Urban Rodrigo Custodio, Nakada Liane Yuri Kondo
Environ Urban. 2021 Apr;33(1):229-238. doi: 10.1177/0956247820963962.
Seeking to understand the socio-spatial behaviour of the COVID-19 virus in the most impacted area in Brazil, five spatial regression models were analysed to assess the disease distribution in the affected territory. Results obtained using the Spearman correlation test provided evidence for the correlation between COVID-19 death incidence and social aspects such as population density, average people per household, and informal urban settlements. More importantly, all analysed models using four selected explanatory variables have proven to represent at least 85 per cent of reported deaths at the district level. Overall, our results have demonstrated that the geographically weighted regression (GWR) model best explains the spatial distribution of COVID-19 in the city of São Paulo, highlighting the spatial aspects of the data. Spatial analysis has shown the spread of COVID-19 in areas with highly vulnerable populations. Our findings corroborate reports from the recent literature, pointing out the need for special attention in peripheral areas and informal settlements.
为了解新冠病毒在巴西受影响最严重地区的社会空间行为,分析了五个空间回归模型,以评估该疾病在受影响地区的分布情况。使用斯皮尔曼相关性检验获得的结果为新冠死亡发病率与社会因素(如人口密度、每户平均人数和城市非正式住区)之间的相关性提供了证据。更重要的是,所有使用四个选定解释变量的分析模型已证明,在地区层面上能够解释至少85%的报告死亡病例。总体而言,我们的结果表明,地理加权回归(GWR)模型最能解释圣保罗市新冠病毒的空间分布,突出了数据的空间特征。空间分析显示了新冠病毒在弱势群体高度集中地区的传播情况。我们的研究结果证实了近期文献中的报道,指出在外围地区和非正式住区需要给予特别关注。