Evidence map›Paper›PMID 33734846›Full record

ArticleAmerican journal of public health2021

Sinophobic Stigma Going Viral: Addressing the Social Impact of COVID-19 in a Globalized World.

Anahí Viladrich

Open access · greenAbstract read
In one paragraph

Article in American journal of public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

17 citing papers in PubMed, 54 citations in OpenAlex.

  1. Article
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  3. COVID-19 Racism and Chinese American Families' Mental Health: A Comparison between 2020 and 2021.International journal of environmental research and public health · 2023
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  15. Pervasive systemic drivers underpin COVID-19 vulnerabilities in migrants.International journal for equity in health · 2021
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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

1 author at 1 institution in 1 country.

Anahí ViladrichAnahí Viladrich is with the Department of Sociology and Department of Anthropology, Queens College, and the Graduate Center and the Graduate School of Public Health and Health Policy of the City University of New York (CUNY), New York, NY.
The Graduate Center, CUNY · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article critically examines the recent literature on stigma that addresses the overspread association among the COVID-19 pandemic and racial and ethnic groups (i.e., mainland Chinese and East Asian populations) assumed to be the source of the virus.The analysis begins by reviewing the way in which infectious diseases have historically been associated with developing countries and their citizens, which, in turn, are supposed to become prime vectors of contagion. The latter extends to the current labeling of COVID-19 as the "Chinese virus," that-along with a number of other terms-has fueled race-based stigma against Asian groups in the United States and overseas. This review further discusses the limitations of current COVID-19 antistigma initiatives that mostly focus on individual-based education campaigns as opposed to multisectorial programs informed by human rights and intersectional perspectives.Finally, the article ends with a call to the international public health community toward addressing the most recent outbreak of stigma, one that has revealed the enormous impact of words in amplifying racial bias against particular minority populations in the developed world.

Indexed as

Asian PeopleCOVID-19EthnicityRacismSocial ChangeSocial StigmaHealth EducationHumansInternationalityUnited States

Identifiers

PMID33734846
PMCPMC8034019
OpenAlexW3138642516

What OpenQuestion holds

Textmetadata
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.