Background The medical, societal, and economic impact of the coronavirus disease 2019 (COVID-19) pandemic has unknown effects on overall population mortality. Previous models of population mortality are based on death over days among infected people, nearly all of whom thus far have underlying conditions. Models have not incorporated information on high-risk conditions or their longer-term baseline (pre-COVID-19) mortality. We estimated the excess number of deaths over 1 year under different COVID-19 incidence scenarios based on varying levels of transmission suppression and differing mortality impacts based on different relative risks for the disease. Methods In this population-based cohort study, we used linked primary and secondary care electronic health records from England (Health Data Research UK-CALIBER). We report prevalence of underlying conditions defined by Public Health England guidelines (from March 16, 2020) in individuals aged 30 years or older registered with a practice between 1997 and 2017, using validated, openly available phenotypes for each condition. We estimated 1-year mortality in each condition, developing simple models (and a tool for calculation) of excess COVID-19-related deaths, assuming relative impact (as relative risks [RRs]) of the COVID-19 pandemic (compared with background mortality) of 1·5, 2·0, and 3·0 at differing infection rate scenarios, including full suppression (0·001%), partial suppression (1%), mitigation (10%), and do nothing (80%). We also developed an online, public, prototype risk calculator for excess death estimation. Findings We included 3 862 012 individuals (1 957 935 [50·7%] women and 1 904 077 [49·3%] men). We estimated that more than 20% of the study population are in the high-risk category, of whom 13·7% were older than 70 years and 6·3% were aged 70 years or younger with at least one underlying condition. 1-year mortality in the high-risk population was estimated to be 4·46% (95% CI 4·41-4·51). Age and underlying conditions combined to influence background risk, varying markedly across conditions. In a full suppression scenario in the UK population, we estimated that there would be two excess deaths (vs baseline deaths) with an RR of 1·5, four with an RR of 2·0, and seven with an RR of 3·0. In a mitigation scenario, we estimated 18 374 excess deaths with an RR of 1·5, 36 749 with an RR of 2·0, and 73 498 with an RR of 3·0. In a do nothing scenario, we estimated 146 996 excess deaths with an RR of 1·5, 293 991 with an RR of 2·0, and 587 982 with an RR of 3·0. Interpretation We provide policy makers, researchers, and the public a simple model and an online tool for understanding excess mortality over 1 year from the COVID-19 pandemic, based on age, sex, and underlying condition-specific estimates. These results signal the need for sustained stringent suppression measures as well as sustained efforts to target those at highest risk because of underlying conditions with a range of preventive interventions. Countries should assess the overall (direct and indirect) effects of the pandemic on excess mortality. Funding National Institute for Health Research University College London Hospitals Biomedical Research Centre, Health Data Research UK.

中文翻译：

---

根据基本条件和年龄估计与 COVID-19 大流行相关的一年超额死亡率：一项基于人群的队列研究。


背景 2019 年冠状病毒病 (COVID-19) 大流行的医疗、社会和经济影响对总体人口死亡率的影响尚不清楚。以前的人口死亡率模型是基于感染者几天内的死亡情况，到目前为止，几乎所有感染者都患有基础疾病。模型未纳入有关高风险状况或其长期基线（COVID-19 之前）死亡率的信息。我们根据不同的传播抑制水平和不同的死亡率影响（基于该疾病的不同相对风险）估计了不同 COVID-19 发病情况下一年内的超额死亡人数。方法 在这项基于人群的队列研究中，我们使用了来自英国的初级和二级保健电子健康记录（英国健康数据研究中心-CALIBRE）。我们报告了 1997 年至 2017 年间注册执业的 30 岁或以上个人中英国公共卫生指南（自 2020 年 3 月 16 日起）定义的潜在疾病的患病率，使用每种疾病经过验证的、公开的表型。我们估计了每种情况下的 1 年死亡率，开发了与 COVID-19 相关的过量死亡的简单模型（和计算工具），假设了 COVID-19 大流行的相对影响（作为相对风险 [RR]）（与背景相比）不同感染率场景下的死亡率）分别为1·5、2·0和3·0，包括完全抑制（0·001%）、部分抑制（1%）、缓解（10%）和不采取任何措施（80%） ）。我们还开发了一个在线、公共、原型风险计算器，用于估计超额死亡。结果 我们纳入了 3 862 012 人（1 957 935 [50·7%] 女性和 1 904 077 [49·3%] 男性）。 我们估计超过 20% 的研究人群属于高危人群，其中 13·7% 年龄超过 70 岁，6·3% 年龄在 70 岁或以下且至少患有一种潜在疾病。高危人群的 1 年死亡率估计为 4·46% (95% CI 4·41-4·51)。年龄和基础条件共同影响背景风险，不同条件下差异显着。在英国人口完全抑制的情况下，我们估计会出现 2 例过量死亡（相对于基线死亡），RR 为 1·5，4 例 RR 为 2·0，7 例 RR 为 3·0 。在缓解情景中，我们估计 RR 为 1·5 的超额死亡人数为 18 374 人，RR 为 2·0 的超额死亡人数为 36 749 人，RR 为 3·0 的超额死亡人数为 73 498 人。在不采取任何措施的情况下，我们估计 RR 为 1·5 的超额死亡人数为 146 996 人，RR 为 2·0 的超额死亡人数为 293 991 人，RR 为 3·0 的超额死亡人数为 587 982 人。解释 我们为政策制定者、研究人员和公众提供一个简单的模型和在线工具，用于根据年龄、性别和具体情况的基本估计来了解 COVID-19 大流行一年内的超额死亡率。这些结果表明，需要持续采取严格的抑制措施，并持续努力针对那些因潜在条件而面临最高风险的人，采取一系列预防性干预措施。各国应评估这一流行病对过高死亡率的总体（直接和间接）影响。资助英国国家健康研究所、伦敦大学学院医院生物医学研究中心、英国健康数据研究中心。