A spatial risk assessment model framework for incursion of exotic animal disease into the European Union Member States

摘要: Abstract Disease incursion and transmission modelling can play an important role in elucidating pathways dynamics of transboundary diseases. It is pre-requisite for preparedness rapid response. A model framework has been developed which makes use global datasets to predict the probability entry exotic animal pathogens European Union (EU) member states (MSs) via some most likely routes introduction: legal trade livestock meat products, illegal red meat, wild dispersion, windborne vector dispersion human introduction pets. The was designed be applicable a wide range pathogens, many have limited data. We demonstrate its application through four case study pathogens: African swine fever, Classical Bluetongue classical rabies. results highlight differences between EU MSs; absolute values given route differed across MSs whilst different were predicted as having highest same MSs. Scenario analyses suggested that heavily influenced by pathogen prevalence country origin extent pose risk each other; greatest predominantly from countries within EU. While we believe input data are obtained high quality sources, there still big issues with regards uncertainty areas, particular populations consistency reporting animals all world. Thus, it inevitable degree associated values. However, main strength broad over entry. also relatively easy update new web based visualisation tool allows users interrogate model. As such, proposed here useful quantitative complement current qualitative early warning systems, helping drive risk-based surveillance activities, providing detailed comparisons indicate enter EU, into areas Europe.