A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Christopher J.R. Illingworth; William L. Hamilton; Christopher Jackson; Ben Warne; Ashley Popay; Luke Meredith; Myra Hosmillo; Aminu Jahun; Tom Fieldman; Matthew Routledge; Charlotte J. Houldcroft; Laura Caller; Sarah Caddy; Anna Yakovleva; Grant Hall; Fahad A. Khokhar; Theresa Feltwell; Malte L. Pinckert; Iliana Georgana; Yasmin Chaudhry; Martin Curran; Surendra Parmar; Dominic Sparkes; Lucy Rivett; Nick K. Jones; Sushmita Sridhar; Sally Forrest; Tom Dymond; Kayleigh Grainger; Chris Workman; Effrossyni Gkrania-Klotsas; Nicholas M. Brown; Michael P. Weekes; Stephen Baker; Sharon J. Peacock; Theodore Gouliouris; Ian Goodfellow; Daniela De Angelis; M. Estee Török

doi:10.1093/molbev/msac025

A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Christopher J.R. Illingworth^*, William L. Hamilton, Christopher Jackson, Ben Warne, Ashley Popay, Luke Meredith, Myra Hosmillo, Aminu Jahun, Tom Fieldman, Matthew Routledge, Charlotte J. Houldcroft, Laura Caller, Sarah Caddy, Anna Yakovleva, Grant Hall, Fahad A. Khokhar, Theresa Feltwell, Malte L. Pinckert, Iliana Georgana, Yasmin ChaudhryMartin Curran, Surendra Parmar, Dominic Sparkes, Lucy Rivett, Nick K. Jones, Sushmita Sridhar, Sally Forrest, Tom Dymond, Kayleigh Grainger, Chris Workman, Effrossyni Gkrania-Klotsas, Nicholas M. Brown, Michael P. Weekes, Stephen Baker, Sharon J. Peacock, Theodore Gouliouris, Ian Goodfellow, Daniela De Angelis, M. Estee Török

^*Corresponding author for this work

Statistics Unit

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Abstract

Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

Original language	English
Article number	025
Number of pages	14
Journal	Molecular Biology and Evolution
Volume	39
Issue number	3
Early online date	2 Feb 2022
DOIs	https://doi.org/10.1093/molbev/msac025
Publication status	Published - 2 Mar 2022

Bibliographical note

Funding Information: This work was funded by COG-UK, which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute; We also acknowledge the support from the Wellcome [Senior Clinical Fellowship to M.P.W. (ref.: 108070/Z/15/Z), Senior Research Fellowship to S.B. (ref.: 215515/Z/19/Z), Senior Fellowship to I.G. (ref.: 207498/Z/17/Z); Collaborative Grant to C.J.H. (ref.: 204870/Z/16/Z); the Academy of Medical Sciences & the Health Foundation (Clinician Scientist Fellowship to M.E.T.), the NIHR Cambridge Biomedical Research Centre (to B.W., M.E.T.) and the NIHR Clinical Research Network Greenshoots award (to E.G.K.). C.J.R.I. was supported by Deutsche Forschungsgemeinschaft (DFG) Grant SFB 1310 and by UKRI through the JUNIPER modeling consortium [grant number MR/V038613/1]. We acknowledge UKRI Medical Research Council funding (Unit Programme numbers MC_UU_00002/11 and MC_UU_12014); NIHR Health Protection Units in Behavioural Science and Evaluation.

Open Access: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Publisher Copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Citation: Christopher J R Illingworth, William L Hamilton, Christopher Jackson, Ben Warne, Ashley Popay, Luke Meredith, Myra Hosmillo, Aminu Jahun, Tom Fieldman, Matthew Routledge, Charlotte J Houldcroft, Laura Caller, Sarah Caddy, Anna Yakovleva, Grant Hall, Fahad A Khokhar, Theresa Feltwell, Malte L Pinckert, Iliana Georgana, Yasmin Chaudhry, Martin Curran, Surendra Parmar, Dominic Sparkes, Lucy Rivett, Nick K Jones, Sushmita Sridhar, Sally Forrest, Tom Dymond, Kayleigh Grainger, Chris Workman, Effrossyni Gkrania-Klotsas, Nicholas M Brown, Michael P Weekes, Stephen Baker, Sharon J Peacock, Theodore Gouliouris, Ian Goodfellow, Daniela De Angelis, M Estée Török, A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events, Molecular Biology and Evolution, Volume 39, Issue 3, March 2022, msac025,

DOI: https://doi.org/10.1093/molbev/msac025

Keywords

Evolution
Hospital
SARS-CoV-2
Transmission

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1093/molbev/msac025Licence: CC BY

Illingworth2022A2BCOVIDAToolForRapidlyEvaluatingPotentialMolBiolEvolFinal published version, 1.04 MBLicence: CC BY

Cite this

Illingworth, C. J. R., Hamilton, W. L., Jackson, C., Warne, B., Popay, A., Meredith, L., Hosmillo, M., Jahun, A., Fieldman, T., Routledge, M., Houldcroft, C. J., Caller, L., Caddy, S., Yakovleva, A., Hall, G., Khokhar, F. A., Feltwell, T., Pinckert, M. L., Georgana, I., ... Estee Török, M. (2022). A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events. Molecular Biology and Evolution, 39(3), Article 025. https://doi.org/10.1093/molbev/msac025

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title = "A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events",

abstract = "Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.",

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author = "Illingworth, {Christopher J.R.} and Hamilton, {William L.} and Christopher Jackson and Ben Warne and Ashley Popay and Luke Meredith and Myra Hosmillo and Aminu Jahun and Tom Fieldman and Matthew Routledge and Houldcroft, {Charlotte J.} and Laura Caller and Sarah Caddy and Anna Yakovleva and Grant Hall and Khokhar, {Fahad A.} and Theresa Feltwell and Pinckert, {Malte L.} and Iliana Georgana and Yasmin Chaudhry and Martin Curran and Surendra Parmar and Dominic Sparkes and Lucy Rivett and Jones, {Nick K.} and Sushmita Sridhar and Sally Forrest and Tom Dymond and Kayleigh Grainger and Chris Workman and Effrossyni Gkrania-Klotsas and Brown, {Nicholas M.} and Weekes, {Michael P.} and Stephen Baker and Peacock, {Sharon J.} and Theodore Gouliouris and Ian Goodfellow and {De Angelis}, Daniela and {Estee T{\"o}r{\"o}k}, M.",

note = "Funding Information: This work was funded by COG-UK, which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute; We also acknowledge the support from the Wellcome [Senior Clinical Fellowship to M.P.W. (ref.: 108070/Z/15/Z), Senior Research Fellowship to S.B. (ref.: 215515/Z/19/Z), Senior Fellowship to I.G. (ref.: 207498/Z/17/Z); Collaborative Grant to C.J.H. (ref.: 204870/Z/16/Z); the Academy of Medical Sciences & the Health Foundation (Clinician Scientist Fellowship to M.E.T.), the NIHR Cambridge Biomedical Research Centre (to B.W., M.E.T.) and the NIHR Clinical Research Network Greenshoots award (to E.G.K.). C.J.R.I. was supported by Deutsche Forschungsgemeinschaft (DFG) Grant SFB 1310 and by UKRI through the JUNIPER modeling consortium [grant number MR/V038613/1]. We acknowledge UKRI Medical Research Council funding (Unit Programme numbers MC_UU_00002/11 and MC_UU_12014); NIHR Health Protection Units in Behavioural Science and Evaluation. Open Access: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Publisher Copyright: {\textcopyright} The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. Citation: Christopher J R Illingworth, William L Hamilton, Christopher Jackson, Ben Warne, Ashley Popay, Luke Meredith, Myra Hosmillo, Aminu Jahun, Tom Fieldman, Matthew Routledge, Charlotte J Houldcroft, Laura Caller, Sarah Caddy, Anna Yakovleva, Grant Hall, Fahad A Khokhar, Theresa Feltwell, Malte L Pinckert, Iliana Georgana, Yasmin Chaudhry, Martin Curran, Surendra Parmar, Dominic Sparkes, Lucy Rivett, Nick K Jones, Sushmita Sridhar, Sally Forrest, Tom Dymond, Kayleigh Grainger, Chris Workman, Effrossyni Gkrania-Klotsas, Nicholas M Brown, Michael P Weekes, Stephen Baker, Sharon J Peacock, Theodore Gouliouris, Ian Goodfellow, Daniela De Angelis, M Est{\'e}e T{\"o}r{\"o}k, A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events, Molecular Biology and Evolution, Volume 39, Issue 3, March 2022, msac025, DOI: https://doi.org/10.1093/molbev/msac025",

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Illingworth, CJR, Hamilton, WL, Jackson, C, Warne, B, Popay, A, Meredith, L, Hosmillo, M, Jahun, A, Fieldman, T, Routledge, M, Houldcroft, CJ, Caller, L, Caddy, S, Yakovleva, A, Hall, G, Khokhar, FA, Feltwell, T, Pinckert, ML, Georgana, I, Chaudhry, Y, Curran, M, Parmar, S, Sparkes, D, Rivett, L, Jones, NK, Sridhar, S, Forrest, S, Dymond, T, Grainger, K, Workman, C, Gkrania-Klotsas, E, Brown, NM, Weekes, MP, Baker, S, Peacock, SJ, Gouliouris, T, Goodfellow, I, De Angelis, D & Estee Török, M 2022, 'A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events', Molecular Biology and Evolution, vol. 39, no. 3, 025. https://doi.org/10.1093/molbev/msac025

TY - JOUR

T1 - A2B-COVID

T2 - A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

AU - Illingworth, Christopher J.R.

AU - Hamilton, William L.

AU - Jackson, Christopher

AU - Warne, Ben

AU - Popay, Ashley

AU - Meredith, Luke

AU - Hosmillo, Myra

AU - Jahun, Aminu

AU - Fieldman, Tom

AU - Routledge, Matthew

AU - Houldcroft, Charlotte J.

AU - Caller, Laura

AU - Caddy, Sarah

AU - Yakovleva, Anna

AU - Hall, Grant

AU - Khokhar, Fahad A.

AU - Feltwell, Theresa

AU - Pinckert, Malte L.

AU - Georgana, Iliana

AU - Chaudhry, Yasmin

AU - Curran, Martin

AU - Parmar, Surendra

AU - Sparkes, Dominic

AU - Rivett, Lucy

AU - Jones, Nick K.

AU - Sridhar, Sushmita

AU - Forrest, Sally

AU - Dymond, Tom

AU - Grainger, Kayleigh

AU - Workman, Chris

AU - Gkrania-Klotsas, Effrossyni

AU - Brown, Nicholas M.

AU - Weekes, Michael P.

AU - Baker, Stephen

AU - Peacock, Sharon J.

AU - Gouliouris, Theodore

AU - Goodfellow, Ian

AU - De Angelis, Daniela

AU - Estee Török, M.

N1 - Funding Information: This work was funded by COG-UK, which is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute; We also acknowledge the support from the Wellcome [Senior Clinical Fellowship to M.P.W. (ref.: 108070/Z/15/Z), Senior Research Fellowship to S.B. (ref.: 215515/Z/19/Z), Senior Fellowship to I.G. (ref.: 207498/Z/17/Z); Collaborative Grant to C.J.H. (ref.: 204870/Z/16/Z); the Academy of Medical Sciences & the Health Foundation (Clinician Scientist Fellowship to M.E.T.), the NIHR Cambridge Biomedical Research Centre (to B.W., M.E.T.) and the NIHR Clinical Research Network Greenshoots award (to E.G.K.). C.J.R.I. was supported by Deutsche Forschungsgemeinschaft (DFG) Grant SFB 1310 and by UKRI through the JUNIPER modeling consortium [grant number MR/V038613/1]. We acknowledge UKRI Medical Research Council funding (Unit Programme numbers MC_UU_00002/11 and MC_UU_12014); NIHR Health Protection Units in Behavioural Science and Evaluation. Open Access: This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Publisher Copyright: © The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. Citation: Christopher J R Illingworth, William L Hamilton, Christopher Jackson, Ben Warne, Ashley Popay, Luke Meredith, Myra Hosmillo, Aminu Jahun, Tom Fieldman, Matthew Routledge, Charlotte J Houldcroft, Laura Caller, Sarah Caddy, Anna Yakovleva, Grant Hall, Fahad A Khokhar, Theresa Feltwell, Malte L Pinckert, Iliana Georgana, Yasmin Chaudhry, Martin Curran, Surendra Parmar, Dominic Sparkes, Lucy Rivett, Nick K Jones, Sushmita Sridhar, Sally Forrest, Tom Dymond, Kayleigh Grainger, Chris Workman, Effrossyni Gkrania-Klotsas, Nicholas M Brown, Michael P Weekes, Stephen Baker, Sharon J Peacock, Theodore Gouliouris, Ian Goodfellow, Daniela De Angelis, M Estée Török, A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events, Molecular Biology and Evolution, Volume 39, Issue 3, March 2022, msac025, DOI: https://doi.org/10.1093/molbev/msac025

PY - 2022/3/2

Y1 - 2022/3/2

N2 - Identifying linked cases of infection is a critical component of the public health response to viral infectious diseases. In a clinical context, there is a need to make rapid assessments of whether cases of infection have arrived independently onto a ward, or are potentially linked via direct transmission. Viral genome sequence data are of great value in making these assessments, but are often not the only form of data available. Here, we describe A2B-COVID, a method for the rapid identification of potentially linked cases of COVID-19 infection designed for clinical settings. Our method combines knowledge about infection dynamics, data describing the movements of individuals, and evolutionary analysis of genome sequences to assess whether data collected from cases of infection are consistent or inconsistent with linkage via direct transmission. A retrospective analysis of data from two wards at Cambridge University Hospitals NHS Foundation Trust during the first wave of the pandemic showed qualitatively different patterns of linkage between cases on designated COVID-19 and non-COVID-19 wards. The subsequent real-time application of our method to data from the second epidemic wave highlights its value for monitoring cases of infection in a clinical context.

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KW - Evolution

KW - Hospital

KW - SARS-CoV-2

KW - Transmission

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U2 - 10.1093/molbev/msac025

DO - 10.1093/molbev/msac025

M3 - Article

C2 - 35106603

AN - SCOPUS:85125680604

SN - 0737-4038

VL - 39

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

IS - 3

M1 - 025

ER -

A2B-COVID: A Tool for Rapidly Evaluating Potential SARS-CoV-2 Transmission Events

Abstract

Bibliographical note

Keywords

UN SDGs

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