Public health surveillance systems in South Africa are crucial for monitoring disease prevalence and guiding intervention strategies. However, their effectiveness varies widely across different regions and populations. The study will employ a fixed-effects model to analyse longitudinal data from various health districts, accounting for potential confounders and temporal trends. Panel data will be collected through standardised surveys and administrative records. A preliminary analysis indicates that the panel data approach can effectively capture variations in risk reduction across different geographical regions within South Africa. The fixed-effects model provides a nuanced understanding of how public health interventions impact disease rates over time, offering insights into resource allocation strategies. Public health officials should prioritise continuous monitoring and evaluation of surveillance systems to ensure they remain effective in detecting and responding to emerging health threats. public health surveillance, panel data analysis, risk reduction, South Africa Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Mkhize et al. (Thu,) studied this question.