Methodological Evaluation of Public Health Surveillance Systems in Ethiopia: A Systematic Review of Quasi-Experimental Designs for Clinical Outcome Measurement

{ "background": "Public health surveillance systems are critical for monitoring disease burdens and guiding interventions in low-resource settings. In Ethiopia, the methodological rigour of evaluations for these systems, particularly those employing quasi-experimental designs to assess clinical outcomes, requires systematic assessment to inform evidence-based public health practice.", "purpose and objectives": "This systematic review aims to critically appraise the methodological approaches used in quasi-experimental evaluations of public health surveillance systems within the country, focusing on their design, analytical techniques, and the validity of clinical outcome measurements.", "methodology": "A systematic search of multiple electronic databases was conducted following a pre-registered protocol. Studies were included if they employed a quasi-experimental design (e.g., interrupted time series, difference-in-differences) to evaluate a surveillance system's impact on a clinical health outcome. Data were extracted on study design, statistical methods, risk of bias, and key findings. A meta-analysis was precluded due to heterogeneity; a narrative synthesis was performed. The relationship between surveillance system attributes and outcome changes was modelled using a random-effects meta-regression: Yi = \β0 + \β1Xi + ui + ei, where Yᵢ is the standardised mean difference in clinical outcome.", "findings": "Of the 27 included studies, a clear majority (78%) utilised an uncontrolled before-and-after design, which carries a high risk of bias from confounding. Only four studies employed more robust designs such as interrupted time series. A prominent theme was the frequent failure to account for autocorrelation in time-series data. The meta-regression indicated that surveillance systems with integrated laboratory confirmation were associated with improved outcome measurement, though the 95% confidence interval for this effect included the null.", "conclusion": "The methodological quality of quasi-experimental evaluations is highly variable, with a predominant reliance on weak study designs that limit causal inference about the impact of surveillance systems on clinical outcomes.", "recommendations": "Future evaluations should adopt more