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The complexity of Brazilian food systems and the global syndemic: simulations and proposals for action

Grant number: 22/03091-6
Support Opportunities:Research Grants - Initial Project Research Grant
Duration: February 01, 2023 - January 31, 2028
Field of knowledge:Health Sciences - Collective Health - Public Health
Principal Investigator:Aline Martins de Carvalho
Grantee:Aline Martins de Carvalho
Host Institution: Faculdade de Saúde Pública (FSP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated researchers:Alexandre Cláudio Botazzo Delbem ; Ana Luiza Gomes Domingos ; Andrew D Jones ; Antonio Mauro Saraiva ; Dirce Maria Lobo Marchioni ; Eliseu Verly Junior ; Evandro Marcos Saidel Ribeiro ; Flávia Mori Sarti ; Olivier Jolliet

Abstract

Food systems can be defined as the set of elements and activities related to the production, processing, distribution, preparation, and food consumption; being considered the main drivers of the global syndemic of malnutrition, obesity, and climate change. Because they are very complex, with many agents and interactions, little is known about the dynamics of food systems and their impacts on health and the environment, especially in the Global South. Thus, the objective of the present project is to map and model the Brazilian food system, identifying the main actors, their relationships and interactions that impact the global syndemic in different Brazilian regions using innovative methodologies capable of dealing with the complexity of food systems and simulating different scenarios of intervention. The Brazilian food system will be represented by an agent-based model, where the components influence the system through their decisions and interrelationships. The conceptual model will be developed from a synthetic representation of the components of the Brazilian food system, including a set of static structure diagrams, derived from an integrative literature review. Then, specific mathematical models will be implemented to represent the behaviors and rules of interactions between agents and their effects on the environment, including linear and non-linear models, methods for generating social networks, dynamic Bayesian networks, multi-criteria causal models, among others. Finally, the model will be subjected to calibration and validation of parameters based on real data from the Brazilian regions for the creation of an interactive platform capable of simulating possible changes in the food system through interventions at different levels (individual, institutional and political) and its impacts on the syndemic. (AU)

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