Reviewing model application to support animal health decision making

Prev Vet Med. 2011 Apr 1;99(1):60-7. doi: 10.1016/j.prevetmed.2011.01.004.

Abstract

Animal health is of societal importance as it affects human welfare, and anthropogenic interests shape decision making to assure animal health. Scientific advice to support decision making is manifold. Modelling, as one piece of the scientific toolbox, is appreciated for its ability to describe and structure data, to give insight in complex processes and to predict future outcome. In this paper we study the application of scientific modelling to support practical animal health decisions. We reviewed the 35 animal health related scientific opinions adopted by the Animal Health and Animal Welfare Panel of the European Food Safety Authority (EFSA). Thirteen of these documents were based on the application of models. The review took two viewpoints, the decision maker's need and the modeller's approach. In the reviewed material three types of modelling questions were addressed by four specific model types. The correspondence between tasks and models underpinned the importance of the modelling question in triggering the modelling approach. End point quantifications were the dominating request from decision makers, implying that prediction of risk is a major need. However, due to knowledge gaps corresponding modelling studies often shed away from providing exact numbers. Instead, comparative scenario analyses were performed, furthering the understanding of the decision problem and effects of alternative management options. In conclusion, the most adequate scientific support for decision making - including available modelling capacity - might be expected if the required advice is clearly stated.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animal Diseases / epidemiology
  • Animal Diseases / prevention & control*
  • Animal Diseases / transmission
  • Animal Welfare*
  • Animals
  • Decision Making
  • Models, Biological*
  • Predictive Value of Tests
  • Risk Assessment