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Utility of Nontraditional Data Sources for Early Detection of Influenza

机译：非传统数据源在流感早期检测中的应用

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Objective This session will provide an overview of the current systems for influenza surveillance; review the role of schools in influenza transmission; discuss relationships between school closures, school absenteeism, and influenza transmission; and explore the usefulness of school absenteeism and unplanned school closure monitoring for early detection of influenza in schools and broader communities. Introduction Influenza surveillance is conducted through a complex network of laboratory and epidemiologic systems essential for estimating population burden of disease, selecting influenza vaccine viruses, and detecting novel influenza viruses with pandemic potential (1). Influenza surveillance faces numerous challenges, such as constantly changing influenza viruses, substantial variability in the number of affected people and the severity of disease, nonspecific symptoms, and need for laboratory testing to confirm diagnosis. Exploring additional components that provide morbidity information may enhance current influenza surveillance. School-aged children have the highest influenza incidence rates among all age groups. Due to the close interaction of children in schools and subsequent introduction of influenza into households, it is recognized that schools can serve as amplification points of influenza transmission in communities. For this reason, pandemic preparedness recommendations include possible pre-emptive school closures, before transmission is widespread within a school system or broader community, to slow influenza transmission until appropriate vaccines become available. During seasonal influenza epidemics, school closures are usually reactive, implemented in response to high absenteeism of students and staff after the disease is already widespread in the community. Reactive closures are often too late to reduce influenza transmission and are ineffective. To enhance timely influenza detection, a variety of nontraditional data sources have been explored. School absenteeism was suggested by several research groups to improve school-based influenza surveillance. A study conducted in Japan demonstrated that influenza- associated absenteeism can predict influenza outbreaks with high sensitivity and specificity (2). Another study found the use of all- causes absenteeism to be too nonspecific for utility in influenza surveillance (3). Creation of school-based early warning systems for pandemic influenza remains an interest, and further studies are needed. The panel will discuss how school-based surveillance can complement existing influenza surveillance systems.
机译：目的本届会议将概述当前的流感监测系统;审查学校在流感传播中的作用;讨论停课，学校旷工和流感传播之间的关系;并探讨学校旷工和计划外的停课监测对学校和更广泛社区的流感早期检测的有用性。引言流感监测是通过复杂的实验室和流行病学系统网络进行的，这些网络对于估计疾病的人口负担，选择流感疫苗病毒以及检测具有大流行潜力的新型流感病毒至关重要（1）。流感监测面临许多挑战，例如不断变化的流感病毒，受感染人数和疾病严重程度的巨大差异，非特异性症状以及需要实验室测试以确认诊断的需求。探索提供发病率信息的其他组件可能会增强当前的流感监测。在所有年龄段中，学龄儿童的流感发病率最高。由于学校中儿童的紧密互动以及随后将流感引入家庭，人们认识到学校可以作为社区中流感传播的放大点。因此，大流行的防范建议包括在学校系统或更广泛的社区广泛传播之前，可能先行关闭学校，以减慢流感的传播速度，直到获得合适的疫苗为止。在季节性流感流行期间，学校关闭通常是反应性的，是由于该疾病已经在社区中广泛传播之后，针对学生和教职员工的高缺勤而实施的。反应性封闭通常为时已晚，不足以减少流感传播，而且效果不佳。为了加强及时的流感检测，已经探索了各种非传统数据源。几个研究小组建议学校缺勤，以改善基于学校的流感监测。在日本进行的一项研究表明，与流感相关的旷工可以高灵敏度和特异性地预测流感暴发（2）。另一项研究发现，全因缺勤的使用对于在流感监测中的效用过于非特异性（3）。建立基于学校的大流行性流感预警系统仍然是人们的兴趣所在，需要进一步研究。小组将讨论基于学校的监视如何补充现有的流感监视系统。

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