Evidence map›Paper›PMID 32783794›Full record

ArticleThe American journal of tropical medicine and hygiene2020

COVID-19-Related Infodemic and Its Impact on Public Health: A Global Social Media Analysis.

Md Saiful Islam, Tonmoy Sarkar, Sazzad Hossain Khan, Abu-Hena Mostofa Kamal, S M Murshid Hasan, Alamgir Kabir, Dalia Yeasmin, Mohammad Ariful Islam, Kamal Ibne Amin Chowdhury, Kazi Selim Anwar and 2 more

Abstract read
In one paragraph

Article in The American journal of tropical medicine and hygiene, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 347 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
347citing papers in PubMed, 6 pooled it
–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

347 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  5. Infodemics and health misinformation: a systematic review of reviews.Bulletin of the World Health Organization · 2022
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287 more citing papers are in PubMed but not listed here.

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

12 authors.

Md Saiful Islam1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Tonmoy Sarkar1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Sazzad Hossain Khan1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Abu-Hena Mostofa Kamal3Khulna University of Engineering and Technology, Khulna, Bangladesh.
S M Murshid Hasan4Mahidol University, Nakhon Pathom, Thailand.
Alamgir Kabir2School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia.
Dalia Yeasmin1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Mohammad Ariful Islam1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Kamal Ibne Amin Chowdhury1Program for Emerging Infections, Infectious Diseases Division, icddr,b, Dhaka, Bangladesh.
Kazi Selim Anwar6Department of Infectious Diseases and Microbiology, School of Medicine, International University of Health and Welfare, Narita, Japan.
Abrar Ahmad Chughtai2School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia.
Holly Seale2School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Infodemics, often including rumors, stigma, and conspiracy theories, have been common during the COVID-19 pandemic. Monitoring social media data has been identified as the best method for tracking rumors in real time and as a possible way to dispel misinformation and reduce stigma. However, the detection, assessment, and response to rumors, stigma, and conspiracy theories in real time are a challenge. Therefore, we followed and examined COVID-19-related rumors, stigma, and conspiracy theories circulating on online platforms, including fact-checking agency websites, Facebook, Twitter, and online newspapers, and their impacts on public health. Information was extracted between December 31, 2019 and April 5, 2020, and descriptively analyzed. We performed a content analysis of the news articles to compare and contrast data collected from other sources. We identified 2,311 reports of rumors, stigma, and conspiracy theories in 25 languages from 87 countries. Claims were related to illness, transmission and mortality (24%), control measures (21%), treatment and cure (19%), cause of disease including the origin (15%), violence (1%), and miscellaneous (20%). Of the 2,276 reports for which text ratings were available, 1,856 claims were false (82%). Misinformation fueled by rumors, stigma, and conspiracy theories can have potentially serious implications on the individual and community if prioritized over evidence-based guidelines. Health agencies must track misinformation associated with the COVID-19 in real time, and engage local communities and government stakeholders to debunk misinformation.

Indexed as

BetacoronavirusCoronavirus InfectionsPandemicsPneumonia, ViralPublic HealthSocial MediaCOVID-19Data AnalysisData CollectionGlobal HealthHumansRetrospective StudiesSARS-CoV-2Social DiscriminationSocial Stigma

Identifiers

PMID32783794
PMCPMC7543839

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.