The cumulative incidence and infection hospitalization risk of SARS-CoV-2 by variant: a longitudinal study in England

The COVID Infection Survey monitored daily positivity through the COVID-19 pandemic from April 26, 2020 to March 13, 2023. In total, 451 079 participants in private residential households were enrolled in England and tested at regular intervals for SARS-CoV-2. Here, we estimated the cumulative incidence of polymerase chain reaction-positive infections using a multilevel regression and poststratification model to obtain estimates of daily positivity, combined with a distribution of the duration of positivity from regular testing data. We estimated cumulative incidence by epoch (approximated by the dominance of successive SARS-CoV-2 variants) and calculated the corresponding infection hospitalization ratios. We found that cumulative incidence was relatively low during pre-Alpha and Alpha-dominant epochs, rose steadily during the Delta-dominant epoch, and was highest during successive Omicron-dominant epochs. High cumulative incidences in successive Omicron-dominant epochs are consistent with lack of protection from previous infections. However, infection hospitalization ratios, whilst higher at the start of the pandemic, remained low after the Delta-dominant epoch and vaccine introduction. Stratified estimates show hospitalization risk was consistently very low for younger age groups, increasing with age. Surveys with random sampling and longitudinal designs facilitate direct estimation of prevalence and incidence, however, should be complemented by dense sampling to estimate duration of infection to maximize their value.

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Publication Details

Journal
American Journal of Epidemiology
Published
2025-09-15
DOI
https://doi.org/10.1093/aje/kwaf203
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

The cumulative incidence and infection hospitalization risk of SARS-CoV-2 by variant: a longitudinal study in England

A. Sarah Walker, Charlotte Gaughan, Daniela De Angelis, Koen B. Pouwels et al.
American Journal of Epidemiology
COVID-19 epidemiological studies
article

The cumulative incidence and infection hospitalization risk of SARS-CoV-2 by variant: a longitudinal study in England

A. Sarah Walker, Charlotte Gaughan, Daniela De Angelis, Koen B. Pouwels, Joy Preece, David Braunholtz, Tarnjit K. Khera, Paul Birrell, Joshua Blake, The Team, Leanne Massie
article en

Abstract

The COVID Infection Survey monitored daily positivity through the COVID-19 pandemic from April 26, 2020 to March 13, 2023. In total, 451 079 participants in private residential households were enrolled in England and tested at regular intervals for SARS-CoV-2. Here, we estimated the cumulative incidence of polymerase chain reaction-positive infections using a multilevel regression and poststratification model to obtain estimates of daily positivity, combined with a distribution of the duration of positivity from regular testing data. We estimated cumulative incidence by epoch (approximated by the dominance of successive SARS-CoV-2 variants) and calculated the corresponding infection hospitalization ratios. We found that cumulative incidence was relatively low during pre-Alpha and Alpha-dominant epochs, rose steadily during the Delta-dominant epoch, and was highest during successive Omicron-dominant epochs. High cumulative incidences in successive Omicron-dominant epochs are consistent with lack of protection from previous infections. However, infection hospitalization ratios, whilst higher at the start of the pandemic, remained low after the Delta-dominant epoch and vaccine introduction. Stratified estimates show hospitalization risk was consistently very low for younger age groups, increasing with age. Surveys with random sampling and longitudinal designs facilitate direct estimation of prevalence and incidence, however, should be complemented by dense sampling to estimate duration of infection to maximize their value.

American Journal of EpidemiologyVol. 195(1)
National Security Agency (US), Office for National Statistics (GB), University of Cambridge (GB), National Institute for Health and Care Research (GB), University of Oxford (GB), MRC Biostatistics Unit (GB), UK Health Security Agency (GB)
Openalex Percentile: Top 71%
COVID-19 epidemiological studies
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