Department of Medicine (Affiliated), Stanford University, Stanford, California, United States of America.
Department of Medicine and Public Health, University of California Los Angeles, Los Angeles, California, United States of America.
PLoS One. 2020 Dec 7;15(12):e0243026. doi: 10.1371/journal.pone.0243026. eCollection 2020.
We describe a method to estimate individual risks of hospitalization and death attributable to non-household and household transmission of SARS-CoV-2 using available public data on confirmed-case incidence data along with estimates of the clinical fraction, timing of transmission, isolation adherence, secondary infection risks, contact rates, and case-hospitalization and case-fatality ratios. Using the method, we estimate that risks for a 90-day period at the median daily summertime U.S. county confirmed COVID-19 case incidence of 10.8 per 100,000 and pre-pandemic contact rates range from 0.4 to 8.9 per 100,000 for the four deciles of age between 20 and 60 years. The corresponding 90-day period risk of hospitalization ranges from 13.7 to 69.2 per 100,000. Assuming a non-household secondary infection risk of 4% and pre-pandemic contact rates, the share of transmissions attributable to household settings ranges from 73% to 78%. These estimates are sensitive to the parameter assumptions; nevertheless, they are comparable to the COVID-19 hospitalization and fatality rates observed over the time period. We conclude that individual risk of hospitalization and death from SARS-CoV-2 infection is calculable from publicly available data sources. Access to publicly reported infection incidence data by setting and other exposure characteristics along with setting specific estimates of secondary infection risk would allow for more precise individual risk estimation.
我们描述了一种使用已公布的确诊病例数据以及临床比例、传播时间、隔离依从性、二次感染风险、接触率和病例住院及病死率的估计值来估计非家庭和家庭传播 SARS-CoV-2 导致住院和死亡的个体风险的方法。使用该方法,我们估计在夏季美国县日均确诊 COVID-19 病例为 10.8/10 万、流行前接触率为 0.4-8.9/10 万的情况下,年龄在 20-60 岁之间的四个十分位数的 90 天期间风险为每 10 万人中有 0.4-8.9/10 万。相应的 90 天期间住院风险为每 10 万人中有 13.7-69.2 人。假设非家庭二次感染风险为 4%,流行前接触率不变,家庭环境传播的比例在 73%-78%之间。这些估计值对参数假设敏感,但与观察到的 COVID-19 住院和病死率相当。我们得出结论,从公共数据源可计算出个体因 SARS-CoV-2 感染而住院和死亡的风险。通过设置和其他暴露特征获得公众报告的感染发生率数据以及设置特定的二次感染风险估计值,将能够更准确地进行个体风险估计。