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On Deterministic and Stochastic Multiple Pathogen Epidemic Models
In this paper, we consider a stochastic epidemic model with two pathogens. In order to analyze the coexistence of two pathogens, we compute numerically the expectation time until extinction (the mean persistence time), which satisfies a stationary partial differential equation with degenerate variab...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620904/ https://www.ncbi.nlm.nih.gov/pubmed/36417229 http://dx.doi.org/10.3390/epidemiologia2030025 |
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author | Vadillo, Fernando |
author_facet | Vadillo, Fernando |
author_sort | Vadillo, Fernando |
collection | PubMed |
description | In this paper, we consider a stochastic epidemic model with two pathogens. In order to analyze the coexistence of two pathogens, we compute numerically the expectation time until extinction (the mean persistence time), which satisfies a stationary partial differential equation with degenerate variable coefficients, related to backward Kolmogorov equation. I use the finite element method in order to solve this equation, and we implement it in FreeFem++. The main conclusion of this paper is that the deterministic and stochastic epidemic models differ considerably in predicting coexistence of the two diseases and in the extinction outcome of one of them. Now, the main challenge would be to find an explanation for this result. |
format | Online Article Text |
id | pubmed-9620904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96209042022-11-18 On Deterministic and Stochastic Multiple Pathogen Epidemic Models Vadillo, Fernando Epidemiologia (Basel) Article In this paper, we consider a stochastic epidemic model with two pathogens. In order to analyze the coexistence of two pathogens, we compute numerically the expectation time until extinction (the mean persistence time), which satisfies a stationary partial differential equation with degenerate variable coefficients, related to backward Kolmogorov equation. I use the finite element method in order to solve this equation, and we implement it in FreeFem++. The main conclusion of this paper is that the deterministic and stochastic epidemic models differ considerably in predicting coexistence of the two diseases and in the extinction outcome of one of them. Now, the main challenge would be to find an explanation for this result. MDPI 2021-08-12 /pmc/articles/PMC9620904/ /pubmed/36417229 http://dx.doi.org/10.3390/epidemiologia2030025 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Vadillo, Fernando On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title | On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title_full | On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title_fullStr | On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title_full_unstemmed | On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title_short | On Deterministic and Stochastic Multiple Pathogen Epidemic Models |
title_sort | on deterministic and stochastic multiple pathogen epidemic models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620904/ https://www.ncbi.nlm.nih.gov/pubmed/36417229 http://dx.doi.org/10.3390/epidemiologia2030025 |
work_keys_str_mv | AT vadillofernando ondeterministicandstochasticmultiplepathogenepidemicmodels |