Internet search data with spatiotemporal analysis in infectious disease surveillance

Challenges and perspectives

Bibliographic Data

ID22076544
AuthorsHua Sun (0000-0003-4026-7554), Yuzhou Zhang (0000-0001-8515-3388, Zhejiang University of Science and Technology, corresponding author), Guang Gao (0000-0002-9011-9640), Dun Wu (0000-0002-4906-8263)
Year2022
Volume10
Pages958835-958835
Publication date2022-12-05
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2022.958835
PMID36544794
OpenAlexW4310672677
LanguageEN
Citations received1
References cited69

With the rapid development of the internet, the application of internet search data has been seen as a novel data source to offer timely infectious disease surveillance intelligence. Moreover, the advancements in internet search data, which include rich information at both space and time scales, enable investigators to sufficiently consider the spatiotemporal uncertainty, which can benefit researchers to better monitor infectious diseases and epidemics. In the present study, we present the necessary groundwork and critical appraisal of the use of internet search data and spatiotemporal analysis approaches in infectious disease surveillance by updating the current stage of knowledge on them. The study also provides future directions for researchers to investigate the combination of internet search data with the spatiotemporal analysis in infectious disease surveillance. Internet search data demonstrate a promising potential to offer timely epidemic intelligence, which can be seen as the prerequisite for improving infectious disease surveillance

Data science · Disease · Disease surveillance · Internet privacy · Pathology · The Internet · World Wide Web · Computer Science · COVID-19 epidemiological studies · Data-Driven Disease Surveillance · Influenza Virus Research Studies · Medicine

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Open DOIOpen Access