New publication Be-FAST in Preventive Veterinary Medicine
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
- We developed a novel economic module into Be-FAST software based on stochastic time-spatial model for livestock and infectious disease epidemics in order to evaluate losses associated to control measures.
- We validated the economic module with real data regarding the last Spanish epidemic of classical swine fever. The results show a good approximation to the real case.
- Final cost classification show a high impact of transferred cost in all simulations correlated strongly with the number of outbreaks. Indirect cost are strongly associated with the duration of the epidemic. Payable and calculated costs varied among severe and mild epidemics.
- Well-informed data collection of similar livestock diseases and/or regionsallow to work with Be-FAST to evaluate the economic impact of epidemics.
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."