Public health surveillance systems in Tanzania are crucial for monitoring and responding to infectious diseases such as malaria and tuberculosis (TB). A systematic review of studies applying difference-in-differences models to evaluate public health surveillance effectiveness in Tanzania. Studies were selected based on specific criteria related to data availability and study design quality. The application of difference-in-differences models revealed mixed results, with some studies showing significant efficiency gains in disease reporting times but others indicating persistent inefficiencies due to logistical challenges. Despite methodological variations, the majority of reviewed studies used difference-in-differences effectively as a tool for assessing surveillance system performance and identifying areas needing improvement. Future research should prioritise robust data collection methods and continuous evaluation to ensure consistent application of difference-in-differences models in public health surveillance systems. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.