Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.

We apply Bayesian inference methods to a suite of distinct compartmental models of generalised SEIR type, in which diagnosis and quarantine are included via extra compartments. We investigate the evidence for a change in lethality of COVID-19 in late autumn 2020 in the UK, using age-structured, week...

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Autores principales:	Patrick Pietzonka, Erik Brorson, William Bankes, Michael E Cates, Robert L Jack, Ronojoy Adhikari
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4698aff553614bc0aa451beaa5974cbf
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spelling	oai:doaj.org-article:4698aff553614bc0aa451beaa5974cbf2021-12-02T20:16:10ZBayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.1932-620310.1371/journal.pone.0258968https://doaj.org/article/4698aff553614bc0aa451beaa5974cbf2021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258968https://doaj.org/toc/1932-6203We apply Bayesian inference methods to a suite of distinct compartmental models of generalised SEIR type, in which diagnosis and quarantine are included via extra compartments. We investigate the evidence for a change in lethality of COVID-19 in late autumn 2020 in the UK, using age-structured, weekly national aggregate data for cases and mortalities. Models that allow a (step-like or graded) change in infection fatality rate (IFR) have consistently higher model evidence than those without. Moreover, they all infer a close to two-fold increase in IFR. This value lies well above most previously available estimates. However, the same models consistently infer that, most probably, the increase in IFR preceded the time window during which variant B.1.1.7 (alpha) became the dominant strain in the UK. Therefore, according to our models, the caseload and mortality data do not offer unequivocal evidence for higher lethality of a new variant. We compare these results for the UK with similar models for Germany and France, which also show increases in inferred IFR during the same period, despite the even later arrival of new variants in those countries. We argue that while the new variant(s) may be one contributing cause of a large increase in IFR in the UK in autumn 2020, other factors, such as seasonality, or pressure on health services, are likely to also have contributed.Patrick PietzonkaErik BrorsonWilliam BankesMichael E CatesRobert L JackRonojoy AdhikariPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 11, p e0258968 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Patrick Pietzonka Erik Brorson William Bankes Michael E Cates Robert L Jack Ronojoy Adhikari Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
description	We apply Bayesian inference methods to a suite of distinct compartmental models of generalised SEIR type, in which diagnosis and quarantine are included via extra compartments. We investigate the evidence for a change in lethality of COVID-19 in late autumn 2020 in the UK, using age-structured, weekly national aggregate data for cases and mortalities. Models that allow a (step-like or graded) change in infection fatality rate (IFR) have consistently higher model evidence than those without. Moreover, they all infer a close to two-fold increase in IFR. This value lies well above most previously available estimates. However, the same models consistently infer that, most probably, the increase in IFR preceded the time window during which variant B.1.1.7 (alpha) became the dominant strain in the UK. Therefore, according to our models, the caseload and mortality data do not offer unequivocal evidence for higher lethality of a new variant. We compare these results for the UK with similar models for Germany and France, which also show increases in inferred IFR during the same period, despite the even later arrival of new variants in those countries. We argue that while the new variant(s) may be one contributing cause of a large increase in IFR in the UK in autumn 2020, other factors, such as seasonality, or pressure on health services, are likely to also have contributed.
format	article
author	Patrick Pietzonka Erik Brorson William Bankes Michael E Cates Robert L Jack Ronojoy Adhikari
author_facet	Patrick Pietzonka Erik Brorson William Bankes Michael E Cates Robert L Jack Ronojoy Adhikari
author_sort	Patrick Pietzonka
title	Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
title_short	Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
title_full	Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
title_fullStr	Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
title_full_unstemmed	Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.
title_sort	bayesian inference across multiple models suggests a strong increase in lethality of covid-19 in late 2020 in the uk.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/4698aff553614bc0aa451beaa5974cbf
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Bayesian inference across multiple models suggests a strong increase in lethality of COVID-19 in late 2020 in the UK.

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