A Randomised Field Trial Evaluating Surveillance System Methodologies for Communicable Disease Risk Reduction in Kenya

{ "background": "Communicable disease surveillance in sub-Saharan Africa faces challenges in timeliness and data quality, impacting outbreak response. The comparative effectiveness of different surveillance methodologies for reducing community-level disease risk is not well established through rigorous field trials.", "purpose and objectives": "This study aimed to evaluate the impact of three distinct surveillance system methodologies—community health worker-led syndromic reporting, facility-based laboratory-confirmed reporting, and a hybrid mobile health (mHealth) tool—on reducing the incidence of acute febrile illness at the community level.", "methodology": "A three-arm, cluster-randomised field trial was conducted across 120 community units. The primary outcome was the community-based incidence of acute febrile illness, measured through active monthly household surveys. A negative binomial regression model was fitted: log(E(Yij)) = \β0 + \β1 X1ij + \β2 X2ij + log(Pij) + uj, where Yij is the case count, X1 and X2 are intervention indicators, Pij is the population offset, and uⱼ is a cluster-level random effect.", "findings": "The mHealth hybrid system was associated with a 32% reduction (incidence rate ratio 0.68, 95% CI: 0.52 to 0.89) in febrile illness incidence compared to the facility-based control arm. The community health worker syndromic arm showed a non-significant 15% reduction (IRR 0.85, 95% CI: 0.70 to 1.04).", "conclusion": "A surveillance system integrating mHealth tools for community-based reporting significantly reduced the incidence of acute febrile illness, whereas syndromic reporting alone did not yield a statistically significant effect.", "recommendations": "National surveillance programmes should prioritise investment in integrated mHealth platforms that link community symptom reporting with