Nikolay Birgit, Salje Henrik, Khan A K M Dawlat, Sazzad Hossain M S, Satter Syed M, Rahman Mahmudur, Doan Stephanie, Knust Barbara, Flora Meerjady Sabrina, Luby Stephen P, Cauchemez Simon, Gurley Emily S
Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, CNRS, Paris, France.
Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
J Infect Dis. 2020 May 11;221(Suppl 4):S363-S369. doi: 10.1093/infdis/jiaa074.
It is of uttermost importance that the global health community develops the surveillance capability to effectively monitor emerging zoonotic pathogens that constitute a major and evolving threat for human health. In this study, we propose a comprehensive framework to measure changes in (1) spillover risk, (2) interhuman transmission, and (3) morbidity/mortality associated with infections based on 6 epidemiological key indicators derived from routine surveillance. We demonstrate the indicators' value for the retrospective or real-time assessment of changes in transmission and epidemiological characteristics using data collected through a long-standing, systematic, hospital-based surveillance system for Nipah virus in Bangladesh. We show that although interhuman transmission and morbidity/mortality indicators were stable, the number and geographic extent of spillovers varied significantly over time. This combination of systematic surveillance and active tracking of transmission and epidemiological indicators should be applied to other high-risk emerging pathogens to prevent public health emergencies.
全球卫生界发展监测能力,以有效监测对人类健康构成重大且不断演变威胁的新发人畜共患病原体,这至关重要。在本研究中,我们提出了一个综合框架,用于基于从常规监测中得出的6个流行病学关键指标来衡量(1)溢出风险、(2)人际传播以及(3)与感染相关的发病率/死亡率的变化。我们利用通过孟加拉国一个长期、系统的基于医院的尼帕病毒监测系统收集的数据,展示了这些指标在回顾性或实时评估传播和流行病学特征变化方面的价值。我们表明,尽管人际传播和发病率/死亡率指标稳定,但溢出事件的数量和地理范围随时间有显著变化。这种系统监测与对传播和流行病学指标的主动跟踪相结合的方法,应应用于其他高风险的新发病原体,以预防突发公共卫生事件。