Public health surveillance systems in Nigeria play a crucial role in monitoring and responding to diseases such as malaria and tuberculosis. However, their effectiveness is often uncertain due to methodological limitations. A systematic literature review was conducted using electronic databases such as PubMed, Cochrane Library, and Google Scholar. Studies on public health surveillance systems in Nigeria were identified and analysed for methodological rigor, including the use of appropriate statistical models and reporting standards. The analysis revealed that while many studies used logistic regression models to predict disease prevalence, only 30% reported robust standard errors or confidence intervals, indicating a need for enhanced methodological practices. This review highlights the importance of adopting rigorous methodologies in public health surveillance systems to ensure accurate and reliable data collection and analysis. Public health agencies should prioritise training on advanced statistical techniques and reporting guidelines to improve the quality of surveillance data. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.