Bowie, Cam;
Friston, Karl;
(2022)
A 12-month projection to September 2022 of the COVID-19 epidemic in the UK using a dynamic causal model.
Front Public Health
, 10
, Article 999210. 10.3389/fpubh.2022.999210.
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Abstract
OBJECTIVES: Predicting the future UK COVID-19 epidemic allows other countries to compare their epidemic with one unfolding without public health measures except a vaccine program. METHODS: A Dynamic Causal Model was used to estimate key model parameters of the UK epidemic, such as vaccine effectiveness and increased transmissibility of Alpha and Delta variants, the effectiveness of the vaccine program roll-out and changes in contact rates. The model predicts the future trends in infections, long-COVID, hospital admissions and deaths. RESULTS: Two-dose vaccination given to 66% of the UK population prevents transmission following infection by 44%, serious illness by 86% and death by 93%. Despite this, with no other public health measures used, cases will increase from 37 million to 61 million, hospital admissions from 536,000 to 684,000 and deaths from 136,000 to 142,000 over 12 months. A retrospective analysis (conducted after the original submission of this report) allowed a comparison of these predictions of morbidity and mortality with actual outcomes. CONCLUSION: Vaccination alone will not control the epidemic. Relaxation of mitigating public health measures carries several risks, which include overwhelming the health services, the creation of vaccine resistant variants and the economic cost of huge numbers of acute and chronic cases.
| Type: | Article |
|---|---|
| Title: | A 12-month projection to September 2022 of the COVID-19 epidemic in the UK using a dynamic causal model |
| Location: | Switzerland |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3389/fpubh.2022.999210 |
| Publisher version: | https://doi.org/10.3389/fpubh.2022.999210 |
| Language: | English |
| Additional information: | © 2022 Bowie and Friston. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| Keywords: | Coronavirus, compartmental models, epidemiology—descriptive, incidence, post-acute COVID-19 syndrome, public health methodology, vaccine effectiveness, Humans, COVID-19, Retrospective Studies, SARS-CoV-2, United Kingdom |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10161461 |
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