Abstract
BACKGROUND: Schmallenberg virus (SBV) was first detected in November 2011 in Germany and then rapidly spread throughout Europe. In beef suckler farms, clinical signs are mainly associated with reproductive disorders, particularly in late gestation, and intransient and non-specific symptoms, namely diarrhea, inappetence and fever. The objectives of this study were to develop models that simulate the production of different beef suckler systems in the United Kingdom (UK) and France and to use these models to estimate, through partial budget analyses, the farm-level economic cost of SBV under two disease impact scenarios, namely high and low impact. The probability for a farm to be in the high or low scenario depends, among other, on the high, low or nil vectorial activity for a given period and location and on the period(s) of sensitivity of the animals to the disease. RESULTS: Under the high impact scenario, the estimated SBV impact ranged from 26€ to 43€ per cow per year in France and from 29€ to 36€ per cow per year in the UK. It was approximately half of this amount in the low impact scenario. These financial impacts represent 5 to 16% of the gross margin, depending on the country, impact scenario and livestock system considered. Most of the SBV impact originates from the costs of the steers and heifers not produced. Differences identified between the systems studied mainly stem from differences among the value of the steers or heifers sold: SBV impact is higher for British autumn calving systems compared to spring calving, and for French farms with calving and fattening activities compared to farms with only a single, annual calving activity. CONCLUSIONS: This study shows the usefulness of integrated production and economic models to accurately evaluate the costs of diseases and understand which factors have major impacts in the different systems. The models stand as a useful basis for animal health professionals when considering alternative disease control measures. They are also a farm accounting tool for estimating disease impact on differing production practices, which creates the necessary basis for cost-effectiveness analysis of intervention strategies, such as vaccination.