Abstract
{ "background": "Public health surveillance systems are critical for disease control and prevention, yet their methodological rigour and effectiveness in reducing population health risks in sub-Saharan Africa require systematic assessment. In Ghana, diverse surveillance approaches have been implemented, but a comprehensive, quantitative synthesis of their performance and impact is lacking.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate the performance of public health surveillance systems in Ghana and to model their effectiveness in reducing specific health risks using a Bayesian hierarchical framework.", "methodology": "We conducted a systematic review and meta-analysis of studies evaluating surveillance systems. A Bayesian hierarchical model was employed to synthesise effect estimates and account for heterogeneity across studies. The core model is specified as $yi \\sim N(\\thetai, \\sigma^2i)$, $\\thetai \\sim N(\\mu, \\tau^2)$, where $yi$ are observed log odds ratios, $\\thetai$ are study-specific true effects, and $\\mu$ is the pooled effect. Prior distributions were weakly informative. Inference was based on posterior distributions with 95% credible intervals (CrI).", "findings": "The pooled analysis indicates that enhanced, integrated surveillance systems are associated with a significant reduction in outbreak detection time, with a median decrease of 4.2 days (95% CrI: 2.8 to 5.6). Systems employing community-based reporting and laboratory confirmation demonstrated the greatest methodological robustness and predictive value. Heterogeneity between studies was substantial ($I^2 = 68%$).", "conclusion": "Methodological enhancements in surveillance, particularly integration and community involvement, are substantively linked to improved performance metrics and reduced public health risks in the Ghanaian context.", "recommendations": "Investment should prioritise the integration of surveillance data streams and the strengthening of community-based reporting networks. Future system evaluations must adopt standardised methodological indicators to facilitate comparative analysis.", "key words": "Bayesian meta-analysis, disease surveillance, health systems, risk