Herd immunity – estimating the level required to halt the COVID-19 epidemics in affected countries
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In both countries, as of September 2020, fewer people would 'definitely' take a COVID-19 vaccine than is likely required for herd immunity.
“Here we show that in both countries-as of September 2020-fewer people would 'definitely' take a vaccine than is likely required for herd immunity”
From Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA (2021) · cites this paper as [15]
The paper’s main text gives a formula for the minimum population immunity needed to halt spread, and Table 1 estimates thresholds for countries using data as of 13 March 2020. It does not report September 2020 vaccine willingness, whether people would ‘definitely’ take a vaccine, or a comparison between willingness and those thresholds in the two countries. (LLM, conf=0.88)
Experimental — accuracy not yet measuredA novel COVID-19 vaccine will need to be accepted by at least 55% of the population to provide herd immunity, with estimates reaching as high as 85% depending on country and infection rate.
“It is estimated that a novel COVID-19 vaccine will need to be accepted by at least 55% of the population to provide herd immunity, with estimates reaching as high as 85% depending on country and infection rate 15,16 .”
From Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA (2021) · cites this paper as [15]
In the main text (page unavailable), the paper defines a critical level of population immunity that can be acquired through vaccination or infection. Table 1 reports country-specific thresholds, including 85.0% for Bahrain. It does not estimate vaccine acceptance, and the passages in our copy do not establish a 55% minimum; acceptance cannot be equated with immunity without accounting for vaccine effectiveness. (LLM, conf=0.82)
Experimental — accuracy not yet measured
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Cites
Infectious Diseases of Humans: Dynamics and Control
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How generation intervals shape the relationship between growth rates and reproductive numbers
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Serial interval of novel coronavirus (COVID-19) infections
Nishiura, H., Linton, N. M., & Akhmetzhanov, A. R. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.02.060 · Cited by 1,064 · see citing works
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Case-Fatality Risk Estimates for COVID-19 Calculated by Using a Lag Time for Fatality
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Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA
Loomba, S., de Figueiredo, A., Piatek, S. J., de Graaf, K., & Larson, H. J. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01056-1 · Cited by 1,800 · see citing works
Kost, G. J. (2021) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2020-0716-sa · Cited by 23 · see citing works
- Authors
- Kwok, K. O., Lai, F., Wei, W. I., Wong, S. Y. S., & Tang, J. W. T.
- Affiliations
- Chinese University of Hong Kong (HK)
- University of Leicester (GB)
- Corresponding author
- Kwok, Kin On
- Tang, Julian W.T.
- Venue
- Journal of Infection
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 80
- Issue
- 6
- Pages
- e32-e33
- ISSN
- 0163-4453 (ISSN-L)
- PMC
- PMC7151357
- OpenAlex
- W3012844399
- Cited by
- 499
- References
- 7
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 17 · 2023: 40 · 2022: 90 · 2021: 182 · 2020: 161
- FWCI
- 18.80
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Infection (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Keywords
- herd immunity, COVID-19 pandemic, SARS-CoV-2, epidemic control, lockdown, non-pharmaceutical interventions, vulnerable populations, herd immunity threshold
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Antibodies, Viral, Coronaviridae, Humans, Pneumonia, Viral, Prevalence, Coronavirus Infections, Immunity, Herd, Pandemics
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