Abstract
{ "background": "Public health surveillance is critical for early disease detection and response, yet evidence on the cost-effectiveness of different surveillance system designs in low-resource settings remains sparse. This gap hinders optimal resource allocation for health security.", "purpose and objectives": "This case study aimed to methodologically evaluate a randomised field trial design for measuring the cost-effectiveness of two distinct public health surveillance system architectures in a real-world setting.", "methodology": "We implemented a cluster-randomised field trial across multiple districts. Districts were randomly assigned to either a centralised, laboratory-based surveillance system or a decentralised, community-led system. Cost data were collected prospectively. Effectiveness was measured via timeliness and completeness of case reporting. Cost-effectiveness was analysed using a decision-analytic model, with the primary outcome being the incremental cost-effectiveness ratio (ICER). Statistical inference was based on a generalised linear mixed model: $Y{ij} = \\beta0 + \\beta1 X{ij} + uj + \\epsilon{ij}$, where $u_j$ are random cluster effects, with robust standard errors.", "findings": "The decentralised system demonstrated a lower mean cost per confirmed case reported, with a point estimate of £1,240 (95% CI: £1,100 to £1,410) compared to £1,850 for the centralised system. The primary analysis indicated a 92% probability that the decentralised system was cost-effective at a willingness-to-pay threshold of £1,500 per timely report.", "conclusion": "The randomised field trial proved a rigorous methodological approach for comparative economic evaluation of surveillance systems. The decentralised model showed a high probability of being more cost-effective under the studied conditions.", "recommendations": "Future evaluations of public health surveillance should incorporate randomised designs where ethically and practically feasible. Policymakers should consider piloting decentralised, community-integrated surveillance architectures to enhance cost-efficiency.", "key words": "health economics, incremental cost-effectiveness ratio, cluster