Public health surveillance systems are crucial for monitoring diseases and outbreaks in Uganda. However, their effectiveness can vary significantly across different regions. A quasi-experimental approach was employed, focusing on data from two districts with differing levels of system implementation. Data were collected through surveys and administrative records, analysed using linear regression models to estimate costs and outcomes. The analysis revealed that the surveillance systems in district A (n=300) were more cost-effective than those in district B (n=400), with a marginal improvement in health impact per unit cost of $2.50 ($95 CI: $1.80 to $3.60). The quasi-experimental design provided insights into the cost-effectiveness of public health surveillance systems, offering policy recommendations for resource allocation. Based on findings, it is recommended that additional resources be allocated to districts with less effective surveillance systems in order to improve health outcomes and reduce costs. Quasi-experimental design, Public health surveillance, Cost-effectiveness, Linear regression