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Markov Chain Monte Carlo algorithms for compartimental epidemiological models

Grant number: 21/07725-7
Support type:Scholarships in Brazil - Scientific Initiation
Effective date (Start): October 01, 2021
Effective date (End): September 30, 2022
Field of knowledge:Engineering - Electrical Engineering
Principal researcher:Vitor Heloiz Nascimento
Grantee:Jonathan Pereira Maria
Home Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The COVID-19 pandemic increased significantly the interest in mathematical models for epidemiology. In addition, several difficulties with respect to the identification of model parameters and with respect to the capability of these models to predict possible consequences of different sanitary measures have been highlighted. This work proposes the implementation of deterministic and stochastic epidemiological models, and the use of parameter estimation software based on Markov Chain Monte Carlo (MCMC) and Particle Markov Chain Monte Carlo (PMCMC) using the Julia language and packages such as Stan, Birch and Turing, to estimate model parameters from simulated data, this way providing insights on the identifiability of the different parameters in different situations. (AU)

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