Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.
Identifieur interne : 000367 ( Main/Corpus ); précédent : 000366; suivant : 000368Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.
Auteurs : Ross D. Booton ; Louis Macgregor ; Lucy Vass ; Katharine J. Looker ; Catherine Hyams ; Philip D. Bright ; Irasha Harding ; Rajeka Lazarus ; Fergus Hamilton ; Daniel Lawson ; Leon Danon ; Adrian Pratt ; Richard Wood ; Ellen Brooks-Pollock ; Katherine M E. TurnerSource :
- BMJ open [ 2044-6055 ] ; 2021.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Aged (MeSH), COVID-19 (epidemiology), Child (MeSH), Child, Preschool (MeSH), Critical Care (statistics & numerical data), Decision Making (MeSH), England (epidemiology), Female (MeSH), Hospital Bed Capacity (statistics & numerical data), Hospitalization (statistics & numerical data), Humans (MeSH), Infant (MeSH), Infant, Newborn (MeSH), Intensive Care Units (MeSH), Male (MeSH), Middle Aged (MeSH), Models, Theoretical (MeSH), Regional Health Planning (MeSH), SARS-CoV-2 (MeSH), State Medicine (MeSH), Surge Capacity (MeSH), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : England.
- epidemiology : COVID-19.
- statistics & numerical data : Critical Care, Hospital Bed Capacity, Hospitalization.
- Adolescent, Adult, Aged, Child, Child, Preschool, Decision Making, Female, Humans, Infant, Infant, Newborn, Intensive Care Units, Male, Middle Aged, Models, Theoretical, Regional Health Planning, SARS-CoV-2, State Medicine, Surge Capacity, Young Adult.
Abstract
OBJECTIVES
To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case.
DESIGN
Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths.
SETTING
SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making.
PARTICIPANTS
Publicly available data on patients with COVID-19.
PRIMARY AND SECONDARY OUTCOME MEASURES
The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time.
RESULTS
SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7).
CONCLUSIONS
The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.
DOI: 10.1136/bmjopen-2020-041536
PubMed: 33414147
PubMed Central: PMC7797241
Links to Exploration step
pubmed:33414147Le document en format XML
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Booton</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Macgregor, Louis" sort="Macgregor, Louis" uniqKey="Macgregor L" first="Louis" last="Macgregor">Louis Macgregor</name><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Vass, Lucy" sort="Vass, Lucy" uniqKey="Vass L" first="Lucy" last="Vass">Lucy Vass</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Looker, Katharine J" sort="Looker, Katharine J" uniqKey="Looker K" first="Katharine J" last="Looker">Katharine J. 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Bright</name><affiliation><nlm:affiliation>Immunology, Pathology Sciences, North Bristol NHS Trust, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Harding, Irasha" sort="Harding, Irasha" uniqKey="Harding I" first="Irasha" last="Harding">Irasha Harding</name><affiliation><nlm:affiliation>Consultant in Microbiology, University Hospitals Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Lazarus, Rajeka" sort="Lazarus, Rajeka" uniqKey="Lazarus R" first="Rajeka" last="Lazarus">Rajeka Lazarus</name><affiliation><nlm:affiliation>Consultant in Microbiology and Infectious Diseases, University Hospitals Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Hamilton, Fergus" sort="Hamilton, Fergus" uniqKey="Hamilton F" first="Fergus" last="Hamilton">Fergus Hamilton</name><affiliation><nlm:affiliation>Infection Science, Southmead Hospital, North Bristol NHS Trust, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Lawson, Daniel" sort="Lawson, Daniel" uniqKey="Lawson D" first="Daniel" last="Lawson">Daniel Lawson</name><affiliation><nlm:affiliation>School of Mathematics, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Danon, Leon" sort="Danon, Leon" uniqKey="Danon L" first="Leon" last="Danon">Leon Danon</name><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Department of Engineering Mathematics, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Alan Turing Institute, London, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Pratt, Adrian" sort="Pratt, Adrian" uniqKey="Pratt A" first="Adrian" last="Pratt">Adrian Pratt</name><affiliation><nlm:affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Wood, Richard" sort="Wood, Richard" uniqKey="Wood R" first="Richard" last="Wood">Richard Wood</name><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Brooks Pollock, Ellen" sort="Brooks Pollock, Ellen" uniqKey="Brooks Pollock E" first="Ellen" last="Brooks-Pollock">Ellen Brooks-Pollock</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Turner, Katherine M E" sort="Turner, Katherine M E" uniqKey="Turner K" first="Katherine M E" last="Turner">Katherine M E. Turner</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK katy.turner@bristol.ac.uk.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2021">2021</date><idno type="RBID">pubmed:33414147</idno><idno type="pmid">33414147</idno><idno type="doi">10.1136/bmjopen-2020-041536</idno><idno type="pmc">PMC7797241</idno><idno type="wicri:Area/Main/Corpus">000367</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000367</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.</title><author><name sortKey="Booton, Ross D" sort="Booton, Ross D" uniqKey="Booton R" first="Ross D" last="Booton">Ross D. Booton</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Macgregor, Louis" sort="Macgregor, Louis" uniqKey="Macgregor L" first="Louis" last="Macgregor">Louis Macgregor</name><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Vass, Lucy" sort="Vass, Lucy" uniqKey="Vass L" first="Lucy" last="Vass">Lucy Vass</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Looker, Katharine J" sort="Looker, Katharine J" uniqKey="Looker K" first="Katharine J" last="Looker">Katharine J. Looker</name><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Hyams, Catherine" sort="Hyams, Catherine" uniqKey="Hyams C" first="Catherine" last="Hyams">Catherine Hyams</name><affiliation><nlm:affiliation>Academic Respiratory Unit, Southmead Hospital, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Bright, Philip D" sort="Bright, Philip D" uniqKey="Bright P" first="Philip D" last="Bright">Philip D. Bright</name><affiliation><nlm:affiliation>Immunology, Pathology Sciences, North Bristol NHS Trust, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Harding, Irasha" sort="Harding, Irasha" uniqKey="Harding I" first="Irasha" last="Harding">Irasha Harding</name><affiliation><nlm:affiliation>Consultant in Microbiology, University Hospitals Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Lazarus, Rajeka" sort="Lazarus, Rajeka" uniqKey="Lazarus R" first="Rajeka" last="Lazarus">Rajeka Lazarus</name><affiliation><nlm:affiliation>Consultant in Microbiology and Infectious Diseases, University Hospitals Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Hamilton, Fergus" sort="Hamilton, Fergus" uniqKey="Hamilton F" first="Fergus" last="Hamilton">Fergus Hamilton</name><affiliation><nlm:affiliation>Infection Science, Southmead Hospital, North Bristol NHS Trust, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Lawson, Daniel" sort="Lawson, Daniel" uniqKey="Lawson D" first="Daniel" last="Lawson">Daniel Lawson</name><affiliation><nlm:affiliation>School of Mathematics, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Danon, Leon" sort="Danon, Leon" uniqKey="Danon L" first="Leon" last="Danon">Leon Danon</name><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Department of Engineering Mathematics, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Alan Turing Institute, London, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Pratt, Adrian" sort="Pratt, Adrian" uniqKey="Pratt A" first="Adrian" last="Pratt">Adrian Pratt</name><affiliation><nlm:affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Wood, Richard" sort="Wood, Richard" uniqKey="Wood R" first="Richard" last="Wood">Richard Wood</name><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Brooks Pollock, Ellen" sort="Brooks Pollock, Ellen" uniqKey="Brooks Pollock E" first="Ellen" last="Brooks-Pollock">Ellen Brooks-Pollock</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation></author><author><name sortKey="Turner, Katherine M E" sort="Turner, Katherine M E" uniqKey="Turner K" first="Katherine M E" last="Turner">Katherine M E. Turner</name><affiliation><nlm:affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK katy.turner@bristol.ac.uk.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</nlm:affiliation></affiliation><affiliation><nlm:affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</nlm:affiliation></affiliation></author></analytic><series><title level="j">BMJ open</title><idno type="eISSN">2044-6055</idno><imprint><date when="2021" type="published">2021</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent (MeSH)</term><term>Adult (MeSH)</term><term>Aged (MeSH)</term><term>COVID-19 (epidemiology)</term><term>Child (MeSH)</term><term>Child, Preschool (MeSH)</term><term>Critical Care (statistics & numerical data)</term><term>Decision Making (MeSH)</term><term>England (epidemiology)</term><term>Female (MeSH)</term><term>Hospital Bed Capacity (statistics & numerical data)</term><term>Hospitalization (statistics & numerical data)</term><term>Humans (MeSH)</term><term>Infant (MeSH)</term><term>Infant, Newborn (MeSH)</term><term>Intensive Care Units (MeSH)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Models, Theoretical (MeSH)</term><term>Regional Health Planning (MeSH)</term><term>SARS-CoV-2 (MeSH)</term><term>State Medicine (MeSH)</term><term>Surge Capacity (MeSH)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>England</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>COVID-19</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Critical Care</term><term>Hospital Bed Capacity</term><term>Hospitalization</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Aged</term><term>Child</term><term>Child, Preschool</term><term>Decision Making</term><term>Female</term><term>Humans</term><term>Infant</term><term>Infant, Newborn</term><term>Intensive Care Units</term><term>Male</term><term>Middle Aged</term><term>Models, Theoretical</term><term>Regional Health Planning</term><term>SARS-CoV-2</term><term>State Medicine</term><term>Surge Capacity</term><term>Young Adult</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>OBJECTIVES</b></p><p>To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case.</p></div><div type="abstract" xml:lang="en"><p><b>DESIGN</b></p><p>Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths.</p></div><div type="abstract" xml:lang="en"><p><b>SETTING</b></p><p>SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making.</p></div><div type="abstract" xml:lang="en"><p><b>PARTICIPANTS</b></p><p>Publicly available data on patients with COVID-19.</p></div><div type="abstract" xml:lang="en"><p><b>PRIMARY AND SECONDARY OUTCOME MEASURES</b></p><p>The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7).</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">33414147</PMID><DateCompleted><Year>2021</Year><Month>01</Month><Day>18</Day></DateCompleted><DateRevised><Year>2021</Year><Month>01</Month><Day>18</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2044-6055</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>1</Issue><PubDate><Year>2021</Year><Month>01</Month><Day>07</Day></PubDate></JournalIssue><Title>BMJ open</Title><ISOAbbreviation>BMJ Open</ISOAbbreviation></Journal><ArticleTitle>Estimating the COVID-19 epidemic trajectory and hospital capacity requirements in South West England: a mathematical modelling framework.</ArticleTitle><Pagination><MedlinePgn>e041536</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1136/bmjopen-2020-041536</ELocationID><Abstract><AbstractText Label="OBJECTIVES">To develop a regional model of COVID-19 dynamics for use in estimating the number of infections, deaths and required acute and intensive care (IC) beds using the South West England (SW) as an example case.</AbstractText><AbstractText Label="DESIGN">Open-source age-structured variant of a susceptible-exposed-infectious-recovered compartmental mathematical model. Latin hypercube sampling and maximum likelihood estimation were used to calibrate to cumulative cases and cumulative deaths.</AbstractText><AbstractText Label="SETTING">SW at a time considered early in the pandemic, where National Health Service authorities required evidence to guide localised planning and support decision-making.</AbstractText><AbstractText Label="PARTICIPANTS">Publicly available data on patients with COVID-19.</AbstractText><AbstractText Label="PRIMARY AND SECONDARY OUTCOME MEASURES">The expected numbers of infected cases, deaths due to COVID-19 infection, patient occupancy of acute and IC beds and the reproduction ('R') number over time.</AbstractText><AbstractText Label="RESULTS">SW model projections indicate that, as of 11 May 2020 (when 'lockdown' measures were eased), 5793 (95% credible interval (CrI) 2003 to 12 051) individuals were still infectious (0.10% of the total SW population, 95% CrI 0.04% to 0.22%), and a total of 189 048 (95% CrI 141 580 to 277 955) had been infected with the virus (either asymptomatically or symptomatically), but recovered, which is 3.4% (95% CrI 2.5% to 5.0%) of the SW population. The total number of patients in acute and IC beds in the SW on 11 May 2020 was predicted to be 701 (95% CrI 169 to 1543) and 110 (95% CrI 8 to 464), respectively. The R value in SW was predicted to be 2.6 (95% CrI 2.0 to 3.2) prior to any interventions, with social distancing reducing this to 2.3 (95% CrI 1.8 to 2.9) and lockdown/school closures further reducing the R value to 0.6 (95% CrI 0.5 to 0.7).</AbstractText><AbstractText Label="CONCLUSIONS">The developed model has proved a valuable asset for regional healthcare services. The model will be used further in the SW as the pandemic evolves, and-as open-source software-is portable to healthcare systems in other geographies.</AbstractText><CopyrightInformation>© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Booton</LastName><ForeName>Ross D</ForeName><Initials>RD</Initials><Identifier Source="ORCID">0000-0002-3013-4179</Identifier><AffiliationInfo><Affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>MacGregor</LastName><ForeName>Louis</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Vass</LastName><ForeName>Lucy</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Looker</LastName><ForeName>Katharine J</ForeName><Initials>KJ</Initials><Identifier Source="ORCID">0000-0002-3375-0807</Identifier><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hyams</LastName><ForeName>Catherine</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Academic Respiratory Unit, Southmead Hospital, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bright</LastName><ForeName>Philip D</ForeName><Initials>PD</Initials><AffiliationInfo><Affiliation>Immunology, Pathology Sciences, North Bristol NHS Trust, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Harding</LastName><ForeName>Irasha</ForeName><Initials>I</Initials><AffiliationInfo><Affiliation>Consultant in Microbiology, University Hospitals Bristol, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lazarus</LastName><ForeName>Rajeka</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Consultant in Microbiology and Infectious Diseases, University Hospitals Bristol, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hamilton</LastName><ForeName>Fergus</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Infection Science, Southmead Hospital, North Bristol NHS Trust, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lawson</LastName><ForeName>Daniel</ForeName><Initials>D</Initials><Identifier Source="ORCID">0000-0002-5311-6213</Identifier><AffiliationInfo><Affiliation>School of Mathematics, University of Bristol, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Danon</LastName><ForeName>Leon</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Engineering Mathematics, University of Bristol, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Alan Turing Institute, London, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Pratt</LastName><ForeName>Adrian</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wood</LastName><ForeName>Richard</ForeName><Initials>R</Initials><Identifier Source="ORCID">0000-0002-3476-395X</Identifier><AffiliationInfo><Affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Modelling and Analytics Team, NHS Bristol, North Somerset and South Gloucestershire CCG, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Brooks-Pollock</LastName><ForeName>Ellen</ForeName><Initials>E</Initials><Identifier Source="ORCID">0000-0002-5984-4932</Identifier><AffiliationInfo><Affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Turner</LastName><ForeName>Katherine M E</ForeName><Initials>KME</Initials><Identifier Source="ORCID">0000-0002-8152-6017</Identifier><AffiliationInfo><Affiliation>School of Veterinary Sciences, University of Bristol, Bristol, UK katy.turner@bristol.ac.uk.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Population Health Science Institute, University of Bristol Medical School, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>NIHR Health Protection Research Unit in Behavioural Science and Evaluation, Bristol, UK.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Health Data Research UK South-West of England Partnership, Bristol, UK.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2021</Year><Month>01</Month><Day>07</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMJ Open</MedlineTA><NlmUniqueID>101552874</NlmUniqueID><ISSNLinking>2044-6055</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" 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Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012040" MajorTopicYN="Y">Regional Health Planning</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013222" MajorTopicYN="N">State Medicine</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055872" MajorTopicYN="Y">Surge Capacity</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">epidemiology</Keyword><Keyword MajorTopicYN="Y">infection control</Keyword><Keyword MajorTopicYN="Y">public health</Keyword></KeywordList><CoiStatement>Competing interests: None declared.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate 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