How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology

Naomi R. Waterlow; Edwin van Leeuwen; Nicholas G. Davies; Stefan Flasche; Rosalind M. Eggo

doi:10.1073/pnas.2108395118

How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology

Naomi R. Waterlow^*, Edwin van Leeuwen, Nicholas G. Davies, Stefan Flasche, Rosalind M. Eggo

^*Corresponding author for this work

UK Health Security Agency

Research output: Contribution to journal › Article › peer-review

18 Citations (Scopus)

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Abstract

We hypothesized that cross-protection from seasonal epidemics of human coronaviruses (HCoVs) could have affected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, including generating reduced susceptibility in children. To determine what the prepandemic distribution of immunity to HCoVs was, we fitted a mathematical model to 6 y of seasonal coronavirus surveillance data from England and Wales. We estimated a duration of immunity to seasonal HCoVs of 7.8 y (95% CI 6.3 to 8.1) and show that, while cross-protection between HCoV and SARS-CoV-2 may contribute to the age distribution, it is insufficient to explain the age pattern of SARS-CoV-2 infections in the first wave of the pandemic in England and Wales. Projections from our model illustrate how different strengths of cross-protection between circulating coronaviruses could determine the frequency and magnitude of SARS-CoV-2 epidemics over the coming decade, as well as the potential impact of cross-protection on future seasonal coronavirus transmission.

Original language	English
Article number	e2108395118
Journal	Proceedings of the National Academy of Sciences of the United States of America
Volume	118
Issue number	49
DOIs	https://doi.org/10.1073/pnas.2108395118
Publication status	Published - 3 Dec 2021

Bibliographical note

Funding Information: We thank Dr. Edward M. Hill for his helpful comments on the preprint of this paper. N.R.W. was supported by the Medical Research Council (Grants MR/N013638/1 and MR/V015737/1) and National Institute for Health Research (NIHR) (Grant COV0076). E.v.L. was supported by the NIHR Health Protection Research Unit in Modelling and Health Economics, a partnership between PHE, Imperial College London, and the London School of Hygiene and Tropical Medicine (LSHTM) (Grant NIHR200908). E.v.L. was supported by the European Union's Horizon 2020 Research and Innovation Programme - Project EpiPose (101003688). S.F. is funded through a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 208812/Z/17/Z). R.M.E. acknowledges an Health Data Research (HDR) UK Innovation Fellowship (Grant MR/S003975/1), Medical Research Council - MRC (Grant MC_PC 19065), and NIHR (Grant NIHR200908) for the Health Protection Research Unit in Modelling and Economics at LSHTM.
The following authors were part of the Centre for Mathematical Modelling of Infectious Disease COVID-19 Working Group. Each contributed in processing, cleaning, and interpretation of data; interpreted findings; contributed to the manuscript; and approved the work for publication: Rachael Pung, Paul Mee, William Waites, Damien C. Tully, Katherine E. Atkins, C. Julian Villabona-Arenas, Graham Medley, Frank G. Sandmann, Anna M. Foss, Sophie R. Meakin, Carl A. B. Pearson, Emilie Finch, Nikos I. Bosse, Christopher I. Jarvis, Kiesha Prem, Alicia Rosello, Kevin van Zandvoort, Rosanna C. Barnard, Jiayao Lei, Yang Liu, Adam J. Kucharski, Ciara V. McCarthy, Sam Abbott, Emily S. Nightingale, Joel Hellewell, Thibaut Jombart, David Hodgson, Gwenan M. Knight, Amy Gimma, Yung-Wai Desmond Chan, Yalda Jafari, Samuel Clifford, Timothy W. Russell, Fiona Yueqian Sun, Simon R. Procter, Akira Endo, Oliver Brady, Kaja Abbas, Billy J. Quilty, Mark Jit, Sebastian Funk, Fabienne Krauer, Matthew Quaife, Hamish P. Gibbs, W. John Edmunds, Mihaly Koltai, Kathleen O'Reilly, Rachel Lowe, and James D. Munday. The following funding sources are acknowledged as providing funding for the working group authors. This research was partly funded by the Bill & Melinda Gates Foundation (INV-001754: MQ; INV-003174: J.Y.L., K.P., M.J., Y.L.; INV-016832: S.R.P.; NTD Modelling Consortium OPP1184344: C.A.B.P., G.F.M.; OPP1139859: B.J.Q; OPP1183986: E.S.N; OPP1191821: K.O.). Bill and Melinda Gates Foundation - BMGF (INV-016832; OPP1157270: K.A). Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology - CADDE MR/S0195/1 & The São Paulo Research Foundation - FAPESP 18/14389-0 (P.M.). European & Developing Countries Clinical Trials Partnership - EDCTP2 (RIA2020EF-2983-CSIGN: H.P.G.). Elrha Research for Health in Humanitarian Crises (R2HC/UK), Foreign, Commonwealth & Development Office (FCDO), Wellcome Trust (K.v.Z.). European Research Council (ERC) Starting Grant (#757699: M.Q.). ERC (SG 757688: C.J.V.A., K.E.A.). European Union's Horizon 2020 research and innovation programme - project EpiPose (101003688: A.G., K.P., M.J., R.C.B., W.J.E., Y.L.). FCDO/Wellcome Trust (Epidemic Preparedness Coronavirus research programme 221303/Z/20/Z: C.A.B.P., K.v.Z.). Global Challenges Research Fund (GCRF) project 'RECAP' managed through Research Councils UK (RCUK) and Economic and Social Research Council (ESRC) (ES/ P010873/1: C.I.J., T.J.). Health Protection Research Unit (HPRU) (NIHR200908: N.I.B.). Innovation Fund (01VSF18015: F.K.). MRC (MR/N013638/1: E.F.; MR/ V027956/1: W.W.). Nakajima Foundation (A.E.). NIHR (16/136/46: B.J.Q.; 16/137/109: B.J.Q., F.Y.S., M.J., Y.L.; 1R01AI141534-01A1: D.H.; Health Protection Research Unit for Modelling Methodology HPRU-2012-10096: T.J.; NIHR200908: A.J.K.; NIHR200929: C.V.M., F.G.S., M.J.; PR-OD-1017-20002: A.R., W.J.E.). Royal Society (Dorothy Hodgkin Fellowship: R.L.). Singapore Ministry of Health (R.P.). UK DHSC/UK Aid/NIHR (PR-OD-1017-20001: H.P.G). UK MRC (MC_PC_19065 - Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: S.C., T.J., W.J.E., Y.L.; MR/P014658/1: G.M.K.), UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care (T.J.). UKRI (MR/ V028456/1: Y.J.). Wellcome Trust (206250/Z/17/Z: A.J.K., T.W.R.; 206471/Z/17/Z: O.J.B.; 208812/Z/17/Z: S.C.; 210758/Z/18/Z: J.D.M., J.H., S.A., S.F., S.R.M.; 221303/ Z/20/Z: M.K.; UNS110424: F.K.). No funding (A.M.F., D.C.T., Y.W.D.C.).
This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care.

Open Access: This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY).

Publisher Copyright: © 2021 the Author(s). Published by PNAS.

Citation: How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology. Naomi R. Waterlow, Edwin van Leeuwen, Nicholas G. Davies, CMMID COVID-19 Working Group, Stefan Flasche, Rosalind M. Eggo. Proceedings of the National Academy of Sciences Dec 2021, 118 (49) e2108395118

DOI: 10.1073/pnas.2108395118

Keywords

COVID-19
Coronaviruses
Cross-protection
Immunity
SARS-CoV-2

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10.1073/pnas.2108395118Licence: CC BY

Waterlow2021HowImmunityFromAndInteractionWithSeasonalCoronavirusesProcNatlAcadSciUSAFinal published version, 1.52 MBLicence: CC BY

Cite this

@article{5246b26c59ce42eeb552e75520ed9c1d,

title = "How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology",

abstract = "We hypothesized that cross-protection from seasonal epidemics of human coronaviruses (HCoVs) could have affected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, including generating reduced susceptibility in children. To determine what the prepandemic distribution of immunity to HCoVs was, we fitted a mathematical model to 6 y of seasonal coronavirus surveillance data from England and Wales. We estimated a duration of immunity to seasonal HCoVs of 7.8 y (95% CI 6.3 to 8.1) and show that, while cross-protection between HCoV and SARS-CoV-2 may contribute to the age distribution, it is insufficient to explain the age pattern of SARS-CoV-2 infections in the first wave of the pandemic in England and Wales. Projections from our model illustrate how different strengths of cross-protection between circulating coronaviruses could determine the frequency and magnitude of SARS-CoV-2 epidemics over the coming decade, as well as the potential impact of cross-protection on future seasonal coronavirus transmission.",

keywords = "COVID-19, Coronaviruses, Cross-protection, Immunity, SARS-CoV-2",

author = "Waterlow, {Naomi R.} and {van Leeuwen}, Edwin and Davies, {Nicholas G.} and Stefan Flasche and Eggo, {Rosalind M.}",

note = "Funding Information: We thank Dr. Edward M. Hill for his helpful comments on the preprint of this paper. N.R.W. was supported by the Medical Research Council (Grants MR/N013638/1 and MR/V015737/1) and National Institute for Health Research (NIHR) (Grant COV0076). E.v.L. was supported by the NIHR Health Protection Research Unit in Modelling and Health Economics, a partnership between PHE, Imperial College London, and the London School of Hygiene and Tropical Medicine (LSHTM) (Grant NIHR200908). E.v.L. was supported by the European Union's Horizon 2020 Research and Innovation Programme - Project EpiPose (101003688). S.F. is funded through a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 208812/Z/17/Z). R.M.E. acknowledges an Health Data Research (HDR) UK Innovation Fellowship (Grant MR/S003975/1), Medical Research Council - MRC (Grant MC_PC 19065), and NIHR (Grant NIHR200908) for the Health Protection Research Unit in Modelling and Economics at LSHTM. The following authors were part of the Centre for Mathematical Modelling of Infectious Disease COVID-19 Working Group. Each contributed in processing, cleaning, and interpretation of data; interpreted findings; contributed to the manuscript; and approved the work for publication: Rachael Pung, Paul Mee, William Waites, Damien C. Tully, Katherine E. Atkins, C. Julian Villabona-Arenas, Graham Medley, Frank G. Sandmann, Anna M. Foss, Sophie R. Meakin, Carl A. B. Pearson, Emilie Finch, Nikos I. Bosse, Christopher I. Jarvis, Kiesha Prem, Alicia Rosello, Kevin van Zandvoort, Rosanna C. Barnard, Jiayao Lei, Yang Liu, Adam J. Kucharski, Ciara V. McCarthy, Sam Abbott, Emily S. Nightingale, Joel Hellewell, Thibaut Jombart, David Hodgson, Gwenan M. Knight, Amy Gimma, Yung-Wai Desmond Chan, Yalda Jafari, Samuel Clifford, Timothy W. Russell, Fiona Yueqian Sun, Simon R. Procter, Akira Endo, Oliver Brady, Kaja Abbas, Billy J. Quilty, Mark Jit, Sebastian Funk, Fabienne Krauer, Matthew Quaife, Hamish P. Gibbs, W. John Edmunds, Mihaly Koltai, Kathleen O'Reilly, Rachel Lowe, and James D. Munday. The following funding sources are acknowledged as providing funding for the working group authors. This research was partly funded by the Bill & Melinda Gates Foundation (INV-001754: MQ; INV-003174: J.Y.L., K.P., M.J., Y.L.; INV-016832: S.R.P.; NTD Modelling Consortium OPP1184344: C.A.B.P., G.F.M.; OPP1139859: B.J.Q; OPP1183986: E.S.N; OPP1191821: K.O.). Bill and Melinda Gates Foundation - BMGF (INV-016832; OPP1157270: K.A). Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology - CADDE MR/S0195/1 & The S{\~a}o Paulo Research Foundation - FAPESP 18/14389-0 (P.M.). European & Developing Countries Clinical Trials Partnership - EDCTP2 (RIA2020EF-2983-CSIGN: H.P.G.). Elrha Research for Health in Humanitarian Crises (R2HC/UK), Foreign, Commonwealth & Development Office (FCDO), Wellcome Trust (K.v.Z.). European Research Council (ERC) Starting Grant (#757699: M.Q.). ERC (SG 757688: C.J.V.A., K.E.A.). European Union's Horizon 2020 research and innovation programme - project EpiPose (101003688: A.G., K.P., M.J., R.C.B., W.J.E., Y.L.). FCDO/Wellcome Trust (Epidemic Preparedness Coronavirus research programme 221303/Z/20/Z: C.A.B.P., K.v.Z.). Global Challenges Research Fund (GCRF) project 'RECAP' managed through Research Councils UK (RCUK) and Economic and Social Research Council (ESRC) (ES/ P010873/1: C.I.J., T.J.). Health Protection Research Unit (HPRU) (NIHR200908: N.I.B.). Innovation Fund (01VSF18015: F.K.). MRC (MR/N013638/1: E.F.; MR/ V027956/1: W.W.). Nakajima Foundation (A.E.). NIHR (16/136/46: B.J.Q.; 16/137/109: B.J.Q., F.Y.S., M.J., Y.L.; 1R01AI141534-01A1: D.H.; Health Protection Research Unit for Modelling Methodology HPRU-2012-10096: T.J.; NIHR200908: A.J.K.; NIHR200929: C.V.M., F.G.S., M.J.; PR-OD-1017-20002: A.R., W.J.E.). Royal Society (Dorothy Hodgkin Fellowship: R.L.). Singapore Ministry of Health (R.P.). UK DHSC/UK Aid/NIHR (PR-OD-1017-20001: H.P.G). UK MRC (MC_PC_19065 - Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: S.C., T.J., W.J.E., Y.L.; MR/P014658/1: G.M.K.), UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care (T.J.). UKRI (MR/ V028456/1: Y.J.). Wellcome Trust (206250/Z/17/Z: A.J.K., T.W.R.; 206471/Z/17/Z: O.J.B.; 208812/Z/17/Z: S.C.; 210758/Z/18/Z: J.D.M., J.H., S.A., S.F., S.R.M.; 221303/ Z/20/Z: M.K.; UNS110424: F.K.). No funding (A.M.F., D.C.T., Y.W.D.C.). This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. Open Access: This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY). Publisher Copyright: {\textcopyright} 2021 the Author(s). Published by PNAS. Citation: How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology. Naomi R. Waterlow, Edwin van Leeuwen, Nicholas G. Davies, CMMID COVID-19 Working Group, Stefan Flasche, Rosalind M. Eggo. Proceedings of the National Academy of Sciences Dec 2021, 118 (49) e2108395118 DOI: 10.1073/pnas.2108395118",

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TY - JOUR

T1 - How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology

AU - Waterlow, Naomi R.

AU - van Leeuwen, Edwin

AU - Davies, Nicholas G.

AU - Flasche, Stefan

AU - Eggo, Rosalind M.

N1 - Funding Information: We thank Dr. Edward M. Hill for his helpful comments on the preprint of this paper. N.R.W. was supported by the Medical Research Council (Grants MR/N013638/1 and MR/V015737/1) and National Institute for Health Research (NIHR) (Grant COV0076). E.v.L. was supported by the NIHR Health Protection Research Unit in Modelling and Health Economics, a partnership between PHE, Imperial College London, and the London School of Hygiene and Tropical Medicine (LSHTM) (Grant NIHR200908). E.v.L. was supported by the European Union's Horizon 2020 Research and Innovation Programme - Project EpiPose (101003688). S.F. is funded through a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (Grant 208812/Z/17/Z). R.M.E. acknowledges an Health Data Research (HDR) UK Innovation Fellowship (Grant MR/S003975/1), Medical Research Council - MRC (Grant MC_PC 19065), and NIHR (Grant NIHR200908) for the Health Protection Research Unit in Modelling and Economics at LSHTM. The following authors were part of the Centre for Mathematical Modelling of Infectious Disease COVID-19 Working Group. Each contributed in processing, cleaning, and interpretation of data; interpreted findings; contributed to the manuscript; and approved the work for publication: Rachael Pung, Paul Mee, William Waites, Damien C. Tully, Katherine E. Atkins, C. Julian Villabona-Arenas, Graham Medley, Frank G. Sandmann, Anna M. Foss, Sophie R. Meakin, Carl A. B. Pearson, Emilie Finch, Nikos I. Bosse, Christopher I. Jarvis, Kiesha Prem, Alicia Rosello, Kevin van Zandvoort, Rosanna C. Barnard, Jiayao Lei, Yang Liu, Adam J. Kucharski, Ciara V. McCarthy, Sam Abbott, Emily S. Nightingale, Joel Hellewell, Thibaut Jombart, David Hodgson, Gwenan M. Knight, Amy Gimma, Yung-Wai Desmond Chan, Yalda Jafari, Samuel Clifford, Timothy W. Russell, Fiona Yueqian Sun, Simon R. Procter, Akira Endo, Oliver Brady, Kaja Abbas, Billy J. Quilty, Mark Jit, Sebastian Funk, Fabienne Krauer, Matthew Quaife, Hamish P. Gibbs, W. John Edmunds, Mihaly Koltai, Kathleen O'Reilly, Rachel Lowe, and James D. Munday. The following funding sources are acknowledged as providing funding for the working group authors. This research was partly funded by the Bill & Melinda Gates Foundation (INV-001754: MQ; INV-003174: J.Y.L., K.P., M.J., Y.L.; INV-016832: S.R.P.; NTD Modelling Consortium OPP1184344: C.A.B.P., G.F.M.; OPP1139859: B.J.Q; OPP1183986: E.S.N; OPP1191821: K.O.). Bill and Melinda Gates Foundation - BMGF (INV-016832; OPP1157270: K.A). Brazil-UK Centre for Arbovirus Discovery, Diagnosis, Genomics and Epidemiology - CADDE MR/S0195/1 & The São Paulo Research Foundation - FAPESP 18/14389-0 (P.M.). European & Developing Countries Clinical Trials Partnership - EDCTP2 (RIA2020EF-2983-CSIGN: H.P.G.). Elrha Research for Health in Humanitarian Crises (R2HC/UK), Foreign, Commonwealth & Development Office (FCDO), Wellcome Trust (K.v.Z.). European Research Council (ERC) Starting Grant (#757699: M.Q.). ERC (SG 757688: C.J.V.A., K.E.A.). European Union's Horizon 2020 research and innovation programme - project EpiPose (101003688: A.G., K.P., M.J., R.C.B., W.J.E., Y.L.). FCDO/Wellcome Trust (Epidemic Preparedness Coronavirus research programme 221303/Z/20/Z: C.A.B.P., K.v.Z.). Global Challenges Research Fund (GCRF) project 'RECAP' managed through Research Councils UK (RCUK) and Economic and Social Research Council (ESRC) (ES/ P010873/1: C.I.J., T.J.). Health Protection Research Unit (HPRU) (NIHR200908: N.I.B.). Innovation Fund (01VSF18015: F.K.). MRC (MR/N013638/1: E.F.; MR/ V027956/1: W.W.). Nakajima Foundation (A.E.). NIHR (16/136/46: B.J.Q.; 16/137/109: B.J.Q., F.Y.S., M.J., Y.L.; 1R01AI141534-01A1: D.H.; Health Protection Research Unit for Modelling Methodology HPRU-2012-10096: T.J.; NIHR200908: A.J.K.; NIHR200929: C.V.M., F.G.S., M.J.; PR-OD-1017-20002: A.R., W.J.E.). Royal Society (Dorothy Hodgkin Fellowship: R.L.). Singapore Ministry of Health (R.P.). UK DHSC/UK Aid/NIHR (PR-OD-1017-20001: H.P.G). UK MRC (MC_PC_19065 - Covid 19: Understanding the dynamics and drivers of the COVID-19 epidemic using real-time outbreak analytics: S.C., T.J., W.J.E., Y.L.; MR/P014658/1: G.M.K.), UK Public Health Rapid Support Team funded by the United Kingdom Department of Health and Social Care (T.J.). UKRI (MR/ V028456/1: Y.J.). Wellcome Trust (206250/Z/17/Z: A.J.K., T.W.R.; 206471/Z/17/Z: O.J.B.; 208812/Z/17/Z: S.C.; 210758/Z/18/Z: J.D.M., J.H., S.A., S.F., S.R.M.; 221303/ Z/20/Z: M.K.; UNS110424: F.K.). No funding (A.M.F., D.C.T., Y.W.D.C.). This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care. Open Access: This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY). Publisher Copyright: © 2021 the Author(s). Published by PNAS. Citation: How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology. Naomi R. Waterlow, Edwin van Leeuwen, Nicholas G. Davies, CMMID COVID-19 Working Group, Stefan Flasche, Rosalind M. Eggo. Proceedings of the National Academy of Sciences Dec 2021, 118 (49) e2108395118 DOI: 10.1073/pnas.2108395118

PY - 2021/12/3

Y1 - 2021/12/3

N2 - We hypothesized that cross-protection from seasonal epidemics of human coronaviruses (HCoVs) could have affected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, including generating reduced susceptibility in children. To determine what the prepandemic distribution of immunity to HCoVs was, we fitted a mathematical model to 6 y of seasonal coronavirus surveillance data from England and Wales. We estimated a duration of immunity to seasonal HCoVs of 7.8 y (95% CI 6.3 to 8.1) and show that, while cross-protection between HCoV and SARS-CoV-2 may contribute to the age distribution, it is insufficient to explain the age pattern of SARS-CoV-2 infections in the first wave of the pandemic in England and Wales. Projections from our model illustrate how different strengths of cross-protection between circulating coronaviruses could determine the frequency and magnitude of SARS-CoV-2 epidemics over the coming decade, as well as the potential impact of cross-protection on future seasonal coronavirus transmission.

AB - We hypothesized that cross-protection from seasonal epidemics of human coronaviruses (HCoVs) could have affected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission, including generating reduced susceptibility in children. To determine what the prepandemic distribution of immunity to HCoVs was, we fitted a mathematical model to 6 y of seasonal coronavirus surveillance data from England and Wales. We estimated a duration of immunity to seasonal HCoVs of 7.8 y (95% CI 6.3 to 8.1) and show that, while cross-protection between HCoV and SARS-CoV-2 may contribute to the age distribution, it is insufficient to explain the age pattern of SARS-CoV-2 infections in the first wave of the pandemic in England and Wales. Projections from our model illustrate how different strengths of cross-protection between circulating coronaviruses could determine the frequency and magnitude of SARS-CoV-2 epidemics over the coming decade, as well as the potential impact of cross-protection on future seasonal coronavirus transmission.

KW - COVID-19

KW - Coronaviruses

KW - Cross-protection

KW - Immunity

KW - SARS-CoV-2

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U2 - 10.1073/pnas.2108395118

DO - 10.1073/pnas.2108395118

M3 - Article

AN - SCOPUS:85120863998

SN - 0027-8424

VL - 118

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

IS - 49

M1 - e2108395118

ER -

How immunity from and interaction with seasonal coronaviruses can shape SARS-CoV-2 epidemiology

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