论文标题
使用搜索查询日志和用户位置信息的综合征监视来自日本Covid-19群集的智能手机信息
Syndromic surveillance using search query logs and user location information from smartphones against COVID-19 clusters in Japan
论文作者
论文摘要
[背景] 2019年2月在日本北海道证实了冠状病毒病的两个簇（Covid-19）。为了捕获簇，本研究采用了网络搜索查询日志和用户位置信息，来自智能手机。 [材料和方法]首先，我们匿名确定了使用Web搜索引擎（Yahoo！Japan Search）进行COVID-19或其症状的智能手机用户（Yahoo Japan App）。我们将这些搜索者视为怀疑自己的Covid-19感染（WSSCI）的网络搜索者。其次，我们通过智能手机应用程序提取了WSSCI的位置。将WSSCI数量的时空分布与已知两个簇的实际位置进行了比较。 [结果和讨论]在集群开发的早期阶段之前，我们可以确认几个WSSCI，这证明了我们基于WSSCI的方法的基本可行性。但是，它仅在早期才是准确的，并且在公开宣布集群开发之后，它才有偏见。对于其他与集群相关的资源（例如细粒度统计数据）的情况，拟议的指标将有助于捕捉新兴集群的暗示。
[Background] Two clusters of coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan in February 2020. To capture the clusters, this study employs Web search query logs and user location information from smartphones. [Material and Methods] First, we anonymously identified smartphone users who used a Web search engine (Yahoo! JAPAN Search) for the COVID-19 or its symptoms via its companion application for smartphones (Yahoo Japan App). We regard these searchers as Web searchers who are suspicious of their own COVID-19 infection (WSSCI). Second, we extracted the location of the WSSCI via the smartphone application. The spatio-temporal distribution of the number of WSSCI are compared with the actual location of the known two clusters. [Result and Discussion] Before the early stage of the cluster development, we could confirm several WSSCI, which demonstrated the basic feasibility of our WSSCI-based approach. However, it is accurate only in the early stage, and it was biased after the public announcement of the cluster development. For the case where the other cluster-related resources, such as fine-grained population statistics, are not available, the proposed metric would be helpful to catch the hint of emerging clusters.
