Back to Search Start Over

Modeling COVID-19 scenarios for the United States

Authors :
Kirsten E. Wiens
Brittney Sheena
Alize Ferrari
Simon Hay
Rafael Lozano
Christopher Adolph
Ali Mokdad
Laurie Marczak
Erin Hulland
James Collins
Fiona Charlson
Source :
Nature Medicine
Publication Year :
2020
Publisher :
Nature Publishing Group US, 2020.

Abstract

We use COVID-19 case and mortality data from 1 February 2020 to 21 September 2020 and a deterministic SEIR (susceptible, exposed, infectious and recovered) compartmental framework to model possible trajectories of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and the effects of non-pharmaceutical interventions in the United States at the state level from 22 September 2020 through 28 February 2021. Using this SEIR model, and projections of critical driving covariates (pneumonia seasonality, mobility, testing rates and mask use per capita), we assessed scenarios of social distancing mandates and levels of mask use. Projections of current non-pharmaceutical intervention strategies by state—with social distancing mandates reinstated when a threshold of 8 deaths per million population is exceeded (reference scenario)—suggest that, cumulatively, 511,373 (469,578–578,347) lives could be lost to COVID-19 across the United States by 28 February 2021. We find that achieving universal mask use (95% mask use in public) could be sufficient to ameliorate the worst effects of epidemic resurgences in many states. Universal mask use could save an additional 129,574 (85,284–170,867) lives from September 22, 2020 through the end of February 2021, or an additional 95,814 (60,731–133,077) lives assuming a lesser adoption of mask wearing (85%), when compared to the reference scenario.<br />A modeling study using case and mortality data from the first 8 months of the COVID-19 pandemic in the United States explores five potential future scenarios of social distancing mandates and mask use at the state level, with projections of the course of the epidemic through winter 2021.

Details

Language :
English
ISSN :
1546170X and 10788956
Volume :
27
Issue :
1
Database :
OpenAIRE
Journal :
Nature Medicine
Accession number :
edsair.doi.dedup.....da1ddfeb729ffc9a49e6b5a569fe8d9a