Implementing a probabilistic definition of freedom from infection to facilitate trade of livestock: Putting theory into praxis for the example of bovine herpes virus-1

A description and qualitative comparison of the elements of heterogeneous bovine viral diarrhea control programs that influence confidence of freedom

“…Reasons for these differences can also relate to other factors, such as political realities, cost efficiency, human behavior, or cultural differences (Lindberg and Houe, 2005;Heffernan et al, 2009). This strongly suggests, in agreement with earlier studies (More et al, 2009;Schuppers et al, 2012;Toftaker et al, 2018), that context-specific key factors influence the risks of introduction and must be taken in account in any analysis meant to develop a method to compare the probability of freedom offered by different CEP.…”

“…In the past, freedom from infection claims were underpinned by defined input standards that provide a detailed description of the activity required, such as testing protocol(s) based on negative test result(s), and these were accepted as proof of freedom from infection (More et al, 2009;Schuppers et al, 2012). However, the probability and associated uncertainty that an animal or herd is truly free from infection is not solely dependent on test result and related test characteristics, but is also influenced by the risk that infection had been introduced into the herd before initial testing but not (yet) detected, or had been (re)introduced into the herd subsequent to testing (or between rounds of testing; Schuppers et al, 2012). This suggests that a more accurate estimation of confidence of freedom from infection can be achieved through an output-based approach, noting that differing sanitary measures have the potential to provide the same level of animal health protection (More et al, 2009).…”

“…This suggests that a more accurate estimation of confidence of freedom from infection can be achieved through an output-based approach, noting that differing sanitary measures have the potential to provide the same level of animal health protection (More et al, 2009). Using this approach, account should be taken of factors that influence the risks of either not detecting infection if present or of introducing infection, such as test procedures preceding export, the geographic location of herds, and animal movements (More et al, 2009;Schuppers et al, 2012;Toftaker et al, 2018).…”

“…Ultimately, the project aims to develop simple and practical tools to inform farmers of infection risk when buying animals from certain territories and farms within territories. The project builds on earlier work to evaluate confidence in freedom in CEP, where a range of methods have been used, including scenario-tree analysis and Bayesian and latent class modeling (Martin et al, 2007;Cameron, 2012;Schuppers et al, 2012). This earlier work is promising but…”

Active animal health surveillance in European Union Member States: gaps and opportunities

“…[14], Bovine Herpes virus 1 [15], Avian Influenza virus [16], Transmissible Spongiform Encephalopathies [17,18], Mycobacterium bovis subsp. tuberculosis [19][20][21][22], Mycobacterium avium subsp.…”