Ligia BARROZO, Departamento de Geografia, FFLCH, Universidade de São Paulo, Brazil
Mirela SERAFIM, Departamento de Geografia, FFLCH, Universidade de São Paulo, Brazil
Lucas Antonio GOMES, Secretaria de Desenvolvimento Social do Estado de São Paulo (SEDS-SP), Brazil
Gabriela UHRIGSHARDT, Hospital Israelita Albert Einstein—Big Data Analytics, Brazil
Nathália MARTINS, Secretaria de Desenvolvimento Social do Estado de São Paulo (SEDS-SP), Brazil
Thalita OLIVEIRA, Secretaria de Desenvolvimento Social do Estado de São Paulo (SEDS-SP), Brazil
João Francisco RESENDE, Secretaria de Desenvolvimento Social do Estado de São Paulo (SEDS-SP), Brazil
Edson AMARO JUNIOR, Hospital Israelita Albert Einstein—Big Data Analytics, Brazil
Poverty and health are tightly related in Brazil (Barrozo, 2018; Barrozo et al., 2020). We will not be able to advance in reducing health inequality if we cannot reduce the poverty of the most vulnerable. São Paulo is the most developed State of Brazil, but poverty remains an unresolved problem. In view of this challenge, a methodology is proposed that allows to classify poor families to be benefited by income transfer programs. We started from a population segment considered the target audience for social programs (people registered in the Unified Registry for Social Programs of the Federal Government – CadUnico) and we intended to move forward by integrating the local aggravations near the family's residence, the context of the intensity of municipal poverty and the opportunities offered by the municipality with a view to the outcome of macroeconomic and political issues. The methodology is data-driven and involves the reduction of variables through successive Principal Component Analysis (PCA). We found that poverty pockets concentrate in the Southeastern State, partially coincident with the municipalities that offer more opportunities for upward social mobility. The combination of the situations pointed to the worst municipal contexts located mainly in the south and speckled over the State. The simulation of two programs to benefit 10,000 and 100,000 families based on the proposed Multiscale Approach (MSA) and on the current used multidimensional poverty tool (the MPI-S) showed that MSA tends to concentrate the assistance with greater percentages of families by municipality. The proposed methodology is an alternative to target the poorest people in addition to family conditions and monetary poverty.
Mots clés : cash transfer program|multidimensional poverty|poverty hotspots|regional policies
A105173LB