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Coordinating the real‐time use of global influenza activity data for better public health planning

机译:协调实时使用全球流感活动数据以更好地进行公共卫生计划

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摘要

Health planners from global to local levels must anticipate year‐to‐year and week‐to‐week variation in seasonal influenza activity when planning for and responding to epidemics to mitigate their impact. To help with this, countries routinely collect incidence of mild and severe respiratory illness and virologic data on circulating subtypes and use these data for situational awareness, burden of disease estimates and severity assessments. Advanced analytics and modelling are increasingly used to aid planning and response activities by describing key features of influenza activity for a given location and generating forecasts that can be translated to useful actions such as enhanced risk communications, and informing clinical supply chains. Here, we describe the formation of the Influenza Incidence Analytics Group (IIAG), a coordinated global effort to apply advanced analytics and modelling to public influenza data, both epidemiological and virologic, in real‐time and thus provide additional insights to countries who provide routine surveillance data to WHO. Our objectives are to systematically increase the value of data to health planners by applying advanced analytics and forecasting and for results to be immediately reproducible and deployable using an open repository of data and code. We expect the resources we develop and the associated community to provide an attractive option for the open analysis of key epidemiological data during seasonal epidemics and the early stages of an influenza pandemic.
机译:从全球到地方级别的卫生计划人员,在计划和应对流行病以减轻其影响时,必须预测季节性流感活动的逐年和逐周变化。为此,各国会定期收集轻度和重度呼吸道疾病的发病率以及循环亚型的病毒学数据,并将这些数据用于态势感知,疾病负担估算和严重性评估。先进的分析和建模越来越多地用于通过描述给定位置的流感活动的关键特征并生成可以转化为有用行动(例如增强的风险沟通和通知临床供应链)的预测来辅助计划和响应活动。在这里,我们描述了流感发病率分析小组(IIAG)的成立,这是一项协调一致的全球性工作,旨在将高级分析和建模实时应用于流行病学和病毒学的公共流感数据,从而为提供常规服务的国家提供更多见解向世卫组织提供监测数据。我们的目标是通过应用高级分析和预测来系统地增加数据对健康计划人员的价值,并使用开放的数据和代码存储库立即再现和部署结果。我们希望我们开发的资源和相关社区能够为季节性流行病和流感大流行的早期阶段的关键流行病学数据的开放分析提供有吸引力的选择。

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