A pobreza multidimensional nos municípios do estado de São Paulo: distribuição espacial e relação com a pandemia de covid-19

• Autor(a) principal: Gottardi, Lorenzo
• Data de Publicação: 2023
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da Uninove
• Texto Completo: http://bibliotecatede.uninove.br/handle/tede/3169
• topic: análise espacial; cidades inteligentes; covid-19; objetivos de desenvolvimento sustentável; pobreza multidimensional; spatial analysis; smart cities; covid-19; sustainable development goals; multidimensional poverty; CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO

Introduction: The first of the United Nations' Sustainable Development Goals is the eradication of poverty in all its forms, everywhere. The conception of poverty as a multidimensional phenomenon is central to understanding the deprivations that individuals suffer and how they limit the development of their capabilities. In January 2020, the World Health Organization declared COVID-19 a pandemic, which, throughout 2020 and 2021, affected all municipalities in the state of São Paulo. According to the World Bank, the pandemic may have increased poverty worldwide by around 15%. Objective: To construct a multidimensional poverty indicator for municipalities in the state of São Paulo and to identify the relationship between multidimensional poverty and COVID-19 hospitalization and mortality indicators. Method: This is a descriptive and ecological study with an analytical component that aimed to construct a multidimensional poverty index (MPI) according to the Alkire-Foster method (2009). Data on COVID-19 hospitalizations and deaths in municipalities in the state of São Paulo in 2020 and 2021 were also collected. Finally, spatial analysis techniques, such as global and local Moran's indexes, were used to verify the association between COVID-19 indicators and the multidimensional poverty index. Results: The MPI was composed of 5 dimensions and 14 indicators, and 356 (55.19%) municipalities were considered multidimensionally poor for presenting a total of deprivations above the poverty line, defined at 0.2. A weak negative association was observed between the MPI and COVID-19 hospitalization and mortality rates in 2020 and 2021. Bivariate spatial correlation analysis showed a change in pattern between 2020 and 2021, highlighting a shift in the concentration of hospitalization and mortality rates towards municipalities in the interior of the state of São Paulo, particularly the formation of clusters of municipalities with high multidimensional poverty and high mortality rates in 2021, especially in the DRS of Registro and Sorocaba. Conclusion: The spatial characterization of the MPI and COVID-19 indicators, as well as the study of the relationship between these phenomena, can guide preventive and curative actions, as well as stimulate new studies in the area.