Department of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, Canada.
Lancet Infect Dis. 2012 Mar;12(3):222-30. doi: 10.1016/S1473-3099(11)70313-9. Epub 2012 Jan 16.
Infectious disease surveillance for mass gatherings (MGs) can be directed locally and globally; however, epidemic intelligence from these two levels is not well integrated. Modelling activities related to MGs have historically focused on crowd behaviours around MG focal points and their relation to the safety of attendees. The integration of developments in internet-based global infectious disease surveillance, transportation modelling of populations travelling to and from MGs, mobile phone technology for surveillance during MGs, metapopulation epidemic modelling, and crowd behaviour modelling is important for progress in MG health. Integration of surveillance across geographic frontiers and modelling across scientific specialties could produce the first real-time risk monitoring and assessment platform that could strengthen awareness of global infectious disease threats before, during, and immediately after MGs. An integrated platform of this kind could help identify infectious disease threats of international concern at the earliest stages possible; provide insights into which diseases are most likely to spread into the MG; help with anticipatory surveillance at the MG; enable mathematical modelling to predict the spread of infectious diseases to and from MGs; simulate the effect of public health interventions aimed at different local and global levels; serve as a foundation for scientific research and innovation in MG health; and strengthen engagement between the scientific community and stakeholders at local, national, and global levels.
传染病监测对于大型集会(MGs)可以在本地和全球范围内进行;然而,这两个层面的流行情报并没有很好地整合。与 MGs 相关的建模活动历史上集中在 MG 焦点周围的人群行为及其与参与者安全的关系上。整合基于互联网的全球传染病监测、前往和离开 MGs 的人群的交通建模、MG 期间的移动电话技术监测、混合种群传染病建模和人群行为建模的发展对于 MGs 健康的进展非常重要。跨越地理边界的监测整合和跨越科学专业的建模可以产生第一个实时风险监测和评估平台,该平台可以在 MGs 之前、期间和之后立即加强对全球传染病威胁的认识。这种集成平台可以帮助在最早阶段识别出国际关注的传染病威胁;洞察哪些疾病最有可能传播到 MG;帮助在 MG 进行预期监测;使数学建模能够预测传染病在 MG 内外的传播;模拟针对不同地方和全球各级的公共卫生干预措施的效果;作为 MG 健康科学研究和创新的基础;并加强地方、国家和全球各级科学界和利益相关者之间的参与。