02440nas a2200361   4500000000100000008004100001653000900042653001500051653001300066653001400079100001300093700001400106700001500120700001400135700001500149700001400164700001300178700001100191700001500202700001300217700001400230700001300244700001100257700001400268700001600282700001000298700001300308245012900321300001100450490000700461520159600468022001402064       2016                            d10aWASH10aSanitation10aCoverage10aCommnuity1 aOswald W1 aStewart A1 aFlanders D1 aKramer MR1 aEndeshaw T1 aZerihun M1 aMelaku B1 aSata E1 aGessesse D1 aTeferi T1 aTadesse Z1 aGuadie B1 aKing J1 aEmerson P1 aCallahan EK1 aMoe C1 aClasen T00aPrediction of low community sanitation coverage using environmental and sociodemographic factors in Amhara region, Ethiopia.  a709-190 v953 a<p>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 (&lt; 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.</p>
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