Crowding and the shape of COVID-19 epidemics

Benjamin Rader; Samuel V. Scarpino; Anjalika Nande; Alison L. Hill; Ben Adlam; Robert C. Reiner; David M. Pigott; Bernardo Gutierrez; Alexander E. Zarebski; Munik Shrestha; John S. Brownstein; Marcia C. Castro; Christopher Dye; Huaiyu Tian; Oliver G. Pybus; Moritz U.G. Kraemer

doi:10.1038/s41591-020-1104-0

Crowding and the shape of COVID-19 epidemics

Benjamin Rader, Samuel V. Scarpino, Anjalika Nande, Alison L. Hill, Ben Adlam, Robert C. Reiner, David M. Pigott, Bernardo Gutierrez, Alexander E. Zarebski, Munik Shrestha, John S. Brownstein, Marcia C. Castro, Christopher Dye, Huaiyu Tian, Oliver G. Pybus, Moritz U.G. Kraemer

School of Medicine

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

27 Scopus citations

Abstract

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread^1–4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China^5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking⁷. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.

Original language	English (US)
Pages (from-to)	1829-1834
Number of pages	6
Journal	Nature medicine
Volume	26
Issue number	12
DOIs	https://doi.org/10.1038/s41591-020-1104-0
State	Published - Dec 2020

ASJC Scopus subject areas

Biochemistry, Genetics and Molecular Biology(all)

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10.1038/s41591-020-1104-0

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title = "Crowding and the shape of COVID-19 epidemics",

abstract = "The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread1–4. During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China5,6. Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking7. In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics.",

author = "Benjamin Rader and Scarpino, {Samuel V.} and Anjalika Nande and Hill, {Alison L.} and Ben Adlam and Reiner, {Robert C.} and Pigott, {David M.} and Bernardo Gutierrez and Zarebski, {Alexander E.} and Munik Shrestha and Brownstein, {John S.} and Castro, {Marcia C.} and Christopher Dye and Huaiyu Tian and Pybus, {Oliver G.} and Kraemer, {Moritz U.G.}",

note = "Funding Information: The authors thank K. Cordiano for statistical assistance. We thank the members of the Open COVID-19 Data Working Group. The members of the group are listed in the Supplementary Note. B.R. acknowledges funding from Google.org. M.U.G.K. acknowledges funding from the European Commission H2020 program (MOOD project) and a Branco Weiss Fellowship. O.G.P., M.U.G.K., A.E.Z. and H.T. acknowledge funding from the Oxford Martin School. H.T. acknowledges funding from the Beijing Science and Technology Planning Project (Z201100005420010). A.L.H. and A.N. acknowledge funding from the National Institutes of Health (DP5OD019851). The funding bodies had no role in study design, data collection and analysis, preparation of the manuscript or the decision to publish. All authors saw and approved the manuscript. Publisher Copyright: {\textcopyright} 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.",

year = "2020",

month = dec,

doi = "10.1038/s41591-020-1104-0",

language = "English (US)",

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AU - Rader, Benjamin

AU - Scarpino, Samuel V.

AU - Nande, Anjalika

AU - Hill, Alison L.

AU - Adlam, Ben

AU - Reiner, Robert C.

AU - Pigott, David M.

AU - Gutierrez, Bernardo

AU - Zarebski, Alexander E.

AU - Shrestha, Munik

AU - Brownstein, John S.

AU - Castro, Marcia C.

AU - Dye, Christopher

AU - Tian, Huaiyu

AU - Pybus, Oliver G.

AU - Kraemer, Moritz U.G.

N1 - Funding Information: The authors thank K. Cordiano for statistical assistance. We thank the members of the Open COVID-19 Data Working Group. The members of the group are listed in the Supplementary Note. B.R. acknowledges funding from Google.org. M.U.G.K. acknowledges funding from the European Commission H2020 program (MOOD project) and a Branco Weiss Fellowship. O.G.P., M.U.G.K., A.E.Z. and H.T. acknowledge funding from the Oxford Martin School. H.T. acknowledges funding from the Beijing Science and Technology Planning Project (Z201100005420010). A.L.H. and A.N. acknowledge funding from the National Institutes of Health (DP5OD019851). The funding bodies had no role in study design, data collection and analysis, preparation of the manuscript or the decision to publish. All authors saw and approved the manuscript. Publisher Copyright: © 2020, The Author(s), under exclusive licence to Springer Nature America, Inc.

PY - 2020/12

Y1 - 2020/12

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Crowding and the shape of COVID-19 epidemics

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