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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Bibliographic Details
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
Description
Summary: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.

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