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Patterns of reported infection and reinfection of SARS-CoV-2 in England
One of the key features of any infectious disease is whether infection generates long-lasting immunity or whether repeated reinfection is common. In the former, the long-term dynamics are driven by the birth of susceptible individuals while in the latter the dynamics are governed by the speed of wan...
Autor principal: | |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568275/ https://www.ncbi.nlm.nih.gov/pubmed/36252843 http://dx.doi.org/10.1016/j.jtbi.2022.111299 |
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author | Keeling, Matt J. |
author_facet | Keeling, Matt J. |
author_sort | Keeling, Matt J. |
collection | PubMed |
description | One of the key features of any infectious disease is whether infection generates long-lasting immunity or whether repeated reinfection is common. In the former, the long-term dynamics are driven by the birth of susceptible individuals while in the latter the dynamics are governed by the speed of waning immunity. Between these two extremes a range of scenarios is possible. During the early waves of SARS-CoV-2, the underlying paradigm was for long-lasting immunity, but more recent data and in particular the 2022 Omicron waves have shown that reinfection can be relatively common. Here we investigate reported SARS-CoV-2 cases in England, partitioning the data into four main waves, and consider the temporal distribution of first and second reports of infection. We show that a simple low-dimensional statistical model of random (but scaled) reinfection captures much of the observed dynamics, with the value of this scaling, [Formula: see text] , providing information of underlying epidemiological patterns. We conclude that there is considerable heterogeneity in risk of reporting reinfection by wave, age-group and location. The high levels of reinfection in the Omicron wave (we estimate that 18% of all Omicron cases had been previously infected, although not necessarily previously reported infection) point to reinfection events dominating future COVID-19 dynamics. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”. |
format | Online Article Text |
id | pubmed-9568275 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95682752022-10-16 Patterns of reported infection and reinfection of SARS-CoV-2 in England Keeling, Matt J. J Theor Biol Article One of the key features of any infectious disease is whether infection generates long-lasting immunity or whether repeated reinfection is common. In the former, the long-term dynamics are driven by the birth of susceptible individuals while in the latter the dynamics are governed by the speed of waning immunity. Between these two extremes a range of scenarios is possible. During the early waves of SARS-CoV-2, the underlying paradigm was for long-lasting immunity, but more recent data and in particular the 2022 Omicron waves have shown that reinfection can be relatively common. Here we investigate reported SARS-CoV-2 cases in England, partitioning the data into four main waves, and consider the temporal distribution of first and second reports of infection. We show that a simple low-dimensional statistical model of random (but scaled) reinfection captures much of the observed dynamics, with the value of this scaling, [Formula: see text] , providing information of underlying epidemiological patterns. We conclude that there is considerable heterogeneity in risk of reporting reinfection by wave, age-group and location. The high levels of reinfection in the Omicron wave (we estimate that 18% of all Omicron cases had been previously infected, although not necessarily previously reported infection) point to reinfection events dominating future COVID-19 dynamics. This manuscript was submitted as part of a theme issue on “Modelling COVID-19 and Preparedness for Future Pandemics”. Published by Elsevier Ltd. 2023-01-07 2022-10-15 /pmc/articles/PMC9568275/ /pubmed/36252843 http://dx.doi.org/10.1016/j.jtbi.2022.111299 Text en © 2022 Published by Elsevier Ltd. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Keeling, Matt J. Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title | Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title_full | Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title_fullStr | Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title_full_unstemmed | Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title_short | Patterns of reported infection and reinfection of SARS-CoV-2 in England |
title_sort | patterns of reported infection and reinfection of sars-cov-2 in england |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9568275/ https://www.ncbi.nlm.nih.gov/pubmed/36252843 http://dx.doi.org/10.1016/j.jtbi.2022.111299 |
work_keys_str_mv | AT keelingmattj patternsofreportedinfectionandreinfectionofsarscov2inengland |