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State-level tracking of COVID-19 in the United States

Author

Listed:
  • H. Juliette T. Unwin

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Swapnil Mishra

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Valerie C. Bradley

    (University of Oxford)

  • Axel Gandy

    (Imperial College)

  • Thomas A. Mellan

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Helen Coupland

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Jonathan Ish-Horowicz

    (Imperial College)

  • Michaela A. C. Vollmer

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Charles Whittaker

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Sarah L. Filippi

    (Imperial College)

  • Xiaoyue Xi

    (Imperial College)

  • Mélodie Monod

    (Imperial College)

  • Oliver Ratmann

    (Imperial College)

  • Michael Hutchinson

    (University of Oxford)

  • Fabian Valka
  • Harrison Zhu

    (Imperial College)

  • Iwona Hawryluk

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Philip Milton

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Kylie E. C. Ainslie

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Marc Baguelin

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College
    London School of Hygiene and Tropical Medicine)

  • Adhiratha Boonyasiri

    (Imperial College London)

  • Nick F. Brazeau

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Lorenzo Cattarino

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Zulma Cucunuba

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Gina Cuomo-Dannenburg

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Ilaria Dorigatti

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Oliver D. Eales

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Jeffrey W. Eaton

    (Imperial College)

  • Sabine L. Elsland

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Richard G. FitzJohn

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Katy A. M. Gaythorpe

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • William Green

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Wes Hinsley

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Benjamin Jeffrey

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Edward Knock

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Daniel J. Laydon

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • John Lees

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Gemma Nedjati-Gilani

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Pierre Nouvellet

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College
    University of Sussex)

  • Lucy Okell

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Kris V. Parag

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Igor Siveroni

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Hayley A. Thompson

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Patrick Walker

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Caroline E. Walters

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Oliver J. Watson

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College
    Brown University)

  • Lilith K. Whittles

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Azra C. Ghani

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Neil M. Ferguson

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Steven Riley

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Christl A. Donnelly

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College
    University of Oxford)

  • Samir Bhatt

    (Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Imperial College)

  • Seth Flaxman

    (Imperial College)

Abstract

As of 1st June 2020, the US Centres for Disease Control and Prevention reported 104,232 confirmed or probable COVID-19-related deaths in the US. This was more than twice the number of deaths reported in the next most severely impacted country. We jointly model the US epidemic at the state-level, using publicly available death data within a Bayesian hierarchical semi-mechanistic framework. For each state, we estimate the number of individuals that have been infected, the number of individuals that are currently infectious and the time-varying reproduction number (the average number of secondary infections caused by an infected person). We use changes in mobility to capture the impact that non-pharmaceutical interventions and other behaviour changes have on the rate of transmission of SARS-CoV-2. We estimate that Rt was only below one in 23 states on 1st June. We also estimate that 3.7% [3.4%–4.0%] of the total population of the US had been infected, with wide variation between states, and approximately 0.01% of the population was infectious. We demonstrate good 3 week model forecasts of deaths with low error and good coverage of our credible intervals.

Suggested Citation

  • H. Juliette T. Unwin & Swapnil Mishra & Valerie C. Bradley & Axel Gandy & Thomas A. Mellan & Helen Coupland & Jonathan Ish-Horowicz & Michaela A. C. Vollmer & Charles Whittaker & Sarah L. Filippi & Xi, 2020. "State-level tracking of COVID-19 in the United States," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-19652-6
    DOI: 10.1038/s41467-020-19652-6
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    Cited by:

    1. Vinicius Albani & Matheus Grasselli & Weijie Pang & Jorge P. Zubelli, 2022. "The Interplay between COVID-19 and the Economy in Canada," JRFM, MDPI, vol. 15(10), pages 1-26, October.
    2. Liu, Shasha & Yamamoto, Toshiyuki, 2022. "Role of stay-at-home requests and travel restrictions in preventing the spread of COVID-19 in Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 1-16.

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