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Cost-Effective Control of a Quarantine Disease: A Quantitative Exploration Using “Design of Experiments” Methodology and Bio-Economic Modeling

August 2007 , Volume 97 , Number  8
Pages  945 - 957

Annemarie Breukers , Wopke van der Werf , Jack P. C. Kleijnen , Monique Mourits , and Alfons Oude Lansink

First, fourth, and fifth authors: Department of Social Sciences, Business Economics Group, and second author: Department of Plant Sciences, Group Crop and Weed Ecology, Wageningen University, P.O. Box 8130, 6700 EW Wageningen, The Netherlands; and third author: Department of Information Systems and Management, Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands.

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Accepted for publication 4 March 2007.

An integrated approach to control of quarantine diseases at the level of the plant production chain is complicated. The involved actors have different interests and the system is complex. Consequently, control policies may not be cost effective. By means of a bio-economic model for brown rot in the Dutch potato production chain, the efficacy of different control options was quantitatively analyzed. An impact analysis was performed using the methodology of “design of experiments” to quantify the effect of factors in interaction on incidence and costs of brown rot. Factors can be grouped as policy, sector, economic, and exogenous factors. Results show that brown rot incidence and economic consequences are determined predominantly by policy and sector factors and, to a lesser extent, by economic and exogenous factors. Scenario studies were performed to elucidate how the government and sector can optimize the cost-effectiveness of brown rot control. Optimal cost-effectiveness of control requires cooperation of the sector and government, in which case brown rot incidence can be reduced by 75% and the costs of control can be reduced by at least 2 million euros per year. This study demonstrates quantitatively the potential contribution of an integrated approach to cost-effective disease control at chain level.

Additional keywords: metamodeling, Ralstonia solanacearum, simulation model.

© 2007 The American Phytopathological Society