Individual and community-level risk for COVID-19 mortality in the United States

Jin Jin, Neha Agarwala, Prosenjit Kundu, Benjamin Harvey, Yuqi Zhang, Eliza Wallace, Nilanjan Chatterjee

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations1. To aid in this effort, we developed a general population risk calculator for COVID-19 mortality based on various sociodemographic factors and pre-existing conditions for the US population, combining information from the UK-based OpenSAFELY study with mortality rates by age and ethnicity across US states. We tailored the tool to produce absolute risk estimates in future time frames by incorporating information on pandemic dynamics at the community level. We applied the model to data on risk factor distribution from a variety of sources to project risk for the general adult population across 477 US cities and for the Medicare population aged 65 years and older across 3,113 US counties, respectively. Validation analyses using 54,444 deaths from 7 June to 1 October 2020 show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (for example 4.3%) that might experience a disproportionately large number of deaths (for example 48.7%), but there is wide variation in risk across communities. We provide a web-based risk calculator and interactive maps for viewing community-level risks.

Original languageEnglish (US)
Pages (from-to)264-269
Number of pages6
JournalNature medicine
Issue number2
StatePublished - Feb 2021

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology


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