SIS-SEIQR adaptive network model for pandemic influenza

SIS-SEIQR adaptive network model for pandemic influenza

This paper aims to present an SIS-SEIQR network model for pandemic influenza. We propose a network algorithm to generate an adaptive social network with dynamic hub nodes to capture the disease transmission in a human community. Effects of visiting probability on the spread of the disease are invest...

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Main Authors: Wannika Jumpen, Somsak Orankitjaroen, Pichit Boonkrong, Boonmee Wattananon, Benchawan Wiwatanapataphee
Other Authors: Mahidol University
Format: Conference or Workshop Item
Published: 2018
Subjects:
Computer Science
Mathematics
Online Access:https://repository.li.mahidol.ac.th/handle/123456789/11771
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Institution: Mahidol University
id th-mahidol.11771
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spelling th-mahidol.117712018-05-03T15:19:57Z SIS-SEIQR adaptive network model for pandemic influenza Wannika Jumpen Somsak Orankitjaroen Pichit Boonkrong Boonmee Wattananon Benchawan Wiwatanapataphee Mahidol University South Carolina Commission on Higher Education Computer Science Mathematics This paper aims to present an SIS-SEIQR network model for pandemic influenza. We propose a network algorithm to generate an adaptive social network with dynamic hub nodes to capture the disease transmission in a human community. Effects of visiting probability on the spread of the disease are investigated. The results indicate that high visiting probability increases the transmission rate of the disease. 2018-05-03T08:08:52Z 2018-05-03T08:08:52Z 2011-09-29 Conference Paper Proceedings of the European Computing Conference, ECC '11. (2011), 147-151 2-s2.0-79960106726 https://repository.li.mahidol.ac.th/handle/123456789/11771 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960106726&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Computer Science
Mathematics
spellingShingle Computer Science
Mathematics
Wannika Jumpen
Somsak Orankitjaroen
Pichit Boonkrong
Boonmee Wattananon
Benchawan Wiwatanapataphee
SIS-SEIQR adaptive network model for pandemic influenza
description This paper aims to present an SIS-SEIQR network model for pandemic influenza. We propose a network algorithm to generate an adaptive social network with dynamic hub nodes to capture the disease transmission in a human community. Effects of visiting probability on the spread of the disease are investigated. The results indicate that high visiting probability increases the transmission rate of the disease.
author2 Mahidol University
author_facet Mahidol University
Wannika Jumpen
Somsak Orankitjaroen
Pichit Boonkrong
Boonmee Wattananon
Benchawan Wiwatanapataphee
format Conference or Workshop Item
author Wannika Jumpen
Somsak Orankitjaroen
Pichit Boonkrong
Boonmee Wattananon
Benchawan Wiwatanapataphee
author_sort Wannika Jumpen
title SIS-SEIQR adaptive network model for pandemic influenza
title_short SIS-SEIQR adaptive network model for pandemic influenza
title_full SIS-SEIQR adaptive network model for pandemic influenza
title_fullStr SIS-SEIQR adaptive network model for pandemic influenza
title_full_unstemmed SIS-SEIQR adaptive network model for pandemic influenza
title_sort sis-seiqr adaptive network model for pandemic influenza
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/11771
_version_ 1763491735864868864

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