Programa de Pós-Graduação em Análise de Sistemas Ambientais, Cesmac, Maceió, Alagoas, Brasil.
Programa de Pós-Graduação em Saúde da Família, Universidade Federal de Alagoas, Maceió, Brasil.
J Infect Dev Ctries. 2022 Aug 30;16(8):1285-1293. doi: 10.3855/jidc.15214.
COVID-19 is a major public health concern in this century. The causative agent SARS-CoV-2, is highly contagious and spreads continuously across territories. Spatial analysis is of enormous importance in the process of understanding the disease and its transmission mechanisms. We aimed to identify the risk areas for COVID-19 and analyze their association with social vulnerability in Maceió, Alagoas. The study was conducted in 2020.
This is an ecological study to evaluate the incidence, mortality and case fatality rate of COVID-19 and their relationship with 12 indicators of human development and social vulnerability. Multivariate and spatial statistics were applied. A 95% confidence interval and a 5% confidence level were considered.
The spatial scan statistic revealed the existence of six high-risk clusters for the incidence of COVID-19. The regression model showed that social indicators, such as literacy of people, residents of private households, households with more than four residents, and resident brown population, were associated with COVID-19 transmission in Maceió-AL. The disease affected localities whose populations are exposed to a context of intense socioeconomic vulnerability.
Based on the results, it is necessary to adopt measures that take into account the social determinants of health in order to minimize the damage caused by the pandemic.
COVID-19 是本世纪的重大公共卫生关注点。其病原体 SARS-CoV-2 具有高度传染性，且在各地持续传播。空间分析在理解疾病及其传播机制的过程中非常重要。我们旨在确定 COVID-19 的风险区域，并分析其与阿拉戈斯州马塞约社会脆弱性的关联。该研究于 2020 年进行。
这是一项评估 COVID-19 的发病率、死亡率和病死率及其与 12 个人类发展和社会脆弱性指标之间关系的生态研究。应用了多变量和空间统计学。考虑了 95%置信区间和 5%置信水平。
空间扫描统计显示存在六个 COVID-19 发病率高风险集群。回归模型表明，社会指标，如人口识字率、私人住户居民、居住人数超过四人的住户以及棕色人种居民，与马塞约-AL 的 COVID-19 传播有关。该疾病影响到那些人口处于强烈社会经济脆弱性背景下的地区。
根据结果，有必要采取考虑健康社会决定因素的措施，以最大限度地减少大流行造成的损害。
