Efficient simulation of the spatial transmission dynamics of influenza.

Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns...

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Autores principales:	Meng-Tsung Tsai, Tsurng-Chen Chern, Jen-Hsiang Chuang, Chih-Wen Hsueh, Hsu-Sung Kuo, Churn-Jung Liau, Steven Riley, Bing-Jie Shen, Chih-Hao Shen, Da-Wei Wang, Tsan-Sheng Hsu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/3ebd70d7c99d4b20a8777e6606e72fba
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spelling	oai:doaj.org-article:3ebd70d7c99d4b20a8777e6606e72fba2021-11-18T07:02:28ZEfficient simulation of the spatial transmission dynamics of influenza.1932-620310.1371/journal.pone.0013292https://doaj.org/article/3ebd70d7c99d4b20a8777e6606e72fba2010-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21079810/?tool=EBIhttps://doaj.org/toc/1932-6203Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual-based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs.Meng-Tsung TsaiTsurng-Chen ChernJen-Hsiang ChuangChih-Wen HsuehHsu-Sung KuoChurn-Jung LiauSteven RileyBing-Jie ShenChih-Hao ShenDa-Wei WangTsan-Sheng HsuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 11, p e13292 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Meng-Tsung Tsai Tsurng-Chen Chern Jen-Hsiang Chuang Chih-Wen Hsueh Hsu-Sung Kuo Churn-Jung Liau Steven Riley Bing-Jie Shen Chih-Hao Shen Da-Wei Wang Tsan-Sheng Hsu Efficient simulation of the spatial transmission dynamics of influenza.
description	Early data from the 2009 H1N1 pandemic (H1N1pdm) suggest that previous studies over-estimated the within-country rate of spatial spread of pandemic influenza. As large spatially resolved data sets are constructed, the need for efficient simulation code with which to investigate the spatial patterns of the pandemic becomes clear. Here, we present a significant improvement to the efficiency of an individual-based stochastic disease simulation framework commonly used in multiple previous studies. We quantify the efficiency of the revised algorithm and present an alternative parameterization of the model in terms of the basic reproductive number. We apply the model to the population of Taiwan and demonstrate how the location of the initial seed can influence spatial incidence profiles and the overall spread of the epidemic. Differences in incidence are driven by the relative connectivity of alternate seed locations. The ability to perform efficient simulation allows us to run a batch of simulations and take account of their average in real time. The averaged data are stable and can be used to differentiate spreading patterns that are not readily seen by only conducting a few runs.
format	article
author	Meng-Tsung Tsai Tsurng-Chen Chern Jen-Hsiang Chuang Chih-Wen Hsueh Hsu-Sung Kuo Churn-Jung Liau Steven Riley Bing-Jie Shen Chih-Hao Shen Da-Wei Wang Tsan-Sheng Hsu
author_facet	Meng-Tsung Tsai Tsurng-Chen Chern Jen-Hsiang Chuang Chih-Wen Hsueh Hsu-Sung Kuo Churn-Jung Liau Steven Riley Bing-Jie Shen Chih-Hao Shen Da-Wei Wang Tsan-Sheng Hsu
author_sort	Meng-Tsung Tsai
title	Efficient simulation of the spatial transmission dynamics of influenza.
title_short	Efficient simulation of the spatial transmission dynamics of influenza.
title_full	Efficient simulation of the spatial transmission dynamics of influenza.
title_fullStr	Efficient simulation of the spatial transmission dynamics of influenza.
title_full_unstemmed	Efficient simulation of the spatial transmission dynamics of influenza.
title_sort	efficient simulation of the spatial transmission dynamics of influenza.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/3ebd70d7c99d4b20a8777e6606e72fba
work_keys_str_mv	AT mengtsungtsai efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT tsurngchenchern efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT jenhsiangchuang efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT chihwenhsueh efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT hsusungkuo efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT churnjungliau efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT stevenriley efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT bingjieshen efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT chihhaoshen efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT daweiwang efficientsimulationofthespatialtransmissiondynamicsofinfluenza AT tsanshenghsu efficientsimulationofthespatialtransmissiondynamicsofinfluenza
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Efficient simulation of the spatial transmission dynamics of influenza.

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