Time-series model forecasts adoption rates in Ugandan community health centres, suggesting insights for policy enhancements.
Community health centres in Uganda have been established to improve access to healthcare services across rural areas where facilities are scarce. A time-series analysis was conducted on data from five Ugandan community health centres, employing an ARIMA (AutoRegressive Integrated Moving Average) model to forecast adoption rates over a six-month period. The ARIMA(1,1,0) model showed that the average monthly adoption rate fluctuated by ±2% around its mean value, indicating moderate variability in service uptake across centres. The time-series forecasting approach provided insights into the potential factors affecting community health centre utilization and can inform future policy interventions aimed at increasing their effectiveness. Further research should explore non-technical barriers to adoption such as cultural norms or financial constraints, alongside improving data collection methods for more accurate forecasting. Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.
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Patrick Okello (2000) studied this question.
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