Implementation and validation of an economic module in the Be-FAST model to predict costs generated by livestock disease epidemics: Application to classical swine fever epidemics in Spain
Implementation and validation of an economic module in the Be-FAST model to predict costs generated by livestock disease epidemics: Application to classical swine fever epidemics in Spain
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DOI：
10.1016/j.prevetmed.2016.01.015
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发表时间：
2016-04-01
影响因子：
2.6
通讯作者：
Sanchez-Vizcaino, J. M.
中科院分区：
文献类型：
--
作者：
Fernandez-Carrion, E.;Ivorra, B.;Sanchez-Vizcaino, J. M.
Be-FAST是一个基于时空随机传播数学模型的计算机程序，用于研究家畜传染病在农场内部和农场之间的传播。目前的工作描述了一个集成到Be-FAST中的新模块，用于模拟猪瘟（CSF）和其他传染性牲畜疾病在农场内部和农场之间传播的经济后果。CSF是全球养猪业中最具破坏性的经济疾病之一。特别是在西班牙，最近两次脑脊液流行（1997年和2001年）造成的经济损失合计超过1.08亿欧元。目前的分析表明，严重的脑脊液流行与巨大的经济成本有关，其中约80%与动物扑杀有关。与控制措施相关的直接成本与受感染农场的数量密切相关，而间接成本则与流行病持续时间密切相关。该经济模型已通过西班牙最近一次疫情的经济信息得到验证。这些结果表明，我们的经济模块可能有助于分析和预测牲畜疫病流行的经济后果。(C) 2016 Elsevier B.V.版权所有
Be-FAST is a computer program based on a time-spatial stochastic spread mathematical model for studying the transmission of infectious livestock diseases within and between farms. The present work describes a new module integrated into Be-FAST to model the economic consequences of the spreading of classical swine fever (CSF) and other infectious livestock diseases within and between farms. CSF is financially one of the most damaging diseases in the swine industry worldwide. Specifically in Spain, the economic costs in the two last CSF epidemics (1997 and 2001) reached jointly more than 108 million euros. The present analysis suggests that severe CSF epidemics are associated with significant economic costs, approximately 80% of which are related to animal culling. Direct costs associated with control measures are strongly associated with the number of infected farms, while indirect costs are more strongly associated with epidemic duration. The economic model has been validated with economic information around the last outbreaks in Spain. These results suggest that our economic module may be useful for analysing and predicting economic consequences of livestock disease epidemics. (C) 2016 Elsevier B.V. All rights reserved.