虽然研究表明COVID-19的发病率和死亡风险存在差异,但很少有努力揭示初始社区传播强度的区域差异。我们使用约翰霍普金斯大学系统科学与工程中心的县级COVID-19数据进行了一项全国性研究。我们通过计算COVID-19在每个县传播的前4周的发病率和病例死亡风险(CFR)来表征初始社区COVID-19攻击的强度。我们使用多变量多水平多项逻辑回归来估计县级特征与COVID-19发病率和CFR的关系。在3143个县中,我们在6月1日纳入了1,052例,至少有100例报告病例。中位发病率为每100,000人口193.4(IQR:94.2-397.5)。病例死亡风险中位数为3.6%(IQR:1.4-7.3)。年龄中位数,农村人口,人口密度,教育水平较低,没有保险的人口,肥胖,COPD患病率呈正相关,而人口,女性性别,种族(亚洲,白色),高等教育,过度饮酒与COVID-19初始发病率呈负相关。年龄中位数,女性性别,亚洲种族,人口密度,高等教育,过度饮酒,重症监护病房病床,空气传播感染隔离室呈正相关,而西班牙裔种族,教育水平较低,肥胖(悖论),未参保人群与初始COVID-19CFR呈负相关。
While studies indicate differences in incidence and
case fatality risk of COVID-19, few efforts have shed light on regional variations in the intensity of initial community spread. We conducted a nationwide study using county-level data on COVID-19 from Center for Systems Science and Engineering at Johns Hopkins University. We characterized intensity of initial community COVID-19 attack by calculating the incidence and
case fatality risk (CFR) for the first 4-week period of COVID-19 spread in each county. We used multivariate multilevel multinomial logistic regression to estimate the association of county-level characteristics with COVID-19 incidence and CFR. Of 3,143 counties, we included 1,052 with at least 100 reported cases on June 1st. Median incidence was 193.4 per 100,000 population (IQR: 94.2-397.5). Median
case fatality risk was 3.6% (IQR: 1.4-7.3). Median age, rural population, population density, lower education, uninsured population, obesity, COPD prevalence were positively associated, while population, female sex, races (Asian, white), higher education, excessive drinking were negatively associated with initial COVID-19 incidence. Median age, female sex, Asian race, population density, higher education, excessive drinking, Intensive Care Unit beds, airborne infection isolation rooms were positively associated, while Hispanic ethnicity, lower education, obesity (paradox), uninsured population were negatively associated with initial COVID-19 CFR.