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arXiv · 2004.10100

Syndromic surveillance using search query logs and user location information from smartphones against COVID-19 clusters in Japan

Shohei Hisada·Taichi Murayama·Kota Tsubouchi·Sumio Fujita·Shuntaro Yada·Shoko Wakamiya·Eiji Aramaki
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Abstract

[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.

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Shohei Hisada, Taichi Murayama, Kota Tsubouchi, Sumio Fujita, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki. 2020-04-21. Syndromic surveillance using search query logs and user location information from smartphones against COVID-19 clusters in Japan. https://doi.org/10.1038/s41598-020-75771-6

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