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

Publication ,  Journal Article
Unwin, HJT; Mishra, S; Bradley, VC; Gandy, A; Mellan, TA; Coupland, H; Ish-Horowicz, J; Vollmer, MAC; Whittaker, C; Filippi, SL; Xi, X; Zhu, H ...
Published in: Nature communications
December 2020

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.

Duke Scholars

Published In

Nature communications

DOI

EISSN

2041-1723

ISSN

2041-1723

Publication Date

December 2020

Volume

11

Issue

1

Start / End Page

6189

Related Subject Headings

  • Virus Diseases
  • United States
  • Pandemics
  • Models, Statistical
  • Humans
  • COVID-19
  • Bayes Theorem
 

Citation

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MLA
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Unwin, H. J. T., Mishra, S., Bradley, V. C., Gandy, A., Mellan, T. A., Coupland, H., … Flaxman, S. (2020). State-level tracking of COVID-19 in the United States. Nature Communications, 11(1), 6189. https://doi.org/10.1038/s41467-020-19652-6
Unwin, H Juliette T., Swapnil Mishra, Valerie C. Bradley, Axel Gandy, Thomas A. Mellan, Helen Coupland, Jonathan Ish-Horowicz, et al. “State-level tracking of COVID-19 in the United States.Nature Communications 11, no. 1 (December 2020): 6189. https://doi.org/10.1038/s41467-020-19652-6.
Unwin HJT, Mishra S, Bradley VC, Gandy A, Mellan TA, Coupland H, et al. State-level tracking of COVID-19 in the United States. Nature communications. 2020 Dec;11(1):6189.
Unwin, H. Juliette T., et al. “State-level tracking of COVID-19 in the United States.Nature Communications, vol. 11, no. 1, Dec. 2020, p. 6189. Epmc, doi:10.1038/s41467-020-19652-6.
Unwin HJT, Mishra S, Bradley VC, Gandy A, Mellan TA, Coupland H, Ish-Horowicz J, Vollmer MAC, Whittaker C, Filippi SL, Xi X, Monod M, Ratmann O, Hutchinson M, Valka F, Zhu H, Hawryluk I, Milton P, Ainslie KEC, Baguelin M, Boonyasiri A, Brazeau NF, Cattarino L, Cucunuba Z, Cuomo-Dannenburg G, Dorigatti I, Eales OD, Eaton JW, van Elsland SL, FitzJohn RG, Gaythorpe KAM, Green W, Hinsley W, Jeffrey B, Knock E, Laydon DJ, Lees J, Nedjati-Gilani G, Nouvellet P, Okell L, Parag KV, Siveroni I, Thompson HA, Walker P, Walters CE, Watson OJ, Whittles LK, Ghani AC, Ferguson NM, Riley S, Donnelly CA, Bhatt S, Flaxman S. State-level tracking of COVID-19 in the United States. Nature communications. 2020 Dec;11(1):6189.

Published In

Nature communications

DOI

EISSN

2041-1723

ISSN

2041-1723

Publication Date

December 2020

Volume

11

Issue

1

Start / End Page

6189

Related Subject Headings

  • Virus Diseases
  • United States
  • Pandemics
  • Models, Statistical
  • Humans
  • COVID-19
  • Bayes Theorem