Public health surveillance systems in South Africa are crucial for monitoring infectious diseases and public health emergencies. However, their efficiency varies across different levels of government and communities. A multilevel regression model was applied to assess the impact of various factors influencing surveillance system performance at both local and national levels. The model is specified as: Y₈₉ = eta₀ + eta₁X₈₉₁ + eta₂X₈₉₂ + uᵢ + vⱼ + e₈₉, where uᵢ represents the fixed effects of regions, vⱼ captures the random effects of different levels, and e₈₉ is the error term. Robust standard errors were used to account for potential heteroscedasticity. The model revealed significant differences in surveillance efficiency across provinces, with some areas showing substantial room for improvement in reporting accuracy and timeliness. This study highlights the importance of multilevel analysis for understanding public health surveillance system performance and suggests targeted interventions to enhance overall efficiency. Investment should be prioritised in improving data collection methods, training personnel at all levels, and fostering collaboration between government entities and communities. multilevel regression, public health surveillance systems, South Africa, efficiency gains
Sibusiso Motshega (Wed,) studied this question.
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