Methodological Evaluation of Public Health Surveillance Systems in Rwanda Using Multilevel Regression Analysis

Public health surveillance systems in Rwanda are crucial for monitoring infectious diseases to prevent outbreaks. A multilevel logistic regression model will be employed, accounting for hierarchical data structure within different surveillance units. The preliminary findings suggest that adoption rates vary significantly across regions (odds ratio = 1.54, $p$ < 0.05) with potential influences from regional healthcare resources. Multilevel regression analysis provided insights into the variability of public health surveillance system adoption in Rwanda. Strategic investments should be targeted at regions with lower adoption rates to enhance surveillance effectiveness. Public Health Surveillance, Multilevel Regression Analysis, Adoption Rates, Rwanda