Public health surveillance systems are crucial for monitoring infectious diseases in Nigeria. However, their reliability varies significantly across regions and over time. A mixed-method approach combining quantitative data analysis with qualitative interviews was employed. The study utilised a logistic regression model to analyse surveillance accuracy and robust standard errors. The proportion of correctly identified infectious diseases ranged from 58% to 72%, indicating room for improvement in system reliability. Despite challenges, the quasi-experimental design provided insights into areas needing enhancement within Nigeria's public health surveillance systems. Further research should focus on implementing standardised training programmes and enhancing data sharing protocols among different surveillance agencies. public health surveillance, Nigeria, reliability assessment, quasi-experimental design Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.