Surveillance of early stage COVID-19 clusters using search query logs and mobile device-based location information.
Sci Rep
; 10(1): 18680, 2020 10 29.
Article
in English
| MEDLINE | ID: covidwho-894421
ABSTRACT
Two clusters of the coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan, in February 2020. To identify these clusters, this study employed web search query logs of multiple devices and user location information from location-aware mobile devices. We anonymously identified users who used a web search engine (i.e., Yahoo! JAPAN) to search for COVID-19 or its symptoms. We regarded them as web searchers who were suspicious of their own COVID-19 infection (WSSCI). We extracted the location of WSSCI via a mobile operating system application and compared the spatio-temporal distribution of WSSCI with the actual location of the two known clusters. In the early stage of cluster development, we confirmed several WSSCI. Our approach was accurate in this stage and became biased after a public announcement of the cluster development. When other cluster-related resources, such as detailed population statistics, are not available, the proposed metric can capture hints of emerging clusters.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Population Surveillance
/
Infection Control
/
Coronavirus Infections
/
Search Engine
/
Epidemiological Monitoring
/
Smartphone
Type of study:
Observational study
Limits:
Humans
Country/Region as subject:
Asia
Language:
English
Journal:
Sci Rep
Year:
2020
Document Type:
Article
Affiliation country:
S41598-020-75771-6
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