Public health surveillance systems in Uganda are crucial for monitoring infectious diseases such as malaria and tuberculosis (TB). However, their effectiveness and cost-effectiveness vary across different settings. A comprehensive search strategy was employed using databases including PubMed and Embase. Studies published between and were included if they met specific criteria for methodological quality assessment. Multilevel regression analysis revealed that surveillance systems in rural areas are less effective due to lower population density, but more cost-effective as a result of reduced infrastructure costs. The multilevel regression model provided insights into the cost-effectiveness and potential improvements needed for public health surveillance systems across different regions in Uganda. Investment strategies should prioritise rural areas where surveillance effectiveness is compromised, while also considering cost-saving measures to enhance overall system performance. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Musoke et al. (Mon,) studied this question.
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