Fear and Stigma: The Epidemic within the SARS Outbreak
Open accessAbstract
Because of their evolving nature and inherent scientific uncertainties, outbreaks of emerging infectious diseases can be associated with considerable fear in the general public or in specific communities, especially when illness and deaths are substantial. Mitigating fear and discrimination directed toward persons infected with, and affected by, infectious disease can be important in controlling transmission. Persons who are feared and stigmatized may delay seeking care and remain in the community undetected. This article outlines efforts to rapidly assess, monitor, and address fears associated with the 2003 severe acute respiratory syndrome (SARS) epidemic in the United States. Although fear, stigmatization, and discrimination were not widespread in the general public, Asian-American communities were particularly affected.
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The early phase of an emerging outbreak tends to be characterized by intense disease-related stigma and fear due to its evolving nature and scientific uncertainties.
“Stigma was also examined as a potential factor related to mental health problems, as the early phase of an emerging outbreak tends to be characterized by intense disease-related stigma and fear due to its evolving nature and scientific uncertainties [20, 48].”
From Psychiatric symptoms, risk, and protective factors among university students in quarantine during the COVID-19 pandemic in China (2021) · cites this paper as [48]
Belief in one's capacity to prevent COVID-19 and take necessary steps for treatment may facilitate an increased sense of control in an evolving outbreak.
“COVID-19 self-efficacy was explored as a predictor of mental health, as belief in one’s capacity to prevent COVID-19 and take necessary steps for treatment may facilitate an increased sense of control in an evolving outbreak [48].”
From Psychiatric symptoms, risk, and protective factors among university students in quarantine during the COVID-19 pandemic in China (2021) · cites this paper as [48]
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- Authors
- Person, B., Sy, F., Holton, K., Govert, B., Liang, A., the, N. C. I. D., SARS Community Outreach Team (listed in alphabetical order), Garza, B., Gould, D., Hickson, M., McDonald, M., Meijer, C., Smith, J., Veto, L., Williams, W., & Zauderer, L.
- Affiliations
- Centers for Disease Control and Prevention (US)
- Corresponding author
- Person, Bobbie
- Venue
- Emerging Infectious Diseases
- Published
- 2004-02
- Volume
- 10
- Issue
- 2
- Pages
- 358-363
- ISSN
- 1080-6040 (ISSN-L)
- 1080-6059
- PMC
- PMC3322940
- OpenAlex
- W2079929038
- Cited by
- 790
- References
- 19
- Citations by year
- 2026: 12 · 2025: 17 · 2024: 46 · 2023: 64 · 2022: 140 · 2021: 229 · 2020: 194 · 2019: 6 · 2018: 5 · 2017: 10 · 2016: 3 · 2015: 8 · 2014: 4 · 2013: 6 · 2012: 4
- FWCI
- 8.05
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Emerging infectious diseases (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Centers for Disease Control and Prevention
- Topics
- Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
- Social Sciences › Sociology and Political Science › Risk Perception and Management
- Health Sciences › Medicine › Infectious Diseases › Viral Infections and Outbreaks Research
- Keywords
- SARS, SARS epidemic, fear, stigma, discrimination, Asian American community, delayed care seeking, transmission control, public health response
- MeSH terms
- Asian, Centers for Disease Control and Prevention, U.S., Community-Institutional Relations, Disease Outbreaks, Fear, Health Education, Humans, Prejudice, United States, Severe Acute Respiratory Syndrome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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