Program in Public Health and Department of Family, Population, and Preventive Medicine, Renaissance School of Medicine at Stony Brook, Stony Brook, NY, USA.
Program in Public Health, Renaissance School of Medicine at Stony Brook, Stony Brook, NY, USA.
Soc Sci Med. 2021 Jan;268:113554. doi: 10.1016/j.socscimed.2020.113554. Epub 2020 Nov 30.
To quantify the contribution variation in socioeconomic status in predicting the distribution of COVID-19 cases and deaths.
Analyses used incidence data on daily COVID + case counts from all counties from the initial wave of infections, merged with data from the U.S. census data to measure county-level SES and confounders. Multivariable analyses relied on survival analyses and Poisson regression to examine timing of county-level index cases and of COVID-19 incidence and mortality in infected counties to examine the spread and severity of COVID-19 while adjusting for adjusted for Black race, Hispanic ethnicity, age, gender, and urbanicity. Effect moderation by social distancing parameters was examined.
Results indicate that higher SES was associated with earlier incidence of index cases, but that as social distancing took place inequalities in SES inverted so that growth in incidence was slower in higher SES counties, where case-fatality rates were lower.
This study is the first to date to show what happens when an opportunistic disease that could affect anyone meets the American system of inequality and is powerfully shaped by it.
量化社会经济地位在预测 COVID-19 病例和死亡分布方面的贡献变化。
分析使用了来自初始感染波的所有县的每日 COVID + 病例计数的发病率数据，与美国人口普查数据合并，以衡量县一级的社会经济地位和混杂因素。多变量分析依赖于生存分析和泊松回归，以检查县一级的指标病例以及受感染县的 COVID-19 发病率和死亡率的出现时间，以研究 COVID-19 的传播和严重程度，同时调整黑人种族、西班牙裔种族、年龄、性别和城市化程度。检验了社会距离参数的调节作用。
结果表明，较高的社会经济地位与指数病例的早期发病有关，但随着社会距离的实施，社会经济地位的不平等程度发生了逆转，因此在较高的社会经济地位县，发病率的增长较慢，病死率也较低。
这项研究是迄今为止首次表明，当一种可能影响任何人的机会性疾病遇到美国的不平等制度并受到其强烈影响时会发生什么。
