Methodological Assessment and Yield Improvement Evaluation of Public Health Surveillance Systems in Uganda Using Multilevel Regression Analysis

Public health surveillance systems in Uganda are crucial for monitoring infectious diseases to prevent outbreaks and improve public health outcomes. A multilevel regression model was employed to assess system performance at both national and regional levels, accounting for variability in surveillance data. The model revealed that increasing funding by 10% at the district level significantly improved disease detection rates (OR = 1.23; CI: 1.05-1.47). This study provides a robust framework for optimising public health surveillance systems in Uganda, with specific recommendations for resource allocation. Public health authorities should prioritise additional funding to high-risk districts identified by the model.