Parameter Identification Problem in the discrete-time SIR Model
We investigate the problem of determining time dependent parameters for discrete-time epidemiological compartmental models such as the Susceptible-Infected-Recovered (SIR). We show how to determine parameters based on minimal error type iterative schemes. Such methods involve the computation of the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sociedade Brasileira de Matemática Aplicada e Computacional
2024-11-01
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| Series: | Trends in Computational and Applied Mathematics |
| Subjects: | |
| Online Access: | https://tema.sbmac.org.br/tema/article/view/1805 |
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| Summary: | We investigate the problem of determining time dependent parameters for discrete-time epidemiological compartmental models such as the Susceptible-Infected-Recovered (SIR). We show how to determine parameters based on minimal error type iterative schemes. Such methods involve the computation of the adjoint of the derivative operator of a nonlinear function. This is a nontrivial task that we accomplish by carefully crafting auxiliary problems. To show the efficiency of the method, we consider examples involving real COVID-19 data.
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| ISSN: | 2676-0029 |