Metaheuristic and numerical methods for parameter estimation and spatial analysis in epidemiological and population dynamics models

• Grant number: 22/16196-0
• Support Opportunities: Regular Research Grants
• Start date: October 01, 2024
• End date: September 30, 2026
• Field of knowledge: Interdisciplinary Subjects
• Principal Investigator: Pedro Henrique Triguis Schimit
• Grantee: Pedro Henrique Triguis Schimit
• Host Institution: Universidade Nove de Julho (UNINOVE). Campus Vergueiro. São Paulo , SP, Brazil
• Associated researchers: Fabio Henrique Pereira ; Professor Mark Broom ; Sophie Vanwambeke ; Toshikazu Kuniya

Abstract

Many mathematical models were proposed during the COVID-19 pandemic. However, many of them shared a common challenge: estimating a portion of the model's input parameters. This research project aims to enhance the accuracy of existing epidemiological models by applying metaheuristic and numerical methods for input parameter estimation. Recognizing the limitations of the mathematical models proposed during the COVID-19 pandemic, the goal is to develop calibration techniques for models that examine not only the spread of diseases among humans but also the movement and dispersion of vectors and host animals. As a result, responses to a public health crisis based on simulations can be faster and more accurate. The scope of this study includes diseases transmitted by both mosquitoes and ticks, as well as those spread through direct contact or proximity between individuals. Regarding diseases carried by mosquitoes, there will be a particular emphasis on urban environments, given the significance of the dengue problem in the Brazilian context. Furthermore, the collected data and identified patterns will be shared with the academic community, broadening the reach and potential utility of the project's results. (AU)