Application of integrated production and economic models to estimate the impact of Schmallenberg virus for various sheep production types in the UK and France

Vet Rec Open. 2014 Nov 21;1(1):e000036. doi: 10.1136/vetreco-2014-000036. eCollection 2014.

Abstract

Objective: The present study aimed to estimate and compare the economic impact of Schmallenberg virus (SBV) in different sheep production holdings using partial budget and gross margin analyses in combination with production models.

Participants: The sheep production types considered were lowland spring lambing, upland spring lambing and early lambing flocks in the UK, and grass lamb flocks of the Centre and West of France, extensive lambing flocks and dairy sheep flocks in France.

Methodology: Two disease scenarios with distinct input parameters associated with reproductive problems were considered: low and high impact. Sensitivity analyses were performed for the most uncertain input parameters, and the models were run with all of the lowest and highest values to estimate the range of disease impact.

Results: The estimated net SBV disease cost per year and ewe for the UK was £19.65-£20.85 for the high impact scenario and £6.40-£6.58 for the low impact scenario. No major differences were observed between the different production types. For France, the net SBV disease cost per year and ewe for the meat sheep holdings was £15.59-£17.20 for the high impact scenario and £4.75-£5.26 for the low impact scenario. For the dairy sheep, the costs per year and ewe were £29.81 for the high impact scenario and £10.34 for the low impact scenario.

Conclusions: The models represent a useful decision support tool for farmers and veterinarians who are facing decisions regarding disease control measures. They allow estimating disease impact on a farm accounting for differing production practices, which creates the necessary basis for cost effectiveness analysis of intervention strategies, such as vaccination.

Keywords: Disease impact; Economics; Production models; Schmallenberg.