2016 by The American Society of Tropical Medicine and Hygiene.

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