A pandemia de COVID-19 e associação com a vulnerabilidade social no território brasileiro

• Ano de defesa: 2023
• Autor(a) principal: Filho, João Batista Cavalcante
• Orientador(a): Nunes, Marco Antônio Prado
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Ciências da Saúde
• Palavras-chave em Português: COVID-19; Mortalidade; Vulnerabilidade social; Epidemiologia; Análise espacial
• Palavras-chave em Inglês: Coronavirus infections; Mortality; Social vulnerability; Epidemiology; Spatial analysis
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/23366

Introduction. The World Health Organization (WHO) characterized COVID-19 as a pandemic on March 11, 2020 and on May 5, 2023 declared the end of the Public Health Emergency of International Concern. Approximately 768 million cases of COVID-19 and 6.95 million deaths from the disease were confirmed worldwide by July 5, 2023. Recognized, social vulnerabilities impact the health of people and communities and social inequalities related to access to housing, employment, education, health care continue to play a role in mortality and disease burden, especially in regions with significant economic disparities. Objective. To analyze the association of demographic, socioeconomic and health indicators with mortality from COVID- 19 in the Brazilian territory. Methods. Three observational studies were carried out using different methodological approaches, considering the first two years of the pandemic. The first study correlated the incidence and mortality rates for COVID-19 that occurred in the state of Sergipe, with indicators of human development and social vulnerability through Spearman's correlation. These indices were also associated with the rate of RT PCR exams per municipality. The second study analyzed the spatial distribution of mortality from COVID 19 and its association with socioeconomic and health indicators in the northeast region of Brazil, using the Global Moran Index, global spatial autocorrelation (LISA), multiple linear regression, and autoregressive spatial models. The third study analyzed the relationship between mortality from the disease and demographic indicators, the incidence of the disease and social determinants of health in all Brazilian municipalities, using multiple logistic regression with insertion of variables according to the theoretical model built for this purpose. Results. The statistical analysis of the association between the social vulnerability and human development indices and the incidence and mortality rates for COVID-19 in the state of Sergipe showed that, in the first year of the pandemic, the less vulnerable municipalities and those with greater human development had more cases. and more deaths from the disease. The mortality coefficient in northeastern Brazil, one of the regions with the worst social indicators, had a negative and significant correlation of inequality indicators and a positive correlation with socioeconomic and health indicators, when a model with Spearman's correlation coefficient was used and when A spatial analysis model with high explanatory power was used. The scenario of mortality in the COVID-19 pandemic in relation to demographic, socioeconomic and health indicators in Brazil had considerable differences between the years 2020 and 2021. Conclusion. Socioeconomic vulnerabilities have a well-established role in the spread and severity of COVID-19. However, factors such as age structure, demographic density, economic indicators and political polarization complicate the pandemic scenario in Brazil. Larger and more populous municipalities, with great economic activity and where managers implemented insufficient measures to reduce inequalities and combat the pandemic, suffered more intensely from the effects of the disease. No single narrative could justify the distribution of mortality in the Brazilian territory, which has continental dimensions and great demographic and socioeconomic disparities. The distribution of mortality from COVID 19 was very uneven, with many factors influencing the coefficient.