{ "background": "Public health surveillance systems are critical for disease control and health policy, yet rigorous methodological evaluations of their impact on clinical outcomes in low-resource settings are limited. Rwanda has implemented several innovative surveillance initiatives, but their comparative effectiveness remains unclear.", "purpose and objectives": "This meta-analysis aims to synthesise evidence from randomised field trials to evaluate the methodological rigour of surveillance system assessments and quantify their effect on measurable clinical outcomes within the country's public health framework.", "methodology": "We systematically identified published and unpublished randomised field trials. A random-effects model was employed to pool standardised mean differences (SMDs). Heterogeneity was assessed using the I² statistic, and publication bias was evaluated via funnel plots and Egger's test. The primary statistical model was: $\\thetai = \\mu + \\epsiloni + \\deltai$, where $\\thetai$ is the observed effect in study $i$, $\\mu$ the true effect, $\\epsiloni$ the within-study error, and $\\deltai$ the study heterogeneity.", "findings": "Pooled analysis of interventions integrating community health workers with digital reporting tools showed a significant improvement in case detection rates for notifiable diseases (SMD 0.42, 95% CI 0.28 to 0.56). However, substantial heterogeneity was present (I² = 67%), and the 95% prediction interval for the true effect in a new setting ranged from -0.10 to 0.94.", "conclusion": "Methodologically, trials assessing surveillance systems show variable quality, but evidence indicates that integrated, community-based digital systems can enhance specific clinical outcome measures. The generalisability of these effects is uncertain due to significant study variation.", "recommendations": "Future trials should adopt core outcome sets for surveillance evaluation and employ adaptive trial designs. Investment should prioritise integrated human-digital system components proven to enhance detection, while strengthening methodological standards for field evaluations.", "key words": "public