Instituto Nacional de Infectologia Evandro Chagas, Fiocruz, Rio de Janeiro, RJ, Brazil.
PLoS One. 2022 Apr 28;17(4):e0266109. doi: 10.1371/journal.pone.0266109. eCollection 2022.
The COVID-19 pandemic in Brazil has been showing a pattern of distribution of related deaths associated with individual socioeconomic status (SES). However, little is known about the role of SES in the distribution of the mortality rate in different population, from an ecological perspective.
The objective of this study was to evaluate the role of socioeconomic factors in the distribution of the COVID-19-related mortality rate among Brazilian municipalities in 2020.
We conducted a retrospective, cross-sectional, observational, population-wide, and ecological study, using data of COVID-19-related deaths from the Influenza Epidemiological Surveillance Information System database (SIVEP-Gripe) and SES from the Social Vulnerability Index (SVI), the Human Development Index (HDI), the Geographic Index of the Socioeconomic Context and Social Studies (GeoSES), and 2010 Demographic Census (IBGE/Brazil). We computed crude, age- and sex-standardized, and the latter offset by the time of exposure to the epidemic mortality rates. To determine socioeconomic factors associated with mortality rates we used log-linear models with state codes as a random effect and Haversine variance-covariance matrix.
191,528 deaths were related to COVID-19 and distributed in 4,928 (88.55%) Brazilian municipalities. Whatever the socioeconomic indexes used, the R2 were very small to explain SMRT. Consistent across all socioeconomic indexes used, high-income, more educated, and well infrastructure municipalities generally had higher mortality rates.
Excluding the effect of demographic structure and pandemic timing from mortality rates, the contribution of SES to explain differences in COVID-19-related mortality rates among municipalities in Brazil became very low. The impact of SES on COVID-19-related mortality may vary across levels of aggregation. Urban infrastructure, which includes mobility structures, more complex economic activities and connections, may have influenced the average municipal death rate.
巴西的 COVID-19 大流行呈现出与个体社会经济地位（SES）相关的死亡分布模式。然而，从生态角度来看，关于 SES 在不同人群死亡率分布中的作用知之甚少。
本研究旨在评估 2020 年巴西各城市 SES 因素在 COVID-19 相关死亡率分布中的作用。
我们进行了回顾性、横断面、观察性、全人群和生态研究，使用来自流感流行病学监测信息系统数据库（SIVEP-Gripe）的 COVID-19 相关死亡数据和 SES 数据，包括社会脆弱性指数（SVI）、人类发展指数（HDI）、社会经济背景和社会研究地理指数（GeoSES）以及 2010 年人口普查（IBGE/巴西）。我们计算了粗死亡率、年龄和性别标准化死亡率，以及通过暴露于疫情的时间对死亡率进行了校正。为了确定与死亡率相关的 SES 因素，我们使用带有州代码作为随机效应的对数线性模型和 Haversine 方差协方差矩阵。
共发生了 191528 例与 COVID-19 相关的死亡事件，分布在 4928 个（88.55%）巴西城市中。无论使用何种 SES 指标，解释 SMRT 的 R2 都非常小。在使用的所有 SES 指标中，高收入、受教育程度更高和基础设施完善的城市的死亡率普遍较高。
从死亡率中排除人口结构和大流行时间的影响后，SES 对解释巴西各城市 COVID-19 相关死亡率差异的贡献变得非常低。SES 对 COVID-19 相关死亡率的影响可能因聚合水平而异。城市基础设施包括移动结构、更复杂的经济活动和联系，可能会影响平均市级死亡率。
