SEIQR-SIS epidemic network model and its stability

In this paper, we propose an SEIQR-SIS epidemic network model to study pandemic influenza and derive the approximate threshold condition (basis reproductive number) to examine the stability of the model. The numerical simulation of the disease transmission in the adaptive social network with people...

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Main Authors: Jumpen, W., Orankitjaroen, S., Boonkrong, P., Wiwatanapataphee, Benchawan
Format: Journal Article
Published: 2011
Online Access:http://www.naun.org/main/NAUN//mcs/20-818.pdf
http://hdl.handle.net/20.500.11937/17707
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author Jumpen, W.
Orankitjaroen, S.
Boonkrong, P.
Wiwatanapataphee, Benchawan
author_facet Jumpen, W.
Orankitjaroen, S.
Boonkrong, P.
Wiwatanapataphee, Benchawan
author_sort Jumpen, W.
building Curtin Institutional Repository
collection Online Access
description In this paper, we propose an SEIQR-SIS epidemic network model to study pandemic influenza and derive the approximate threshold condition (basis reproductive number) to examine the stability of the model. The numerical simulation of the disease transmission in the adaptive social network with people nodes and hub nodes is presented. The network parameters including visiting probability, hub radius and contact radius are used to investigate their impacts on the disease transmission. Our results show that these network parameters have a significant effect on the disease spread.
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format Journal Article
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T07:22:29Z
publishDate 2011
recordtype eprints
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spelling curtin-20.500.11937-177072017-01-30T12:03:33Z SEIQR-SIS epidemic network model and its stability Jumpen, W. Orankitjaroen, S. Boonkrong, P. Wiwatanapataphee, Benchawan In this paper, we propose an SEIQR-SIS epidemic network model to study pandemic influenza and derive the approximate threshold condition (basis reproductive number) to examine the stability of the model. The numerical simulation of the disease transmission in the adaptive social network with people nodes and hub nodes is presented. The network parameters including visiting probability, hub radius and contact radius are used to investigate their impacts on the disease transmission. Our results show that these network parameters have a significant effect on the disease spread. 2011 Journal Article http://hdl.handle.net/20.500.11937/17707 http://www.naun.org/main/NAUN//mcs/20-818.pdf restricted
spellingShingle Jumpen, W.
Orankitjaroen, S.
Boonkrong, P.
Wiwatanapataphee, Benchawan
SEIQR-SIS epidemic network model and its stability
title SEIQR-SIS epidemic network model and its stability
title_full SEIQR-SIS epidemic network model and its stability
title_fullStr SEIQR-SIS epidemic network model and its stability
title_full_unstemmed SEIQR-SIS epidemic network model and its stability
title_short SEIQR-SIS epidemic network model and its stability
title_sort seiqr-sis epidemic network model and its stability
url http://www.naun.org/main/NAUN//mcs/20-818.pdf
http://hdl.handle.net/20.500.11937/17707