Risk level scoring criteria.
收藏Figshare2026-01-09 更新2026-04-28 收录
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BackgroundTo 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.MethodA 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.ResultThe 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.ConclusionThe 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.
创建时间:
2026-01-09



