Evidence-based decision-making support for determining the risk of schistosomiasis infection during large events in China: Application of risk assessment

Abstract

Background To investigate the application of risk assessment in decision-making support for disease prevention and control during large-scale events involving schistosomiasis, a rapid system and process for assessing the risk of schistosomiasis transmission were developed. Method A risk assessment indicator framework was developed through literature reviews and the Delphi method. Risk level determination was assessed using the Delphi method and a risk matrix method. Control measures were implemented based on the risk levels determination. Effectiveness evaluation was verified by monitoring schistosomiasis-related public health incidents and tracking key indicators—including oncomelania snail infection prevalence, snail density, human and livestock infection rates, wild feces detection, and sentinel mouse infection—over 1–3 years post-event, supplemented by repeated risk assessments. Result The decision-making support system for schistosomiasis transmission prevention and control during large-scale events comprises a database of recent schistosomiasis cases, onsite schistosomiasis transmission risk monitoring, a case database of outbreaks, a database of assessment experts, a database of the distribution of oncomelania snail, a library of professional strategies, and a preplan. This system encompasses four processes, namely, identification of high-risk factors, risk assessment to determine areas with high, medium and low risk levels, implementation of targeted risk management and control measures, and evaluation of long-term effects. Conclusion The risk assessment system was successfully applied to three large-scale events in Wuhan, effectively supporting evidence-based decision-making support and preventing schistosomiasis transmission. Post-event surveillance and reassessment of indicators verified the sustained effectiveness of the interventions. This closed-loop approach demonstrates that risk assessment is a vital tool for public health decision-making during large events in endemic areas.