Public health surveillance systems (PHSSs) play a crucial role in monitoring disease outbreaks and managing public health emergencies. A Bayesian hierarchical model was employed to assess system reliability within the context of PHSSs. The model accounts for spatial and temporal variability, incorporating prior knowledge about surveillance systems' performance. The analysis revealed that the probability of accurately detecting disease outbreaks across Senegal's regions varied significantly, with some areas having a detection rate as high as 85% in. This study provides insights into the strengths and weaknesses of PHSSs in different regions of Senegal, highlighting the importance of regional-specific surveillance efforts. Future research should focus on developing targeted interventions to improve detection rates in underperforming areas, thereby enhancing overall public health outcomes. Bayesian hierarchical model, Public health surveillance systems, System reliability, Disease outbreak detection, Senegal Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Sow et al. (Sun,) studied this question.
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