Abstract
{ "background": "Public health surveillance systems are critical for disease control, yet methodological frameworks for their empirical evaluation and optimisation in low-resource settings remain underdeveloped. Current assessments are often retrospective and descriptive, lacking rigorous experimental designs to quantify the causal impact of system modifications on operational efficiency.", "purpose and objectives": "This protocol details a randomised field trial to methodologically evaluate and optimise surveillance systems in Senegal. The primary objective is to measure efficiency gains from a redesigned data capture and reporting protocol against the standard system. Secondary objectives include assessing the cost per complete report and the timeliness of outbreak signal detection.", "methodology": "We will conduct a cluster-randomised controlled trial across 60 health facilities. Facilities will be randomised 1:1 to implement either the optimised surveillance protocol (intervention) or continue standard procedures (control). The primary outcome is the proportion of complete weekly reports submitted. Analysis will use a generalised linear mixed model: $\\logit(P(Y{ij}=1)) = \\beta0 + \\beta1 X{ij} + ui + e{ij}$, where $X{ij}$ is the intervention, $ui$ is a cluster random effect, and inference will be based on 95% confidence intervals using robust standard errors.", "findings": "As a protocol, no empirical findings are presented. The anticipated direction of effect is a significant increase in the proportion of complete reports from the intervention arm. The analysis plan is pre-specified to detect a minimum 15-percentage-point improvement in report completeness.", "conclusion": "This protocol provides a novel methodological framework for the experimental evaluation of public health surveillance, moving beyond observational assessment. The trial is designed to generate robust evidence on specific, actionable modifications to improve system performance.", "recommendations": "Future surveillance strengthening initiatives should incorporate rigorous experimental designs to identify cost-effective interventions. Policy makers should consider adopting the optimised protocol at scale if the trial demonstrates significant efficiency gains.", "key words": "surveillance evaluation