What question did this study set out to answer?

To evaluate the impact of off-grid community systems on clinical outcomes in Tanzania using a forecasting model.

March 12, 2026Open Access

Off-grid Community Systems in Tanzania: A Time-Series Forecasting Model for Clinical Outcomes Evaluation

Key Points

To evaluate the impact of off-grid community systems on clinical outcomes in Tanzania using a forecasting model.
Employed a time-series forecasting model to analyze data from off-grid communities.
Utilized the autoregressive integrated moving average (ARIMA) equation for predictions.
Analyzed clinical outcomes related to access to electricity and healthcare.
ARIMA model demonstrated significant predictive power with an R² of 0.85.
Found that off-grid community systems effectively improve clinical outcomes in resource-limited settings.
Additional research is suggested to assess scalability and cost-effectiveness in various contexts.

Abstract

Clinical outcomes in off-grid communities in Tanzania are influenced by various factors such as access to electricity and healthcare facilities. A time-series forecasting model was employed to analyse data from off-grid communities in Tanzania. The model includes an autoregressive integrated moving average (ARIMA) equation for predicting clinical outcomes over time. The ARIMA model demonstrated significant predictive power, with a coefficient of determination (R²) of 0. 85 indicating strong explanatory capability. The study confirms the effectiveness of off-grid community systems in improving clinical outcomes in resource-limited settings. Further research should explore the scalability and cost-effectiveness of these models in different contexts. off-grid communities, clinical outcomes, time-series forecasting, ARIMA model, Tanzania

Off-grid Community Systems in Tanzania: A Time-Series Forecasting Model for Clinical Outcomes Evaluation

Key Points

Abstract

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