A Contamination Predictive Model for Escherichia coli in Rural Communities Dug Shallow Wells

Hítalo Tobias Lôbo Lopes (), Luis Rodrigo Fernandes Baumann and Paulo Sérgio Scalize
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Hítalo Tobias Lôbo Lopes: School of Civil and Environmental Engineering (EECA) and Post-Graduation Program in Environmental and Sanitary Engineering (PPGEAS), Federal University of Goiás, Goiânia 74000-000, Brazil
Luis Rodrigo Fernandes Baumann: Institute of Mathematics and Statistics, Federal University of Goiás, Goiânia 74000-000, Brazil
Paulo Sérgio Scalize: School of Civil and Environmental Engineering (EECA), Post-Graduation Program in Environmental Sciences (CIAMB) and the Post-Graduation Program in Environmental and Sanitary Engineering (PPGEAS), Federal University of Goiás, Goiânia 74000-000, Brazil

Sustainability, 2023, vol. 15, issue 3, 1-16

Abstract: In Brazilian rural communities, the lack of treated water leads their residents to seek individual and alternative solutions, in which dug shallow wells (DSW) are quite widespread. However, water quality may not be fitted for human consumption. For this reason, the current study aimed to predict the contamination of DSW water in rural communities in the Brazilian state of Goiás. For this, secondary data related to water quality, the distance to possible contamination sources, structural conditions, and local geology were evaluated. Therefore, a generalized linear model was applied, and its predictors were evaluated by stepwise methods (Akaike information criterion—AIC and Bayesian information criterion—BIC), generating an intermediate model. After the analysis, turbidity parameter was chosen to be removed resulting in a final, submitted to leave-one-out cross-validation method, and its performance was measured by a confusion matrix. The final model resulted in four predictive variables: well diameter, contour paving width, poultry, and swine husbandry existence. The model accuracy was 82.61%, with a true positive predictor of 82.18% and a negative predictor of 85.71%.

Keywords: logistic regression; groundwater; poultry; swine; small community (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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