Methodological Evaluation and Yield Optimisation of Public Health Surveillance Systems in Rwanda: A Meta-Analysis of Randomised Field Trials (2000–2026)

{ "background": "Public health surveillance is critical for disease control, yet the methodological rigour of field trials evaluating such systems, particularly in low-resource settings, is variable. A consolidated evidence base is required to inform the design of efficient surveillance programmes.", "purpose and objectives": "This meta-analysis aims to synthesise evidence from randomised field trials to methodologically evaluate surveillance systems and quantify their yield improvement for public health outcomes in the specified national context.", "methodology": "We systematically identified randomised field trials comparing surveillance system interventions against control conditions. A random-effects model was fitted to aggregate yield measures, with the summary effect θ = ∑i=1ᵏ wi ∑i=1ᵏ wi estimated, where $wi$ is the inverse-variance weight for the iᵗʰ study. Heterogeneity was assessed using the I² statistic, and publication bias was evaluated via funnel plots and Egger's test.", "findings": "The pooled analysis of included trials demonstrated a significant yield improvement, with a risk ratio of 1.42 (95% CI 1.18 to 1.71) for primary disease detection outcomes. Methodological strengths were identified in cluster randomisation design, while common limitations included inadequate blinding of outcome assessors.", "conclusion": "Evidence from randomised trials indicates that structured interventions within surveillance systems substantially improve case detection yield. Methodological quality varies, underscoring the need for standardised trial reporting.", "recommendations": "Future surveillance research should adopt core outcome sets and ensure blinding where feasible. Programme implementers should prioritise interventions that enhance community-based reporting linkages.", "key words": "public health surveillance, meta-analysis, randomised controlled trials, health systems research, yield, methodology", "contribution statement": "This study provides the first quantitative synthesis of experimental evidence on surveillance system efficacy in the region, introducing a novel quality-appraisal framework specific to surveillance trial design." } ``` Background