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Implementation and validation of an economic module for the epidemiological model Be-FAST to predict the costs generated by livestock diseases epidemics. Application to the Classical Swine Fever case in Spain.

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Fernández-Carrión, E. and Ivorra, Benjamin and Martínez López, Beatriz and Ramos, A. M. and Sánchez-Vizcaíno, José Manuel (2015) Implementation and validation of an economic module for the epidemiological model Be-FAST to predict the costs generated by livestock diseases epidemics. Application to the Classical Swine Fever case in Spain. (Unpublished)

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Abstract

Classical Swine Fever (CSF) is one of the most harmful livestock di-seases for the economy of the swine sector worldwide. Specifically in Spain, the costs in the two last CSF outbreaks (1997 and 2001) have been estimated above 108 million euros. In this work, we aim to evaluate the economic impact of important livestock disease epidemics, and particularly the CSF in Spain. This study starts with a preliminary classification of the costs associated with CSF epidemics. In order to estimate the expected costs of a given epidemic in a considered area, a new economic module has been integrated into the epidemiological model Be-FAST, a time-spatial stochastic spread mathematical model for studying the transmission of diseases within and between farms. The input data for economic parameters have been obtained from entities related with the swine industry in Spain. The new Be-FAST module is tested by comparing the results obtained with historical data from CSF epidemics in Spain. The outcomes show that severe CSF epidemics also have a strong economic impact with around 80% of the costs related to animal culling, while costs associated with control measures are directly associated with the number of infected farms and the duration of the epidemic. The results presented in this work are expected to provide valuable information to decision makers, including animal health officials and insurance companies, and can be extended to other livestock diseases or used to predict the economic impact of future outbreaks.


Item Type:Article
Subjects:Sciences > Mathematics > Numerical analysis
Sciences > Mathematics > Mathematical statistics
Medical sciences > Veterinary
Social sciences > Economics > Economic planning
ID Code:29370
Deposited On:09 Apr 2015 07:59
Last Modified:12 Dec 2018 15:06

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