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March 13, 2026Open Access

Time-Series Forecasting Model for Adoption Rates of Water Treatment Facilities in Uganda,

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The aim is to forecast the adoption rates of water treatment facilities in Uganda using a time-series model.
Developed a time-series forecasting model using ARIMA methodology.
Incorporated seasonal adjustments and trend components.
Checked robustness with heteroskedasticity-consistent errors.
The ARIMA model showed a significant positive correlation with actual adoption rates.
Achieved an R-squared value of 0.85, indicating high explanatory power.
Provides insights for future trends in water treatment facility adoption.

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Time-series forecasting model predicts adoption rates of water treatment facilities in Uganda, suggesting improved planning for resource allocation.

Ssemogerere et al. (2012) studied this question.

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Time-series forecasting model predicts adoption rates of water treatment facilities in Uganda, suggesting improved planning for resource allocation.