Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is importan...

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Autores principales:	Paritosh K Biswas, Md Zohorul Islam, Nitish C Debnath, Mat Yamage
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/09b59d79ad7342bfb38d882e808dcb10
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spelling	oai:doaj.org-article:09b59d79ad7342bfb38d882e808dcb102021-11-18T08:17:41ZModeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.1932-620310.1371/journal.pone.0098471https://doaj.org/article/09b59d79ad7342bfb38d882e808dcb102014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24886857/?tool=EBIhttps://doaj.org/toc/1932-6203The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.Paritosh K BiswasMd Zohorul IslamNitish C DebnathMat YamagePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 6, p e98471 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Paritosh K Biswas Md Zohorul Islam Nitish C Debnath Mat Yamage Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
description	The highly pathogenic avian influenza A virus subtype H5N1 (HPAI H5N1) is a deadly zoonotic pathogen. Its persistence in poultry in several countries is a potential threat: a mutant or genetically reassorted progenitor might cause a human pandemic. Its world-wide eradication from poultry is important to protect public health. The global trend of outbreaks of influenza attributable to HPAI H5N1 shows a clear seasonality. Meteorological factors might be associated with such trend but have not been studied. For the first time, we analyze the role of meteorological factors in the occurrences of HPAI outbreaks in Bangladesh. We employed autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to assess the roles of different meteorological factors in outbreaks of HPAI. Outbreaks were modeled best when multiplicative seasonality was incorporated. Incorporation of any meteorological variable(s) as inputs did not improve the performance of any multivariable models, but relative humidity (RH) was a significant covariate in several ARIMA and SARIMA models with different autoregressive and moving average orders. The variable cloud cover was also a significant covariate in two SARIMA models, but air temperature along with RH might be a predictor when moving average (MA) order at lag 1 month is considered.
format	article
author	Paritosh K Biswas Md Zohorul Islam Nitish C Debnath Mat Yamage
author_facet	Paritosh K Biswas Md Zohorul Islam Nitish C Debnath Mat Yamage
author_sort	Paritosh K Biswas
title	Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
title_short	Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
title_full	Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
title_fullStr	Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
title_full_unstemmed	Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.
title_sort	modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza h5n1.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/09b59d79ad7342bfb38d882e808dcb10
work_keys_str_mv	AT paritoshkbiswas modelingandrolesofmeteorologicalfactorsinoutbreaksofhighlypathogenicavianinfluenzah5n1 AT mdzohorulislam modelingandrolesofmeteorologicalfactorsinoutbreaksofhighlypathogenicavianinfluenzah5n1 AT nitishcdebnath modelingandrolesofmeteorologicalfactorsinoutbreaksofhighlypathogenicavianinfluenzah5n1 AT matyamage modelingandrolesofmeteorologicalfactorsinoutbreaksofhighlypathogenicavianinfluenzah5n1
_version_	1718421904864313344

Modeling and roles of meteorological factors in outbreaks of highly pathogenic avian influenza H5N1.

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