Instituto de Tecnologia em Fármacos, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Escola Nacional de Saúde Pública Sergio Arouca, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Cad Saude Publica. 2020;36(5):e00075720. doi: 10.1590/0102-311x00075720. Epub 2020 May 18.
Given the characteristics of the COVID-19 pandemic and the limited tools for orienting interventions in surveillance, control, and clinical care, the current article aims to identify areas with greater vulnerability to severe cases of the disease in Rio de Janeiro, Brazil, a city characterized by huge social and spatial heterogeneity. In order to identify these areas, the authors prepared an index of vulnerability to severe cases of COVID-19 based on the construction, weighting, and integration of three levels of information: mean number of residents per household and density of persons 60 years or older (both per census tract) and neighborhood tuberculosis incidence rate in the year 2018. The data on residents per household and density of persons 60 years or older were obtained from the 2010 Population Census, and data on tuberculosis incidence were taken from the Brazilian Information System for Notificable Diseases (SINAN). Weighting of the indicators comprising the index used analytic hierarchy process (AHP), and the levels of information were integrated via weighted linear combination with map algebra. Spatialization of the index of vulnerability to severe COVID-19 in the city of Rio de Janeiro reveals the existence of more vulnerable areas in different parts of the city's territory, reflecting its urban complexity. The areas with greatest vulnerability are located in the North and West Zones of the city and in poor neighborhoods nested within upper-income parts of the South and West Zones. Understanding these conditions of vulnerability can facilitate the development of strategies to monitor the evolution of COVID-19 and orient measures for prevention and health promotion.
鉴于 COVID-19 大流行的特点以及用于指导监测、控制和临床护理干预的工具有限,本文旨在确定巴西里约热内卢市(一个具有巨大社会和空间异质性的城市)中更容易出现严重疾病病例的脆弱区域。为了确定这些区域,作者基于构建、加权和整合三个层面的信息,编制了一个 COVID-19 严重病例脆弱性指数:每个家庭的居民人数和 60 岁及以上人口密度(均按普查区计算)以及 2018 年邻里结核发病率。家庭居民人数和 60 岁及以上人口密度的数据来自 2010 年人口普查,结核发病率数据来自巴西传染病报告信息系统(SINAN)。构成指数的指标的加权使用了层次分析法(AHP),并通过加权线性组合与地图代数对信息层面进行了整合。里约热内卢市严重 COVID-19 脆弱性指数的空间化揭示了该市不同地区存在更脆弱的区域,反映了其城市的复杂性。脆弱性最大的区域位于城市的北部和西部区域以及南部和西部区域内的贫困社区。了解这些脆弱性条件可以促进制定监测 COVID-19 演变和指导预防和促进健康措施的战略。