Publication: SIS-SEIQR adaptive network model for pandemic influenza
| dc.contributor.author | Wannika Jumpen | en_US |
| dc.contributor.author | Somsak Orankitjaroen | en_US |
| dc.contributor.author | Pichit Boonkrong | en_US |
| dc.contributor.author | Boonmee Wattananon | en_US |
| dc.contributor.author | Benchawan Wiwatanapataphee | en_US |
| dc.contributor.other | Mahidol University | en_US |
| dc.contributor.other | South Carolina Commission on Higher Education | en_US |
| dc.date.accessioned | 2018-05-03T08:08:52Z | |
| dc.date.available | 2018-05-03T08:08:52Z | |
| dc.date.issued | 2011-09-29 | en_US |
| dc.description.abstract | 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. | en_US |
| dc.identifier.citation | Proceedings of the European Computing Conference, ECC '11. (2011), 147-151 | en_US |
| dc.identifier.other | 2-s2.0-79960106726 | en_US |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/11771 | |
| dc.rights | Mahidol University | en_US |
| dc.rights.holder | SCOPUS | en_US |
| dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960106726&origin=inward | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Mathematics | en_US |
| dc.title | SIS-SEIQR adaptive network model for pandemic influenza | en_US |
| dc.type | Conference Paper | en_US |
| dspace.entity.type | Publication | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=79960106726&origin=inward | en_US |