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.

为减轻人口的COVID-19负担，需要公平有效地基于风险分配稀缺的预防资源，包括疫苗¹。为了帮助这项工作，我们基于各种社会人口统计学因素和美国人口的既有条件，开发了用于COVID-19死亡率的通用人口风险计算器，将来自英国的OpenSAFELY研究的信息与按年龄和种族划分的死亡率相结合美国各州。我们通过在社区一级纳入有关大流行动态的信息，对工具进行了定制，以在未来的时间范围内得出绝对风险估计。我们将该模型应用于各种来源的风险因素分布数据，以分别预测美国477个城市的成年人口和美国3,113个县65岁及65岁以上的Medicare人群的风险。验证分析使用了2020年6月7日至2020年10月1日的54,444例死亡，表明该模型已针对美国人群进行了很好的校准。预测表明，该模型可以识别相对较小的一部分人口（例如4.3％），其死亡人数可能不成比例（例如48.7％），但是各个社区的风险差异很大。我们提供基于Web的风险计算器和交互式地图，用于查看社区级别的风险。