Public health surveillance systems in Nigeria are crucial for monitoring disease prevalence and guiding interventions aimed at reducing risk factors. A randomized field trial was conducted across five states, with data collection using a validated questionnaire. The study employed logistic regression analysis for assessing predictive factors and estimating effect sizes. The preliminary findings suggest that the current surveillance system overestimates the prevalence of smoking by approximately 15%, which may influence policy decisions. While initial results indicate room for improvement, this study provides a robust framework for refining public health surveillance systems in Nigeria. Future research should focus on validating and standardising data collection methods to enhance the accuracy of risk reduction measurements. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Ejike et al. (Sat,) studied this question.