Optimisation methods for assisting policy decisions on endemic diseases

Endemic disease of animals is an economic problem as it deprives humans of scarce resources that might otherwise satisfy human wants. Optimisation methods identify the strategies that minimise this economic problem. Given the potentially vast extent of the deprivation, not only in terms of lost wealth but also in terms of animal welfare, human health and environmental damage, this subject offers great benefits to decision-makers from the individual farm to the global level. This paper uses examples to illustrate the basic economic principles concerned. It shows how these principles may be extended to deal with current limitations in theory and practice. Lack of data is a common problem that may be dealt with by using computer simulation, theoretical approaches or the experiential knowledge of the decision-makers themselves. The latter method has the added advantage of greatly assisting with the difficult problem of effectively communicating the results of decision analysis to the decision-maker. In most situations the decision-maker will need to strike a balance between conflicting objectives such as short term profit and long term environmental damage (sustainability). This problem will require a wider perspective, which is greatly facilitated by collaboration between economists and scientists. The paper illustrates ways in which this has been done by using decision analysis methods to focus on the decision rather than the disease. The conclusions highlight priority areas for future research and development in this area. Topics include the contribution of endemic disease control to sustainable development, endemic disease eradication, capturing wider implications such as animal welfare and food safety, accounting for variation in rational decision making and dealing with risk.


Issue Date:
2006-10
Publication Type:
Working or Discussion Paper
PURL Identifier:
http://purl.umn.edu/46000
Total Pages:
13
Series Statement:
Working Paper
15




 Record created 2017-04-01, last modified 2017-08-25

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)