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Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics
A more realistic mathematical influenza model including dynamics of Twitter, which may reduce and increase the spread of influenza, is introduced. The basic reproductive number is derived and the stability of the steady states is proved. The existence of Hopf bifurcation are also demonstrated by ana...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729764/ https://www.ncbi.nlm.nih.gov/pubmed/26848428 http://dx.doi.org/10.1186/s40064-016-1689-4 |
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author | Huo, Hai-Feng Zhang, Xiang-Ming |
author_facet | Huo, Hai-Feng Zhang, Xiang-Ming |
author_sort | Huo, Hai-Feng |
collection | PubMed |
description | A more realistic mathematical influenza model including dynamics of Twitter, which may reduce and increase the spread of influenza, is introduced. The basic reproductive number is derived and the stability of the steady states is proved. The existence of Hopf bifurcation are also demonstrated by analyzing the associated characteristic equation. Furthermore, numerical simulations and sensitivity analysis of relevant parameters are also carried out. Our results show that the impact posed by the negative information of Twitter is not significant than the impact posed by the positive information of Twitter on influenza while the impact posed by the negative information of Twitter on the influenza virus is still extraordinary. |
format | Online Article Text |
id | pubmed-4729764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-47297642016-02-04 Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics Huo, Hai-Feng Zhang, Xiang-Ming Springerplus Research A more realistic mathematical influenza model including dynamics of Twitter, which may reduce and increase the spread of influenza, is introduced. The basic reproductive number is derived and the stability of the steady states is proved. The existence of Hopf bifurcation are also demonstrated by analyzing the associated characteristic equation. Furthermore, numerical simulations and sensitivity analysis of relevant parameters are also carried out. Our results show that the impact posed by the negative information of Twitter is not significant than the impact posed by the positive information of Twitter on influenza while the impact posed by the negative information of Twitter on the influenza virus is still extraordinary. Springer International Publishing 2016-01-27 /pmc/articles/PMC4729764/ /pubmed/26848428 http://dx.doi.org/10.1186/s40064-016-1689-4 Text en © Huo and 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. |
spellingShingle | Research Huo, Hai-Feng Zhang, Xiang-Ming Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title | Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title_full | Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title_fullStr | Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title_full_unstemmed | Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title_short | Modeling the influence of Twitter in reducing and increasing the spread of influenza epidemics |
title_sort | modeling the influence of twitter in reducing and increasing the spread of influenza epidemics |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4729764/ https://www.ncbi.nlm.nih.gov/pubmed/26848428 http://dx.doi.org/10.1186/s40064-016-1689-4 |
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