Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.

Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of pou...

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Autores principales:	Thomas P Van Boeckel, Weerapong Thanapongtharm, Timothy Robinson, Chandrashekhar M Biradar, Xiangming Xiao, Marius Gilbert
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/84f1a01e3a7c4481979160cf859fd85f
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spelling	oai:doaj.org-article:84f1a01e3a7c4481979160cf859fd85f2021-11-18T08:08:18ZImproving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.1932-620310.1371/journal.pone.0049528https://doaj.org/article/84f1a01e3a7c4481979160cf859fd85f2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23185352/?tool=EBIhttps://doaj.org/toc/1932-6203Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention.Thomas P Van BoeckelWeerapong ThanapongtharmTimothy RobinsonChandrashekhar M BiradarXiangming XiaoMarius GilbertPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e49528 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Thomas P Van Boeckel Weerapong Thanapongtharm Timothy Robinson Chandrashekhar M Biradar Xiangming Xiao Marius Gilbert Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
description	Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention.
format	article
author	Thomas P Van Boeckel Weerapong Thanapongtharm Timothy Robinson Chandrashekhar M Biradar Xiangming Xiao Marius Gilbert
author_facet	Thomas P Van Boeckel Weerapong Thanapongtharm Timothy Robinson Chandrashekhar M Biradar Xiangming Xiao Marius Gilbert
author_sort	Thomas P Van Boeckel
title	Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
title_short	Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
title_full	Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
title_fullStr	Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
title_full_unstemmed	Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.
title_sort	improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 thailand epidemic.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/84f1a01e3a7c4481979160cf859fd85f
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Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic.

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