Bovine besnoitiosis is a cattle disease caused by a protozoan parasite called Besnoitia besnoiti. It is of serious economic concern to the cattle industry and also compromises animal welfare. For several years, it has been considered an emerging disease in some countries and regions located in the north of Europe far away from the known endemic areas in the south. This study describes the situation in the southern part of Belgium, where the parasite was recently introduced through imports of animals coming from departments of France where the disease was present. It details the detection of clinical cases as well as disease transmission features related to contacts during grazing and sales of infected cattle. A tracking and monitoring system was quickly set up and detected twelve outbreaks. Several cattle were controlled, but the lack of appropriate regulations weakens disease-management efforts. Hopefully, this predictable and silent introduction triggers the awareness of decision-makers about the need for an appropriate prevention and control policy, law enforcement, and the implementation of necessary measures to avoid bovine besnoitiosis becoming endemic in Belgium or other non-endemic countries. In addition, more proactive surveillance is required from authorities through threat analysis in the context of the risk of emergence or re-emergence of infectious animal diseases.

Bovine besnoitiosis (BB) is a chronic and debilitating parasitic disease in cattle caused by the protozoan parasite Besnoitia besnoiti. South European countries are affected and have reported clinical cases of BB. However, BB is considered as emerging in other countries/regions of central, eastern and northern Europe. Yet, data on drivers of emergence of BB in Europe are scarce. In this study, fifty possible drivers of emergence of BB in cattle were identified. A scoring system was developed per driver. Then, the scoring was elicited from eleven recognized European experts to: (i) allocate a score to each driver, (ii) weight the score of drivers within each domain and (iii) weight the different domains among themselves. An overall weighted score was calculated per driver, and drivers were ranked in decreasing order of importance. Regression tree analysis was used to group drivers with comparable likelihoods to play a role in the emergence of BB in cattle in Europe. Finally, robustness testing of expert elicitation was performed for the seven drivers having the highest probability to play a key role in the emergence of BB: i.e., (i) legal/illegal movements of live animals from neighbouring/European Union member states or (ii) from third countries, (iii) risk of showing no clinical sign and silent spread during infection and post infection, (iv) as a consequence, difficulty to detect the emergence, (v) existence of vectors and their potential spread, (vi) European geographical proximity of the pathogen/disease to the country, and (vii) animal density of farms. Provided the limited scientific knowledge on the topic, expert elicitation of knowledge, multi-criteria decision analysis, cluster and sensitivity analyses are very important to prioritize future studies, e.g., the need for quantitative import risk assessment and estimation of the burden of BB to evidence and influence policymaking towards changing (or not) its status as a reportable disease, with prevention and control activities targeting, firstly, the top seven drivers. The present methodology could be applied to other emerging animal diseases.