"background": "Public health surveillance is critical for disease control and health system planning. In Tanzania, numerous initiatives have aimed to strengthen surveillance, yet there remains a need for rigorous methodological evaluation of their efficiency and impact. Quasi-experimental designs offer a robust framework for such assessments in real-world settings where randomised trials are not feasible. ", "purpose and objectives": "This systematic review aims to critically appraise the application of quasi-experimental methodologies in evaluating the efficiency gains of public health surveillance systems in Tanzania. It seeks to identify common designs, analytical techniques, and key methodological strengths and limitations. ", "methodology": "A systematic search of multiple electronic databases was conducted following PRISMA guidelines. Studies employing quasi-experimental designs (e. g. , interrupted time series, difference-in-differences, regression discontinuity) to evaluate surveillance system efficiency were included. Quality was assessed using the ROBINS-I tool. A meta-analysis was not feasible due to heterogeneity; findings were synthesised narratively. The primary model considered was a difference-in-differences specification: Y{it = \0 + \1 + \2 + \3 (\) +, where inference relied on cluster-robust standard errors. ", "findings": "Of the 27 included studies, interrupted time series was the most frequently employed design (63%). A key theme was the inconsistent adjustment for confounding and secular trends, with only 41% of studies adequately addressing these. A concrete finding was that studies employing propensity score matching reported a 15–25% greater estimated reduction in reporting latency compared to simpler pre-post comparisons, though confidence intervals were often wide. ", "conclusion": "Quasi-experimental designs are increasingly used but often applied with methodological shortcomings that may bias estimates of surveillance efficiency gains. There is a clear need for more rigorous design and analytical practice to produce credible evidence for policy. ",
Mfinanga et al. (Sat,) studied this question.