Survey-based epidemiological investigation of risk factors for Bovine Herpesvirus 1 seropositivity

1. Survey-based epidemiological investigation of risk factors for Bovine Herpesvirus 1 seropositivity F. Boelaert 1, N. Speybroeck 2, A. de Kruif 3, M. Aerts 4, T. Burzykowski 4, G. Molenberghs 4, and D.L. Berkvens 2 1 Veterinary and Agrochemical Research Centre, Coordination Centre for Veterinary Diagnostics, Brussels, Belgium – e-mail frboe@var.fgov.be; 2 Institute of Tropical Medicine, Antwerp , Belgium; 3 Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Merelbeke , Belgium; 4 Centre for Statistics, Limburgs Universitair Centrum, Universitaire Campus, Diepenbeek , Belgium INTRODUCTION RESULTS In 1998, a large one-stage cluster sample survey of the Belgian cattle population estimated the bovine herpesvirus 1 (BoHV-1) herd seroprevalence to be 67% (95% confidence interval (CI)=62-72). A design-based analysis, taking into account the effects of clustering and stratification estimated the animal-level seroprevalence to be 36% (95% CI=30-42). The objective of the present study was to investigate these survey results for animal-level risk factors associated with BoHV-1 seropositivity. The animal-level factors age, sex and origin (purchased or homebred), and the herd-level covariate herd size were associated with seropositivity to the BoHV-1. First, an increasing (centered) age was a risk factor for seropositivity, but this effect leveled off at higher age (significant negative quadratic term). Second, males were more at risk of being seropositive, compared to females. Significant interactions were observed between the effects of the third and fourth factors associated with bovine herpesvirus 1 seropositivity, origin of the animal and herd size. The resulting overall effect due to purchase status, herd size and the interactions was different for smaller herds, compared to larger ones. For small sized herds (up to 50 animals on the premises), purchased cattle were more at risk, compared to homebred ones, and increasing herd size was also a risk factor. For larger herds, no overall effect was observed any more for origin of cattle and herd size. Figures 1 and 2 show a graphical representation of these relationships, for bulls (Figure 1) and cows (Figure 2). Figure 1. Relation between farm size and the probability for bulls to be seropositive to BoHV-1, for different ages and for different origins, per farm size. MATERIALS AND METHODS Different covariates, obtained via SANITEL, exist. First, there are the animal-level factors: age, sex and origin (purchased or homebred). Second, there are the farm-level covariates: farm type (dairy, mixed or beef) and farm size (number of cattle on the premises). Last, the densities of the cattle and of the farms in the municipalities were determined by dividing the number of cattle and farms, respectively, by the effective agricultural land. Cluster-specific random-effects logistic regression models were implemented. All two-by-two interactions with a biologically meaningful interpretation and second-order (quadratic) factors were considered in a forward stepwise-selection procedure. The polynomial predictor variables were centred to avoid problems of multicollinearity. Selection of the (relative) most important models was based on Akaike’s Information Criterion. Figure 2. Relation between farm size and the probability for cows to be seropositive to BoHV-1, for different ages and for different origins, per farm size. DISCUSSION For farms up to 50 animals, purchased status and increasing farm size were risk factors, whereas these effects were not observed for larger farms. The interpretation of this marked difference in risk assessment for cattle in smaller farms, compared to larger ones, considers the biology of BoHV-1 infection. A key epidemiological feature of BoHV-1 is its contagion. Contagion is a group effect of the dependent variable. Once the infection is introduced in a farm it quickly spreads within-farm, to purchased and to homebred herd mates. This within-farm infection dynamic is cardinal, since the seroprevalence figures, and consequently the statistical model outcome, are a post-epidemic snapshot. Consequently, seroprevalence figures are non-informative with regard to the within-farm index case and the within-farm infection dynamic. We hypothesise that in larger farms, the contagion of homebred herd mates, which are more numerous compared to smaller farms, could have masked the importance of purchased index cases as direct sources of BoHV-1 introduction (Figure 3). From a biological viewpoint, purchase status would be a direct risk factor for farms of any size. Figure 3. Within-farm BoHV-1 infection dynamic masks the importance of purchased index cases as direct sources of BoHV-1 introduction.