Abstract
Understanding the scale of the threat posed by SARS-CoV2 B.1.1.529, or Omicron, variant formed a key problem in public health in the early part of 2022. Early evidence indicated that the variant was more transmissible and less severe than previous variants. As the virus was expected to spread quickly through the population of England, it was important that some understanding of the immunological landscape of the country was developed. This paper attempts to estimate the number of people with good immunity to the Omicron variant, defined as either recent infection with two doses of vaccine, or two doses of vaccine with a recent booster dose. To achieve this, we use a process of iterative proportional fitting to estimate the cell values of a contingency table, using national immunisation records and real-time model infection estimates as marginal values. Our results indicate that, despite the increased risk of immune evasion with the Omicron variant, a high proportion of England’s population had good immunity to the virus, particularly in older age groups. However, low rates of immunity in younger populations may allow endemic infection to persist for some time.
| Original language | English |
|---|---|
| Article number | e0264870 |
| Journal | PLoS ONE |
| Volume | 17 |
| Issue number | 10 October |
| DOIs | |
| Publication status | Published - 14 Oct 2022 |
Bibliographical note
Funding Information: All authors are funded through the UK Government Department for Health and Social Care grant in aid funding to the UK health Security Agency.Open Access: This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Publisher Copyright: © 2022 Shingleton et al.
Citation: Shingleton J, Dyke S, Herrick A, Finnie T (2022) Understanding the immunological landscape of England during SARS-CoV2 Omicron variant wave. PLoS ONE 17(10): e0264870. https://doi.org/10.1371/journal.pone.0264870
DOI: https://doi.org/10.1371/journal.pone.0264870
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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