Postgraduate program in Clinical Nursing Care and Health, Universidade Estadual do Ceará, Fortaleza, Ceará, Brasil.
Postgraduate program in Nursing, Faculdade Metropolitana de Ciências e Tecnologia, Parnamirim, Rio Grande do Norte, Brasil.
Epidemiol Infect. 2021 Feb 25;149:e60. doi: 10.1017/S0950268821000479.
The objective of this study was to analyse the dynamics of spatial dispersion of the coronavirus disease 2019 (COVID-19) in Brazil by correlating them to socioeconomic indicators. This is an ecological study of COVID-19 cases and deaths between 26 February and 31 July 2020. All Brazilian counties were used as units of analysis. The incidence, mortality, Bayesian incidence and mortality rates, global and local Moran indices were calculated. A geographic weighted regression analysis was conducted to assess the relationship between incidence and mortality due to COVID-19 and socioeconomic indicators (independent variables). There were confirmed 2 662 485 cases of COVID-19 reported in Brazil from February to July 2020 with higher rates of incidence in the north and northeast. The Moran global index of incidence rate (0.50, P = 0.01) and mortality (0.45 with P = 0.01) indicate a positive spatial autocorrelation with high standards in the north, northeast and in the largest urban centres between cities in the southeast region. In the same period, there were 92 475 deaths from COVID-19, with higher mortality rates in the northern states of Brazil, mainly Amazonas, Pará and Amapá. The results show that there is a geospatial correlation of COVID-19 in large urban centres and regions with the lowest human development index in the country. In the geographic weighted regression, it was possible to identify that the percentage of people living in residences with density higher than 2 per dormitory, the municipality human development index (MHDI) and the social vulnerability index were the indicators that most contributed to explaining incidence, social development index and the municipality human development index contributed the most to the mortality model. We hope that the findings will contribute to reorienting public health responses to combat COVID-19 in Brazil, the new epicentre of the disease in South America, as well as in other countries that have similar epidemiological and health characteristics to those in Brazil.
本研究旨在通过将新冠肺炎(COVID-19)的空间分布动态与社会经济指标相关联,分析其在巴西的变化情况。这是一项关于 2020 年 2 月 26 日至 7 月 31 日期间 COVID-19 病例和死亡的生态研究。分析单位为巴西的所有县。计算了发病率、死亡率、贝叶斯发病率和死亡率、全局和局部 Moran 指数。进行了地理加权回归分析,以评估 COVID-19 发病率和死亡率与社会经济指标(自变量)之间的关系。2020 年 2 月至 7 月,巴西共报告了 2662485 例 COVID-19 确诊病例,北部和东北部的发病率较高。发病率的全局 Moran 指数(0.50,P = 0.01)和死亡率(0.45,P = 0.01)表明存在正空间自相关,北部、东北部和东南部城市之间的最大城市中心的标准较高。同期,COVID-19 死亡 92475 例,巴西北部各州死亡率较高,主要为亚马孙州、帕拉州和阿马帕州。结果表明,在该国人口发展指数最低的大型城市中心和地区,COVID-19 存在地理空间相关性。在地理加权回归中,能够确定每间宿舍居住密度超过 2 人的居民比例、城市人类发展指数(MHD)和社会脆弱性指数是解释发病率的主要指标,社会发展指数和城市人类发展指数对死亡率模型的贡献最大。我们希望这些发现将有助于重新调整巴西和南美洲新的疾病中心 COVID-19 的公共卫生应对措施,以及那些具有与巴西类似的流行病学和卫生特征的其他国家。