Public health surveillance systems in Tanzania are crucial for monitoring disease outbreaks and implementing effective control measures. The study employed a difference-in-differences model to analyse pre- and post-intervention data from surveillance systems in Tanzania. Uncertainty was addressed through robust standard errors. A significant reduction of 20% (95% CI: 15%-25%) in the number of reported disease cases after system implementation was observed, indicating improved effectiveness. The difference-in-differences model demonstrated that public health surveillance systems are cost-effective, with substantial benefits in reducing disease incidence. Further investment and continuous evaluation of these systems are recommended to maintain their efficacy and impact. Public Health Surveillance, Difference-in-Differences Model, Cost-Effectiveness Analysis, Tanzania Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Magugu et al. (Sun,) studied this question.