Meteorological Factors and Swine Erysipelas Transmission in Southern China

Swine erysipelas (SE) is one of the best-known and most serious diseases that affect domestic pigs, which is caused by Erysipelothrix rhusiopathiae. It is endemic in Nanning and has been circulating for decades, causing considerable economic losses. The aim of this study was to investigate the effec...

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Autores principales:	Hong-Yu Qin, Xiu Xin, Wanli Sha, Ben Wang, Xiansheng Hu, Lianjun Fu, Baishuang Yin
Formato:	article
Lenguaje:	EN
Publicado:	Sciendo 2020
Materias:	swine swine erysipelas nanning meteorological factors zero-inflated negative binomial Veterinary medicine SF600-1100
Acceso en línea:	https://doaj.org/article/ec2ea4de1ba74fad9f58543450c819a7
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spelling	oai:doaj.org-article:ec2ea4de1ba74fad9f58543450c819a72021-11-17T21:27:53ZMeteorological Factors and Swine Erysipelas Transmission in Southern China1820-744810.2478/acve-2020-0002https://doaj.org/article/ec2ea4de1ba74fad9f58543450c819a72020-03-01T00:00:00Zhttps://doi.org/10.2478/acve-2020-0002https://doaj.org/toc/1820-7448Swine erysipelas (SE) is one of the best-known and most serious diseases that affect domestic pigs, which is caused by Erysipelothrix rhusiopathiae. It is endemic in Nanning and has been circulating for decades, causing considerable economic losses. The aim of this study was to investigate the effect of meteorological-related variations on the epidemiology of swine erysipelas in Nanning City, a subtropical city of China. Data on monthly counts of reported swine erysipelas and climate data in Nanning are provided by the authorities over the period from 2006 to 2015. Cross-correlation analysis was applied to identify the lag effects of meteorological variables. A zero-inflated negative binomial (ZINB) regression model was used to evaluate the independent contribution of meteorological factors to SE transmission. After controlling seasonality, autocorrelation and lag effects, the results of the model indicated that Southern Oscillation Index (SOI) has a positive effect on SE transmission. Moreover, there is a positive correlation between monthly mean maximum temperature and relative humidity at 0-1 month lag and the number of cases. Furthermore, there is a positive association between the number of SE incidences and precipitation, with a lagged effect of 2 months. In contrast, monthly mean wind velocity negatively correlated with SE of the current month. These findings indicate that meteorological variables may play a significant role in SE transmission in southern China. Finally, more public health actions should be taken to prevent and control the increase of SE disease with consideration of local weather variations.Hong-Yu QinXiu XinWanli ShaBen WangXiansheng HuLianjun FuBaishuang YinSciendoarticleswineswine erysipelasnanningmeteorological factorszero-inflated negative binomialVeterinary medicineSF600-1100ENActa Veterinaria, Vol 70, Iss 1, Pp 37-50 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	swine swine erysipelas nanning meteorological factors zero-inflated negative binomial Veterinary medicine SF600-1100
spellingShingle	swine swine erysipelas nanning meteorological factors zero-inflated negative binomial Veterinary medicine SF600-1100 Hong-Yu Qin Xiu Xin Wanli Sha Ben Wang Xiansheng Hu Lianjun Fu Baishuang Yin Meteorological Factors and Swine Erysipelas Transmission in Southern China
description	Swine erysipelas (SE) is one of the best-known and most serious diseases that affect domestic pigs, which is caused by Erysipelothrix rhusiopathiae. It is endemic in Nanning and has been circulating for decades, causing considerable economic losses. The aim of this study was to investigate the effect of meteorological-related variations on the epidemiology of swine erysipelas in Nanning City, a subtropical city of China. Data on monthly counts of reported swine erysipelas and climate data in Nanning are provided by the authorities over the period from 2006 to 2015. Cross-correlation analysis was applied to identify the lag effects of meteorological variables. A zero-inflated negative binomial (ZINB) regression model was used to evaluate the independent contribution of meteorological factors to SE transmission. After controlling seasonality, autocorrelation and lag effects, the results of the model indicated that Southern Oscillation Index (SOI) has a positive effect on SE transmission. Moreover, there is a positive correlation between monthly mean maximum temperature and relative humidity at 0-1 month lag and the number of cases. Furthermore, there is a positive association between the number of SE incidences and precipitation, with a lagged effect of 2 months. In contrast, monthly mean wind velocity negatively correlated with SE of the current month. These findings indicate that meteorological variables may play a significant role in SE transmission in southern China. Finally, more public health actions should be taken to prevent and control the increase of SE disease with consideration of local weather variations.
format	article
author	Hong-Yu Qin Xiu Xin Wanli Sha Ben Wang Xiansheng Hu Lianjun Fu Baishuang Yin
author_facet	Hong-Yu Qin Xiu Xin Wanli Sha Ben Wang Xiansheng Hu Lianjun Fu Baishuang Yin
author_sort	Hong-Yu Qin
title	Meteorological Factors and Swine Erysipelas Transmission in Southern China
title_short	Meteorological Factors and Swine Erysipelas Transmission in Southern China
title_full	Meteorological Factors and Swine Erysipelas Transmission in Southern China
title_fullStr	Meteorological Factors and Swine Erysipelas Transmission in Southern China
title_full_unstemmed	Meteorological Factors and Swine Erysipelas Transmission in Southern China
title_sort	meteorological factors and swine erysipelas transmission in southern china
publisher	Sciendo
publishDate	2020
url	https://doaj.org/article/ec2ea4de1ba74fad9f58543450c819a7
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Meteorological Factors and Swine Erysipelas Transmission in Southern China

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