Literature DB >> 26875754

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.

E Fernández-Carrión1, B Ivorra2, B Martínez-López3, A M Ramos2, J M Sánchez-Vizcaíno4.   

Abstract

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.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Be-FAST; Classical swine fever; Economic modeling; Epidemiological modeling; Risk surveillance

Mesh:

Year:  2016        PMID: 26875754     DOI: 10.1016/j.prevetmed.2016.01.015

Source DB:  PubMed          Journal:  Prev Vet Med        ISSN: 0167-5877            Impact factor:   2.670


  1 in total

1.  Motion-based video monitoring for early detection of livestock diseases: The case of African swine fever.

Authors:  Eduardo Fernández-Carrión; Marta Martínez-Avilés; Benjamin Ivorra; Beatriz Martínez-López; Ángel Manuel Ramos; José Manuel Sánchez-Vizcaíno
Journal:  PLoS One       Date:  2017-09-06       Impact factor: 3.240

  1 in total

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