Logistic regression predicts disinfection outcomes based on ultraviolet intensity and water temperature.
Solar Disinfection (SODIS) is an effective method for treating drinking water by exposing it to sunlight in transparent containers for one to two days. Its success depends largely on two factors: Ultraviolet (UV) intensity and water temperature. Hence, the objective of this study is to evaluate the UV intensity and water temperature to predict complete and incomplete treatment in SODIS using logistic regression to classify the outcome of 33 SODIS trials (conducted from May to September 2024) as either complete or incomplete disinfection, based on these two parameters. Results showed that UV intensity (p = 0.005) slightly outperformed peak water temperature (p = 0.006) as a predictor in single-variable models, with the UV-only model achieving a McFadden R² of 0.62 and predictive accuracy of 87.5% in terms of sensitivity, specificity, and precision. The model identified that an average 6-hour UV intensity of 47 W/m² or a maximum water temperature of 49.9°C ensures a 95% likelihood of complete E. coli disinfection. These findings are particularly valuable for SODIS users in rural areas without access to UV measurement devices, as temperature alone can serve as a reliable indicator of disinfection success.
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Okeke et al. (2025) studied this question.
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