Cited by 645COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsSARS-CoV-2 and COVID-19 Research

A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2

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Britton, Tom, Ball, Frank, Trapman, Pieter·2020·Science

Abstract

Heterogeneity and herd immunity In response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), some politicians have been keen to exploit the idea of achieving herd immunity. Countering this possibility are estimates derived from work on historical vaccination studies, which suggest that herd immunity may only be achieved at an unacceptable cost of lives. Because human populations are far from homogeneous, Britton et al. show that by introducing age and activity heterogeneities into population models for SARS-CoV-2, herd immunity can be achieved at a population-wide infection rate of ∼40%, considerably lower than previous estimates. This shift is because transmission and immunity are concentrated among the most active members of a population, who are often younger and less vulnerable. If nonpharmaceutical interventions are very strict, no herd immunity is achieved, and infections will then resurge if they are eased too quickly. Science , this issue p. 846

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  • Natural infection to reach herd immunity, typically estimated at 40-60% of the population infected, would cause unacceptably high disease and death.

    “The disease and death that would accompany natural infection rates to reach herd immunity, typically estimated as 40–60% of the population infected, would be unacceptably high.”
  • The latest estimates on COVID-19 pointed out a range of 60-75% immune individuals necessary to halt forward transmission and community spread.

    “The latest estimates on COVID-19, pointed out a range of 60–75% immune individuals that would be necessary to halt the forward transmission of the virus and community spread of the virus [87,88,89].”

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Research works printed but not linked: 2

  1. [14]F. Ball, T. Britton, P. Trapman, Code for: Population heterogeneity and consequences for herd immunity to SARS-CoV-2, Version 1, Zenodo (2020); 10.1101/10.1101/10.5281/zenodo.3899252. PMC7331793 32576668 · DOI
  2. [16]S. N. Ethier, T. G. Kurtz, Markov Processes: Characterization and Convergence (Wiley, 2009).

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Authors
Britton, T., Ball, F., & Trapman, P.
Affiliations
  • Stockholm University (SE)
  • University of Nottingham (GB)
Corresponding author
Britton, Tom
Venue
Science
Published
2020-08-14
Volume
369
Issue
6505
Pages
846-849
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W3036932834
Cited by
645
References
15
Citations by year
2026: 24 · 2025: 38 · 2024: 48 · 2023: 58 · 2022: 114 · 2021: 255 · 2020: 107 · 2012: 1
FWCI
21.22
Type
journal article
Language
en
Open access
Locations
  • Science (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Repository@Nottingham (University of Nottingham) (publishedVersion, cc-by)
  • Repository@Nottingham (University of Nottingham) (submittedVersion, cc-by)
Funders
  • Vetenskapsrådet (2016-04566)
  • The swedish Research Council (2015-05015)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
  • Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
Keywords
herd immunity, SARS-CoV-2, population heterogeneity, age heterogeneity, transmission dynamics, mathematical model, non-pharmaceutical interventions, infection rate, COVID-19 pandemic
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Age Factors, Demography, Humans, Models, Theoretical, Pneumonia, Viral, Social Behavior, Coronavirus Infections, Immunity, Herd, Basic Reproduction Number, Pandemics, Social Participation

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