{ "background": "Public health surveillance systems are critical for early detection and response to disease outbreaks in Nigeria. However, the methodological rigour of evaluations assessing their effectiveness in reducing population health risks remains inconsistent and inadequately synthesised.", "purpose and objectives": "This meta-analysis aims to appraise the methodological quality of quasi-experimental studies evaluating surveillance systems in the country and to quantitatively synthesise evidence on their risk reduction outcomes.", "methodology": "We systematically searched multiple databases for quasi-experimental studies (including interrupted time series and controlled before-and-after designs) published since . Methodological quality was assessed using a modified Cochrane ROBINS-I tool. A random-effects meta-analysis was performed to pool standardised mean differences (SMD). The primary model was $\\hat{\\theta} = \\sum{i=1}^{k} wi yi / \\sum{i=1}^{k} wi$, where $wi = 1/(v_i + \\tau^2)$. Heterogeneity was quantified using the $I^2$ statistic.", "findings": "The pooled analysis of 18 included studies indicated a moderate, statistically significant overall effect (SMD = -0.42, 95% CI: -0.61 to -0.23), suggesting surveillance interventions reduce health risks. However, high heterogeneity ($I^2 = 78%$) and prevalent methodological limitations, particularly in controlling for confounding, were noted.", "conclusion": "While existing quasi-experimental evidence suggests public health surveillance systems contribute to risk reduction, the strength of this conclusion is tempered by substantial variability in study quality and design.", "recommendations": "Future evaluations should employ more robust quasi-experimental designs with explicit strategies for mitigating confounding. National guidelines should mandate and standardise the use of such designs for programme evaluation.", "key words": "disease surveillance, impact evaluation, quasi-experimental design, programme evaluation, health systems, Nigeria", "contribution statement": "This study provides the first quantitative