ESTIMA-Favelas: Multidimensional Estimates of Housing Needs in Favelas

• Grant number: 25/07390-6
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: August 01, 2025
• End date: July 31, 2027
• Field of knowledge: Applied Social Sciences - Urban and Regional Planning - Methods and Techniques of Urban and Regional Planning
• Principal Investigator: Rosana Denaldi
• Grantee: Twane Maria Cordeiro Xavier
• Host Institution: Centro de Engenharia, Modelagem e Ciências Sociais Aplicadas (CECS). Universidade Federal do ABC (UFABC). Ministério da Educação (Brasil). Santo André , SP, Brazil
• Associated research grant: 22/12259-8 - Center for Favela Studies (CEFAVELA)., AP.CEPID

Abstract

The lack of access to adequate housing affects a significant portion of the Brazilian population and represents a central theme in the debate on sustainability, inequality and poverty. Understanding and monitoring the magnitude and characteristics of housing needs (HN) in its multiple dimensions, at the appropriate spatial and temporal scales, is essential for the formulation of public policies aimed at guaranteeing the right to housing and the city. Therefore, it is necessary to advance in the construction of representations of HN that overcome conceptual and empirical limitations imposed by indicators traditionally used in the country, which include the absence or difficulty of representing some dimensions of HN, low updating frequency and inappropriate spatial scale. Added to this is the need to improve the strategies for analyzing and communicating these indicators so that they are effective in supporting housing planning in different contexts and governmental spheres.The ESTIMA-Favelas project proposes to develop a new analytical framework for HN, which includes methodologies and tools for estimating and analyzing the housing deficit and inadequacy on a local scale, allows frequent monitoring, and introduces new perspectives for a multidimensional and integrated analysis of the phenomenon. This process will involve: (a) integration of alternative data, including administrative records (CadÚnico); (b) use of machine learning and spatial regression techniques to identify patterns of housing inadequacy, its manifestation in the territory and relationship with family characteristics; and (c) the development of a "housing needs dashboard", a web portal to present the research results in a flexible and interactive way. The project will include the participation of stakeholders form the field of housing in the process of designing and evaluating the analytical framework. The Greater ABC Region (State of São Paulo) will be the pilot area of the research. (AU)