RESUMO
Reducing COVID-19 illness and mortality for populations in the future will require equitable and effective risk-based allocations of scarce preventive resources, including early available vaccines. To aid in this effort, we develop a risk calculator for COVID-19 mortality based on various socio-demographic factors and pre-existing conditions for the US adult population by combining information from the UK-based OpenSAFELY study, with mortality rates by age and ethnicity available across US states. We tailor the tool to produce absolute risks for individuals in future time frames by incorporating information on pandemic dynamics at the community level as available from forecasting models. We apply this risk calculation model to available data on prevalence and co-occurrences of the risk-factors from a variety of data sources to project risk for the general adult population across 477 US cities (defined as Census Places) and for the 65 years and older Medicare population across 3,113 US counties, respectively. Validation analyses based on these projected risks and data on tens of thousands of recent deaths show that the model is well calibrated for the US population. Projections show that the model can identify relatively small fractions of the population (e.g. 4.3%) which will lead to a disproportionately large number of deaths (e.g. 49.8%), and thus will be useful for effectively targeting individuals for early vaccinations, but there will be wide variation in risk distribution across US communities. We provide a web-based tool for individualized risk calculations and interactive maps for viewing the city-, county- and state-level risk projections.
