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2007 Conference (51st), February 13-16, 2007, Queenstown, New Zealand >
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http://purl.umn.edu/10354
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| Title: | An Optimal Surveillance Measure Against Foot-and-Mouth Disease in the United States |
| Authors: | van Ha, Pham Che, Tuong Nhu Kompas, Tom |
| Keywords: | Surveillance measures border quarantine disease incursion and spread Foot- and-Mouth disease stochastic optimal control |
| JEL Codes: | Q1 Q17 Q18 |
| Issue Date: | 2007 |
| Series/Report no.: | Conference Paper |
| Abstract: | Surveillance programs on farms and in the local environment provide an essential protection against the importation and spread of exotic diseases. Combined with border quarantine measures, these programs protect both consumers and producers from major health concerns and disease incursions that can potentially destroy local agricultural production and supporting industries, as well as generate substantial losses in trade and tourism. However, surveillance programs also impose costs in the form of expenditures on the surveillance program itself, along with the costs of disease management and eradication should an incursion occur. Taking border quarantine expenditures as given, this paper develops a stochastic optimal control model (with a jump-diffusion process) to determine the optimal level of surveillance activity against a disease incursion by minimizing the present value of the major direct and indirect costs of the disease, as well as the cost of the surveillance and disease management and eradication programs. The model is applied to the case of a potential entry and spread of Foot-and-Mouth Disease in the United States. Results show that current surveillance expenditures are far less than optimal. |
| URI: | http://purl.umn.edu/10354 |
| Institution/Association: | Australian Agricultural and Resource Economics Society - 2007>2007 Conference (51st), February 13-16, 2007, Queenstown, New Zealand |
| Total Pages: | 22 |
| Language: | English |
| Collections: | 2007 Conference (51st), February 13-16, 2007, Queenstown, New Zealand
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