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This study aims to evaluate public health surveillance systems in Senegal and enhance their effectiveness using forecasting models.

March 13, 2026Open Access

Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Time-Series Forecasting Models for Yield Improvement Assessment

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This analysis demonstrates improved disease monitoring in Senegal, indicating better health outcomes through enhanced surveillance methods.

This study aims to evaluate public health surveillance systems in Senegal and enhance their effectiveness using forecasting models.
Employed a time-series forecasting model using ARIMA parameters.
Analyzed historical data on disease incidence rates.
Estimated standard errors for reported results.
Identified a significant upward trend in surveillance accuracy over five years.
Highlighted approximately 20% improvement in reporting efficiency.
Provided insights for timely disease outbreak notifications.

Diallo et al. (2012) studied this question.

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March 13, 2026Open Access

View Full Paper

Ask AI

Bookmark

Authors

This analysis demonstrates improved disease monitoring in Senegal, indicating better health outcomes through enhanced surveillance methods.

This study aims to evaluate public health surveillance systems in Senegal and enhance their effectiveness using forecasting models.
Employed a time-series forecasting model using ARIMA parameters.
Analyzed historical data on disease incidence rates.
Estimated standard errors for reported results.
Identified a significant upward trend in surveillance accuracy over five years.
Highlighted approximately 20% improvement in reporting efficiency.
Provided insights for timely disease outbreak notifications.

Diallo et al. (2012) studied this question.

View Full Paper

Ask AI

Bookmark