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Why inequality could spread COVID-19
Open accessAbstract
Pandemics rarely affect all people in a uniform way. The Black Death in the 14th century reduced the global population by a third, with the highest number of deaths observed among the poorest populations.1 Densely populated with malnourished and overworked peasants, medieval Europe was a fertile breeding ground for the bubonic plague. Seven centuries on—with a global gross domestic product of almost US$100 trillion—is our world adequately resourced to prevent another pandemic?2 Current evidence from the coronavirus disease 2019 (COVID-19) pandemic would suggest otherwise.
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“As the economic consequences of COVID-19 have continued to unfold, it has become clear that individuals from lower socioeconomic background have been disproportionately burdened across the globe [1, 12].”
From Psychiatric symptoms, risk, and protective factors among university students in quarantine during the COVID-19 pandemic in China (2021) · cites this paper as [1]
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Metadata
- Authors
- Ahmed, F., Ahmed, N., Pissarides, C., & Stiglitz, J.
- Affiliations
- NHS England (GB)
- London School of Economics and Political Science (GB)
- Columbia University (US)
- Corresponding author
- Ahmed, Faheem
- Venue
- The Lancet Public Health
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 5
- Issue
- 5
- Pages
- e240
- ISSN
- 2468-2667 (ISSN-L)
- PMC
- PMC7270465
- OpenAlex
- W3013942622
- Cited by
- 788
- References
- 3
- Citations by year
- 2026: 13 · 2025: 38 · 2024: 61 · 2023: 78 · 2022: 146 · 2021: 246 · 2020: 203
- FWCI
- 26.75
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Public Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- London School of Economics and Political Science Research Online (London School of Economics and Political Science) (submittedVersion)
- London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Health › Public Health and Social Inequalities
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- COVID-19 pandemic, socioeconomic disparities, pandemic spread, health disparities, poverty, pandemic preparedness, public health resources
- MeSH terms
- COVID-19, Humans, Pneumonia, Viral, Socioeconomic Factors, Coronavirus Infections, Health Status Disparities, Pandemics
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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