Integrated analysis of socio-spatial data through the use of computational tools to support decision-making to reduce disaster risks and achieve the Sustainable Development Goals

• Grant number: 24/03793-6
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date until: May 01, 2024
• End date until: April 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Norma Felicidade Lopes da Silva Valencio
• Grantee: Renata Ribeiro dos Santos
• Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated research grant: 22/09136-1 - Achieving the Sustainable Development Goals in the context of dealing with disasters (CODeS): computational tools in integrated data analysis, AP.ESCIENCE.R

Abstract

A considerable part of Brazilian municipalities experience the recurrence of emergencies, related to different types of disasters, which weaken them, both the public administration and the citizens, while they are equally oriented to operate transitions in order to materialize the 2030 Agenda of the SDGs. Both acute local disaster crises and trans-scalar crises, which the 2030 Agenda attempts to mitigate, are anchored in structural socio-economic and political processes that remain poorly addressed, ranging from distributive inequalities and mismanagement of public resources to environmental conflicts. In this scenario, an intersectoral consultation guided by an integrated approach of social justice, accountability and sustainability is required to renew the social dynamics and the corresponding local public policies. In scientific terms, the challenge to which this proposal is launched is (a) to carry out an integrated analysis of such dynamics in their main social, economic, political and environmental components, in their intertwining and/or synergies, in order to identify the directions of the transitions at the municipal level as well as (b) the comparative analysis of the evolution of the municipalities among themselves, among the Federative Units, among the five macro-regions and between these and the federal level. Methodologically, this will be exercised through modeling based on complex systems, machine learning and fuzzy logic, based on the use of different public databases - demographic, economic, health, disasters - in a dedicated dialog between CHS and Data Science. , also providing for the formation of new staff for such disciplinary interfaces. Among the questions on which this study focuses, the following stand out: Does the declaration of emergency, due to the occurrence of a disaster, reorient the municipal socioeconomic dynamics? If so, do these circumstances favor or undermine institutional conditions and local socio-economic forces to achieve the SDGs? What have been the driving forces, of a socioeconomic nature, that have driven local society towards greater resilience or vulnerability in the face of disaster risks? Is the type of event mentioned in the municipal emergency decree a determining factor in distinguishing the socioeconomic paths during and after the acute crisis phase? It is expected that the results to be disseminated - through publications with international collaboration, the availability and systematic updating of results through an institutional website and in the realization of a mini-course for municipal public managers and community leaders - will contribute to the orientation of a new policy agenda public, more pertinent to dealing with crises, which sometimes escalate, and in a direction of social change.