Evidence map›Paper›PMID 34174781›Full record

ArticleJMIR public health and surveillance2021

Measuring Public Concern About COVID-19 in Japanese Internet Users Through Search Queries: Infodemiological Study.

Zhiwei Gao, Sumio Fujita, Nobuyuki Shimizu, Kongmeng Liew, Taichi Murayama, Shuntaro Yada, Shoko Wakamiya, Eiji Aramaki

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Zhiwei GaoSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0002-8759-9305
Sumio FujitaYahoo Japan Corporation, Tokyo, Japan.ORCID 0000-0002-1282-386X
Nobuyuki ShimizuYahoo Japan Corporation, Tokyo, Japan.ORCID 0000-0001-6767-3662
Kongmeng LiewSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0002-0755-7173
Taichi MurayamaSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0003-1148-711X
Shuntaro YadaSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0002-6209-1054
Shoko WakamiyaSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0002-9371-1340
Eiji AramakiSocial Computing Laboratory, Graduate School of Science and Technology, Nara Institute of Science and Technology, Ikoma, Japan.ORCID 0000-0003-0201-3609

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 has disrupted lives and livelihoods and caused widespread panic worldwide. Emerging reports suggest that people living in rural areas in some countries are more susceptible to COVID-19. However, there is a lack of quantitative evidence that can shed light on whether residents of rural areas are more concerned about COVID-19 than residents of urban areas.

objectiveThis infodemiology study investigated attitudes toward COVID-19 in different Japanese prefectures by aggregating and analyzing Yahoo! JAPAN search queries.

methodsWe measured COVID-19 concerns in each Japanese prefecture by aggregating search counts of COVID-19-related queries of Yahoo! JAPAN users and data related to COVID-19 cases. We then defined two indices-the localized concern index (LCI) and localized concern index by patient percentage (LCIPP)-to quantitatively represent the degree of concern. To investigate the impact of emergency declarations on people's concerns, we divided our study period into three phases according to the timing of the state of emergency in Japan: before, during, and after. In addition, we evaluated the relationship between the LCI and LCIPP in different prefectures by correlating them with prefecture-level indicators of urbanization.

resultsOur results demonstrated that the concerns about COVID-19 in the prefectures changed in accordance with the declaration of the state of emergency. The correlation analyses also indicated that the differentiated types of public concern measured by the LCI and LCIPP reflect the prefectures' level of urbanization to a certain extent (ie, the LCI appears to be more suitable for quantifying COVID-19 concern in urban areas, while the LCIPP seems to be more appropriate for rural areas).

conclusionsWe quantitatively defined Japanese Yahoo users' concerns about COVID-19 by using the search counts of COVID-19-related search queries. Our results also showed that the LCI and LCIPP have external validity.

Indexed as

Attitude to HealthAdultAgedAnxietyCOVID-19FemaleHumansInternetJapanMaleMiddle AgedRural PopulationSearch EngineUrban PopulationattitudeconcernCOVID-19infodemiologyinformation-seeking behaviorInternetJapanquantitative analysisruralsearch queryurban

Identifiers

PMID34174781
PMCPMC8294121

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.