Evidence map›Paper›PMID 35958849›Full record

ArticleFrontiers in public health2022

Spatiotemporal evolution of online attention to vaccines since 2011: An empirical study in China.

Feng Hu, Liping Qiu, Wei Xia, Chi-Fang Liu, Xun Xi, Shuang Zhao, Jiaao Yu, Shaobin Wei, Xiao Hu, Ning Su and 3 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

13 citing papers in PubMed.

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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

13 authors.

Feng HuGlobal Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
Liping QiuGlobal Value Chain Research Center, Zhejiang Gongshang University, Hangzhou, China.
Wei XiaInstitute of International Business and Economics Innovation and Governance, Shanghai University of International Business and Economics, Shanghai, China.
Chi-Fang LiuDepartment of Business Administration, Cheng Shiu University, Kaohsiung, Taiwan.
Xun XiSchool of Management, Shandong Technology and Business University, Yantai, China.
Shuang ZhaoBusiness School, Hohai University, Nanjing, China.
Jiaao YuLondon College of Communication, University of the Arts London, London, United Kingdom.
Shaobin WeiInstitute of Spatial Planning & Design, Zhejiang University City College, Hangzhou, China.
Xiao HuCash Crop Workstation, Shangcheng Bureau of Agriculture and Rural Affairs, Shangcheng, China.
Ning SuSchool of MBA, Zhejiang Gongshang University, Hangzhou, China.
Tianyu HuSchool of Information Engineering, Zhengzhou University, Zhengzhou, China.
Haiyan ZhouInstitute of Artificial Intelligence and Change Management, Shanghai University of International Business and Economics, Shanghai, China.
Zhuang JinBaotou Teachers' College, Inner Mongolia University of Science & Technology, Baotou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the outbreak of Coronavirus Disease 2019 (COVID-19), the Chinese government has taken a number of measures to effectively control the pandemic. By the end of 2021, China achieved a full vaccination rate higher than 85%. The Chinese Plan provides an important model for the global fight against COVID-19. Internet search reflects the public's attention toward and potential demand for a particular thing. Research on the spatiotemporal characteristics of online attention to vaccines can determine the spatiotemporal distribution of vaccine demand in China and provides a basis for global public health policy making. This study analyzes the spatiotemporal characteristics of online attention to vaccines and their influencing factors in 31 provinces/municipalities in mainland China with Baidu Index as the data source by using geographic concentration index, coefficient of variation, GeoDetector, and other methods. The following findings are presented. First, online attention to vaccines showed an overall upward trend in China since 2011, especially after 2016. Significant seasonal differences and an unbalanced monthly distribution were observed. Second, there was an obvious geographical imbalance in online attention to vaccines among the provinces/municipalities, generally exhibiting a spatial pattern of "high in the east and low in the west." Low aggregation and obvious spatial dispersion among the provinces/municipalities were also observed. The geographic distribution of hot and cold spots of online attention to vaccines has clear boundaries. The hot spots are mainly distributed in the central-eastern provinces and the cold spots are in the western provinces. Third, the spatiotemporal differences in online attention to vaccines are the combined result of socioeconomic level, socio-demographic characteristics, and disease control level.

Indexed as

COVID-19VaccinesChinaDisease OutbreaksHumansPandemicsVaccinesGeoDetectoronline attentionpublic healthspatiotemporal characteristicsvaccine

Identifiers

PMID35958849
PMCPMC9360794

What Socratic holds

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LicenceCC BY
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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 Socratic graph.