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March 12, 2026Open Access

Methodological Evaluation of Public Health Surveillance Systems in Senegal Using Time-Series Forecasting Models for Risk Reduction Measurement

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Authors

SGSene GueyeMSMamadou SallTDToure Diallo

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Overview

Methodological evaluation reveals reduced disease incidence in Senegal, suggesting effective public health interventions.

Key Points

  • This research evaluates the effectiveness of public health surveillance systems in Senegal using time-series forecasting for disease trends.
  • Utilized ARIMA model for forecasting disease incidence rates.
  • Assessed uncertainty through robust standard errors and confidence intervals.
  • Analyzed data over the past five years to identify trends in disease cases.
  • Estimated treatment effects using a logit model for more precise predictions.
  • Identified a downward trend in reported disease cases over five years.
  • Demonstrated the utility of the ARIMA model in forecasting disease trends.
  • Suggested that current surveillance measures effectively reduce the impact of communicable diseases.

Cite This Study

Gueye et al. (2011) studied this question.

synapsesocial.com/papers/69b25b7196eeacc4fceca3cfhttps://doi.org/10.5281/zenodo.18937848
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