Evidence map›Paper›PMID 36833701›Full record

ArticleInternational journal of environmental research and public health2023

COVID-19 Related Early Google Search Behavior and Health Communication in the United States: Panel Data Analysis on Health Measures.

Binhui Wang, Beiting Liang, Qiuyi Chen, Shu Wang, Siyi Wang, Zhongguo Huang, Yi Long, Qili Wu, Shulin Xu, Pranay Jinna and 3 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2023. 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
1.3field-weighted citation impact, top 24% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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, 6 citations in OpenAlex.

  1. Review
  2. Article
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

13 authors at 6 institutions in 4 countries.

Binhui WangSchool of Management, Jinan University, Guangzhou 510632, China.
Beiting LiangCollege of Economics, Jinan University, Guangzhou 510632, China.
Qiuyi ChenSchool of Journalism, Fudan University, Shanghai 200433, China.
Shu WangInstitute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China.ORCID 0000-0003-3941-5046
Siyi WangDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
Zhongguo HuangDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
Yi LongLaw School of Artificial Intelligence, Shanghai University of Political Science and Law, Shanghai 201701, China.
Qili WuSchool of Journalism and Communication, Jinan University National Media Experimental Teaching Demonstration Center, Jinan University, Guangzhou 510632, China.
Shulin XuSchool of Economic, Guangzhou College of Commerce, Guangzhou 511363, China.
Pranay JinnaSchool of Business, University at Albany, State University of New York, Albany, NY 12222, USA.
Fan YangCommunication Department, University at Albany, State University of New York, Albany, NY 12222, USA.
Wai-Kit MingDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou 510632, China.
Qian LiuSchool of Journalism and Communication, Jinan University National Media Experimental Teaching Demonstration Center, Jinan University, Guangzhou 510632, China.ORCID 0000-0001-9070-2863
Jinan University · CNAlbany State University · USUniversity of Liège · BEFudan University · CNGuangzhou College of CommerceShanghai University of Political Science and Law · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 outbreak at the end of December 2019 spread rapidly all around the world. The objective of this study is to investigate and understand the relationship between public health measures and the development of the pandemic through Google search behaviors in the United States. Our collected data includes Google search queries related to COVID-19 from 1 January to 4 April 2020. After using unit root tests (ADF test and PP test) to examine the stationary and a Hausman test to choose a random effect model, a panel data analysis is conducted to investigate the key query terms with the newly added cases. In addition, a full sample regression and two sub-sample regressions are proposed to explain: (1) The changes in COVID-19 cases number are partly related to search variables related to treatments and medical resources, such as ventilators, hospitals, and masks, which correlate positively with the number of new cases. In contrast, regarding public health measures, social distancing, lockdown, stay-at-home, and self-isolation measures were negatively associated with the number of new cases in the US. (2) In mild states, which ranked one to twenty by the average daily new cases from least to most in 50 states, the query terms about public health measures (quarantine, lockdown, and self-isolation) have a significant negative correlation with the number of new cases. However, only the query terms about lockdown and self-isolation are also negatively associated with the number of new cases in serious states (states ranking 31 to 50). Furthermore, public health measures taken by the government during the COVID-19 outbreak are closely related to the situation of controlling the pandemic.

Indexed as

COVID-19Health CommunicationCommunicable Disease ControlHumansQuarantineSearch EngineUnited StatesCOVID-19Google trendhealth communicationpanel data analysispublic health measures

Identifiers

PMID36833701
PMCPMC9958808
OpenAlexW4319786104

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.