Individual and community-level risk for COVID-19 mortality in the United States
dc.contributor.author | Jin, Jin | |
dc.contributor.author | Agarwala, Neha | |
dc.contributor.author | Kundu, Prosenjit | |
dc.contributor.author | Harvey, Benjamin | |
dc.contributor.author | Zhang, Yuqi | |
dc.contributor.author | Wallace, Eliza | |
dc.contributor.author | Chatterjee, Nilanjan | |
dc.date.accessioned | 2021-01-20T18:10:27Z | |
dc.date.available | 2021-01-20T18:10:27Z | |
dc.date.issued | 2020-12-11 | |
dc.description.abstract | Reducing COVID-19 burden for populations will require equitable and effective risk-based allocations of scarce preventive resources, including vaccinations. 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. | en_US |
dc.description.sponsorship | We thank A. Meisner from the John Hopkins University, Biostatistics Department and M. García-Closas from the Division of Cancer Epidemiology and Genetics at the NCI for their comments on a previous version of the manuscript. This research was funded by the Bloomberg Distinguished Professorship endowment. | en_US |
dc.description.uri | https://www.nature.com/articles/s41591-020-01191-8 | en_US |
dc.genre | journal articles | en_US |
dc.identifier | doi:10.13016/m29vm3-4zug | |
dc.identifier.citation | Jin, Jin; Agarwala, Neha; Kundu, Prosenjit; Harvey, Benjamin; Zhang, Yuqi; Wallace, Eliza; Chatterjee, Nilanjan; Individual and community-level risk for COVID-19 mortality in the United States; Nature Medicine (2020); https://www.nature.com/articles/s41591-020-01191-8 | en_US |
dc.identifier.uri | https://doi.org/10.1038/s41591-020-01191-8 | |
dc.identifier.uri | http://hdl.handle.net/11603/20562 | |
dc.language.iso | en_US | en_US |
dc.publisher | Nature | en_US |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Mathematics Department Collection | |
dc.relation.ispartof | UMBC Student Collection | |
dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
dc.subject | diseases | en_US |
dc.subject | health care | en_US |
dc.subject | medical research | en_US |
dc.subject | risk factors | en_US |
dc.title | Individual and community-level risk for COVID-19 mortality in the United States | en_US |
dc.type | Text | en_US |
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