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ID 46845
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Author
Fukutome, Ayako
Watashi, Koichi
Kawakami, Norito
Ishikawa, Hirofumi Kaken ID publons researchmap
Abstract
An outbreak of Severe Acute Respiratory Syndrome (SARS) occurred in Hong Kong in late February 2003, resulting in 8,096 cumulative cases with 774 deaths. The outbreak was amplified by nosocomial transmission in many hospitals. Using mathematical modeling, we simulated the number of new incident and prevalent cases of SARS after one infected person was admitted to a hospital (index case). The simulation was tested stochastically using the SEIR model based on previously reported Gamma distributions. We estimated the duration time until 10 beds in negative pressure rooms in Chiyoda-ku, one of the 23 wards in Tokyo, were fully occupied with SARS-infected patients. We determined the impact of an increasing number of days on the number of prevalent cases until the index case was isolated. The prevalent cases increase exponentially along with the increase of the non-isolation period of the index case, and all the beds were fully occupied if the index case was not isolated until more than 6 days. However even 2 days non-isolation period of the index case could fill up all the beds when 16% of secondary infections are transmitted outside the hospital. There is a possibility that an epidemic will occur with the isolation of the index case even at early days if the infection is transmitted outside the hospital. The simulation results revealed that it was important to recognize and isolate SARS patients as early as possible and also to prevent the transmission spreading outside the hospital to control an epidemic.
Keywords
SARS
Nosocomial transmission
Stochastic model
Simulation
Note
編集 : 日本細菌学会、日本ウイルス学会、日本免疫学会
関連情報 : 岡山大学学位論文 学位番号甲第3778号
Published Date
2007
Publication Title
Microbiology and Immunology
Volume
volume51
Issue
issue9
Publisher
財団法人 学会誌刊行センター
Start Page
823
End Page
832
ISSN
0385-5600
NCID
AA00738350
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
File Version
publisher
PubMed ID
DOI
Web of Science KeyUT
Official Url
http://www.jstage.jst.go.jp/browse/mandi/-char/ja/
Related Url
http://ousar.lib.okayama-u.ac.jp/metadata/14875