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

Authors :
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
Source :
Nature communications [Nat Commun] 2020 Dec 03; Vol. 11 (1), pp. 6189. Date of Electronic Publication: 2020 Dec 03.
Publication Year :
2020

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 R <subscript>t</subscript> 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.

Details

Language :
English
ISSN :
2041-1723
Volume :
11
Issue :
1
Database :
MEDLINE
Journal :
Nature communications
Publication Type :
Academic Journal
Accession number :
33273462
Full Text :
https://doi.org/10.1038/s41467-020-19652-6