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Invasion reproductive numbers for discrete-time models
Although invasion reproductive numbers (IRNs) are utilized frequently in continuous-time models with multiple interacting pathogens, they are yet to be explored in discrete-time systems. Here, we extend the concept of IRNs to discrete-time models by showing how to calculate them for a set of two-pat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
KeAi Publishing
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468161/ https://www.ncbi.nlm.nih.gov/pubmed/31016273 http://dx.doi.org/10.1016/j.idm.2019.03.002 |
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author | Olawoyin, Omomayowa Kribs, Christopher |
author_facet | Olawoyin, Omomayowa Kribs, Christopher |
author_sort | Olawoyin, Omomayowa |
collection | PubMed |
description | Although invasion reproductive numbers (IRNs) are utilized frequently in continuous-time models with multiple interacting pathogens, they are yet to be explored in discrete-time systems. Here, we extend the concept of IRNs to discrete-time models by showing how to calculate them for a set of two-pathogen SIS models with coinfection. In our exploration, we address how sequencing events impacts the basic reproductive number (BRN) and IRN. As an illustrative example, our models are applied to rhinovirus and respiratory syncytial virus co-circulation. Results show that while the BRN is unaffected by variations in the order of events, the IRN differs. Furthermore, our models predict copersistence of multiple pathogen strains under cross-immunity, which is atypical of analogous continuous-time models. This investigation shows that sequencing events has important consequences for the IRN and can drastically alter competition dynamics. |
format | Online Article Text |
id | pubmed-6468161 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | KeAi Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-64681612019-04-23 Invasion reproductive numbers for discrete-time models Olawoyin, Omomayowa Kribs, Christopher Infect Dis Model Original Research Article Although invasion reproductive numbers (IRNs) are utilized frequently in continuous-time models with multiple interacting pathogens, they are yet to be explored in discrete-time systems. Here, we extend the concept of IRNs to discrete-time models by showing how to calculate them for a set of two-pathogen SIS models with coinfection. In our exploration, we address how sequencing events impacts the basic reproductive number (BRN) and IRN. As an illustrative example, our models are applied to rhinovirus and respiratory syncytial virus co-circulation. Results show that while the BRN is unaffected by variations in the order of events, the IRN differs. Furthermore, our models predict copersistence of multiple pathogen strains under cross-immunity, which is atypical of analogous continuous-time models. This investigation shows that sequencing events has important consequences for the IRN and can drastically alter competition dynamics. KeAi Publishing 2019-04-04 /pmc/articles/PMC6468161/ /pubmed/31016273 http://dx.doi.org/10.1016/j.idm.2019.03.002 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Original Research Article Olawoyin, Omomayowa Kribs, Christopher Invasion reproductive numbers for discrete-time models |
title | Invasion reproductive numbers for discrete-time models |
title_full | Invasion reproductive numbers for discrete-time models |
title_fullStr | Invasion reproductive numbers for discrete-time models |
title_full_unstemmed | Invasion reproductive numbers for discrete-time models |
title_short | Invasion reproductive numbers for discrete-time models |
title_sort | invasion reproductive numbers for discrete-time models |
topic | Original Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468161/ https://www.ncbi.nlm.nih.gov/pubmed/31016273 http://dx.doi.org/10.1016/j.idm.2019.03.002 |
work_keys_str_mv | AT olawoyinomomayowa invasionreproductivenumbersfordiscretetimemodels AT kribschristopher invasionreproductivenumbersfordiscretetimemodels |