Sorbonne Université, INSERM, Institut Pierre Louis d'Epidémiologie et de Santé Publique (IPLESP), Paris, France.
UFR des sciences de la santé Simone-Veil, Université Versailles-Saint-Quentin-en-Yvelines, Versailles, France.
Euro Surveill. 2018 Jun;23(25). doi: 10.2807/1560-7917.ES.2018.23.25.1700337.
IntroductionParticipatory surveillance systems provide rich crowdsourced data, profiling individuals and their health status at a given time. We explored the usefulness of data from GrippeNet.fr, a participatory surveillance system, to estimate influenza-related illness incidence in France. GrippeNet.fr is an online cohort since 2012 averaging ca. 5,000 weekly participants reporting signs/symptoms suggestive of influenza. GrippeNet.fr has flexible criteria to define influenza-related illness. Different case definitions based on reported signs/symptoms and inclusions of criteria accounting for individuals' reporting and participation were used to produce influenza-related illness incidence estimates, which were compared to those from sentinel networks. We focused on the 2012/13 and 2013/14 seasons when two sentinel networks, monitoring influenza-like-illness (ILI) and acute respiratory infections (ARI) existed in France. : GrippeNet.fr incidence estimates agreed well with official temporal trends, with a higher accuracy for ARI than ILI. The influenza epidemic peak was often anticipated by one week, despite irregular participation of individuals. The European Centre for Disease Prevention and Control ILI definition, commonly used by participatory surveillance in Europe, performed better in tracking ARI than ILI when applied to GrippeNet.fr data. : Evaluation of the epidemic intensity from crowdsourced data requires epidemic and intensity threshold estimations from several consecutive seasons. The study provides a standardised analytical framework for crowdsourced surveillance showing high sensitivity in detecting influenza-related changes in the population. It contributes to improve the comparability of epidemics across seasons and with sentinel systems. In France, GrippeNet.fr may supplement the ILI sentinel network after ARI surveillance discontinuation in 2014.
引言
参与式监测系统提供了丰富的众包数据,可以在特定时间内对个人及其健康状况进行分析。我们探讨了利用参与式监测系统 GrippeNet.fr 来估计法国流感相关疾病发病率的有效性。GrippeNet.fr 是一个自 2012 年以来的在线队列,每周平均约有 5000 名参与者报告提示流感的体征/症状。GrippeNet.fr 对流感相关疾病的定义较为灵活。我们使用了不同的病例定义,这些定义基于报告的体征/症状,并纳入了考虑个体报告和参与情况的标准,以生成流感相关疾病发病率估计值,并与哨点网络进行比较。我们重点关注了 2012/13 年和 2013/14 年两个流感季节,当时法国存在两个监测流感样疾病(ILI)和急性呼吸道感染(ARI)的哨点网络。
结果
GrippeNet.fr 的发病率估计值与官方时间趋势吻合较好,ARI 的准确性高于 ILI。尽管个体参与情况不规则,但流感流行高峰通常会提前一周出现。欧洲疾病预防控制中心 ILI 定义,在欧洲参与式监测中被广泛应用,在应用于 GrippeNet.fr 数据时,比 ILI 更能准确跟踪 ARI。
结论
从众包数据评估疫情强度需要对多个连续季节的疫情和强度阈值进行估计。该研究提供了一个标准化的分析框架,用于众包监测,在检测人群中流感相关变化方面具有较高的敏感性。它有助于提高跨季节和与哨点系统的疫情可比性。在法国,GrippeNet.fr 可能会在 2014 年停止急性呼吸道感染监测后,补充 ILI 哨点网络。