Spatial distribution and incidence of bovine neonatal pancytopenia in Bavaria, Germany

德国巴伐利亚州牛新生儿全血细胞减少症的空间分布和发病率

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Abstract

BACKGROUND: Bovine neonatal pancytopenia (BNP) is a haemorrhagic disease of neonatal calves. BNP was first described in Germany in 2009, later on also in other European countries, and in New Zealand in 2011. The disease is characterised by spontaneous bleeding, pancytopaenia in the bone marrow, and a high case fatality ratio. The causal role of a specific bovine viral diarrhoea virus (BVDV) vaccine (PregSure®BVD, then Pfizer Animal Health, now Zoetis, Berlin, Germany) has been established over the last years, causing the production of alloantibodies in some vaccinated cattle, which in the case of pregnant cattle, are transferred to the newborn calf via the colostrum. However, striking regional differences in the incidence of the disease were observed within Germany and other countries, but as the disease was not notifiable, no representative data on the spatial distribution are available. In this study, we address the spatial distribution and incidence of BNP using the results of two representative surveys amongst cattle practitioners in Bavaria, Germany. The surveys, asking about the occurrence of BNP, were conducted in 2009 and 2010. Answers were analysed spatially by testing for clusters using space-time models. Practitioners were also asked how many cows they serve in their practice and this number was used to estimate the incidence of BNP. Furthermore, in the survey of 2010, practitioners were also asked about usage of vaccine against BVDV. RESULTS: From the results of the surveys, three clusters were identified in Bavaria. These clusters also coincided with the usage of the specific BVDV vaccine as indicated by the veterinary practices. Furthermore, the representative surveys allow the estimation of the incidence of BNP to be in the order of 4 cases per 10,000 calves at risk. CONCLUSIONS: The study is the only representative survey conducted on BNP. Despite the fact that BNP is a non-infectious disease, regional clusters were identified.

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