Coordinating the real-time use of global influenza activity data for better public health planning
Coordinating the real-time use of global influenza activity data for better public health planning
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DOI：
10.1111/irv.12705
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发表时间：
2019-12-03
影响因子：
4.4
通讯作者：
Wu, Joseph T.
中科院分区：
文献类型：
--
作者：
Biggerstaff, Matthew;Dahlgren, Fredrick Scott;Wu, Joseph T.
从全球到地方各级的卫生规划人员在规划和应对流行病时必须预测季节性流感活动的年与年和周与周的变化，以减轻其影响。为了帮助做到这一点，各国定期收集轻度和重度呼吸道疾病的发病率以及关于流行亚型的病毒学数据，并利用这些数据进行情况了解、疾病负担估计和严重程度评估。先进的分析和建模越来越多地用于帮助规划和应对活动，描述特定地点流感活动的关键特征，并生成预测，这些预测可以转化为有用的行动，例如加强风险沟通，并通知临床供应链。在此，我们介绍了流感发病率分析小组（IIAG）的成立，这是一项全球协调努力，旨在将先进的分析和建模应用于实时的流行病学和病毒学公共流感数据，从而为向世卫组织提供常规监测数据的国家提供更多见解。我们的目标是通过应用先进的分析和预测，系统地增加数据对健康规划师的价值，并使用开放的数据和代码库立即复制和部署结果。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早期阶段的关键流行病学数据的开放分析提供一个有吸引力的选择。
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.