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Epidemic cycling in a multi-strain SIRS epidemic network model
BACKGROUND: One common observation in infectious diseases caused by multi-strain pathogens is that both the incidence of all infections and the relative fraction of infection with each strain oscillate with time (i.e., so-called Epidemic cycling). Many different mechanisms have been proposed for the...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4836137/ https://www.ncbi.nlm.nih.gov/pubmed/27090782 http://dx.doi.org/10.1186/s12976-016-0040-7 |
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author | Zhang, Xu-Sheng |
author_facet | Zhang, Xu-Sheng |
author_sort | Zhang, Xu-Sheng |
collection | PubMed |
description | BACKGROUND: One common observation in infectious diseases caused by multi-strain pathogens is that both the incidence of all infections and the relative fraction of infection with each strain oscillate with time (i.e., so-called Epidemic cycling). Many different mechanisms have been proposed for the pervasive nature of epidemic cycling. Nevertheless, the two facts that people contact each other through a network rather than following a simple mass-action law and most infectious diseases involve multiple strains have not been considered together for their influence on the epidemic cycling. METHODS: To demonstrate how the structural contacts among people influences the dynamical patterns of multi-strain pathogens, we investigate a two strain epidemic model in a network where every individual randomly contacts with a fixed number of other individuals. The standard pair approximation is applied to describe the changing numbers of individuals in different infection states and contact pairs. RESULTS: We show that spatial correlation due to contact network and interactions between strains through both ecological interference and immune response interact to generate epidemic cycling. Compared to one strain epidemic model, the two strain model presented here can generate epidemic cycling within a much wider parameter range that covers many infectious diseases. CONCLUSION: Our results suggest that co-circulation of multiple strains within a contact network provides an explanation for epidemic cycling. |
format | Online Article Text |
id | pubmed-4836137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-48361372016-04-20 Epidemic cycling in a multi-strain SIRS epidemic network model Zhang, Xu-Sheng Theor Biol Med Model Research BACKGROUND: One common observation in infectious diseases caused by multi-strain pathogens is that both the incidence of all infections and the relative fraction of infection with each strain oscillate with time (i.e., so-called Epidemic cycling). Many different mechanisms have been proposed for the pervasive nature of epidemic cycling. Nevertheless, the two facts that people contact each other through a network rather than following a simple mass-action law and most infectious diseases involve multiple strains have not been considered together for their influence on the epidemic cycling. METHODS: To demonstrate how the structural contacts among people influences the dynamical patterns of multi-strain pathogens, we investigate a two strain epidemic model in a network where every individual randomly contacts with a fixed number of other individuals. The standard pair approximation is applied to describe the changing numbers of individuals in different infection states and contact pairs. RESULTS: We show that spatial correlation due to contact network and interactions between strains through both ecological interference and immune response interact to generate epidemic cycling. Compared to one strain epidemic model, the two strain model presented here can generate epidemic cycling within a much wider parameter range that covers many infectious diseases. CONCLUSION: Our results suggest that co-circulation of multiple strains within a contact network provides an explanation for epidemic cycling. BioMed Central 2016-04-18 /pmc/articles/PMC4836137/ /pubmed/27090782 http://dx.doi.org/10.1186/s12976-016-0040-7 Text en © Zhang. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zhang, Xu-Sheng Epidemic cycling in a multi-strain SIRS epidemic network model |
title | Epidemic cycling in a multi-strain SIRS epidemic network model |
title_full | Epidemic cycling in a multi-strain SIRS epidemic network model |
title_fullStr | Epidemic cycling in a multi-strain SIRS epidemic network model |
title_full_unstemmed | Epidemic cycling in a multi-strain SIRS epidemic network model |
title_short | Epidemic cycling in a multi-strain SIRS epidemic network model |
title_sort | epidemic cycling in a multi-strain sirs epidemic network model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4836137/ https://www.ncbi.nlm.nih.gov/pubmed/27090782 http://dx.doi.org/10.1186/s12976-016-0040-7 |
work_keys_str_mv | AT zhangxusheng epidemiccyclinginamultistrainsirsepidemicnetworkmodel |