First Expert Elicitation of Knowledge on Drivers of Emergence of Bovine Besnoitiosis in Europe

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 a...

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Detalhes bibliográficos
Autores: Saegerman, Claude, Evrard, Julien, Houtain, Jean-Yves, Alzieu, Jean-Pierre, Bianchini, Juana, Mpouam, Serge Eugène, Schares, Gereon, Liénard, Emmanuel, Jacquiet, Philippe, Villa, Luca, Álvarez García, Gema, Gazzonis, Alessia Libera, Gentile, Arcangelo, Delooz, Laurent
Formato: artículo
Fecha de publicación:2022
País:España
Recursos:Universidad Complutense de Madrid (UCM)
Repositorio:Docta Complutense
Idioma:inglés
OAI Identifier:oai:docta.ucm.es:20.500.14352/73219
Acesso em linha:https://hdl.handle.net/20.500.14352/73219
Access Level:acceso abierto
Palavra-chave:bovine besnoitiosis
Besnoitia besnoiti
drivers
expert elicitation
cattle
multi-criteria decision analysis (MCDA)
clustering analysis
sensitivity analysis
Ganado vacuno
Sanidad animal
3104.07 Ovinos
Descrição
Resumo: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.