Public health surveillance systems are crucial for monitoring disease prevalence and guiding intervention strategies in South Africa, a country with significant public health challenges. A difference-in-differences approach was employed to assess changes in clinical outcomes over time, comparing pre- and post-intervention periods. Data from two surveillance sites were analysed using statistical software. The DiD model indicated a significant reduction (p < 0. 05) in hospitalization rates for respiratory infections following the implementation of new screening protocols. This study demonstrates the utility of DiD models in evaluating public health surveillance systems and highlights the potential for improving clinical outcomes through targeted interventions. Public health agencies should consider implementing similar evaluation methods to monitor system effectiveness and inform future policy decisions. public health, surveillance systems, difference-in-differences (DiD), clinical outcomes, infectious diseases Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Siyabonga Khumalo (Tue,) studied this question.
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