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Developing a Generic Risk Assessment Simulation Modelling Software Tool for Assessing the Risk of Foot and Mouth
B Tameru1, B Gebremadhin1, T Habtemariam1
1Center for Computational Epidemiology, Bioinformatics and Risk Analysis (CCEBRA), College of Veterinary Medicine, Nursing and Allied Health, Tuskegee University, Tuskegee, AL 36088. Fax : 334-724-4277 http://www.onemedicine.tuskegee.edu.
Abstract:
Foot and Mouth disease (FMD) is a highly contagious viral disease that affects all cloven-hoofed animals. Because of its devastating effects on the agricultural industry, many countries take measures to stop the introduction of FMD virus into their countries. Decision makers at multiple levels of the United States Department of Agriculture (USDA) use Risk Assessments (RAs) (both quantitative and qualitative) to make better and more informed scientifically based decisions to prevent the accidental or intentional introduction of the disease. There is a need for a generic RA that can be applied to any country (whether FMD free or non-FMD free) and for any product (FMD infected animals and animal products). We developed a user-friendly generic RA tool (software) that can be used to conduct and examine different scenarios of quantitative/qualitative risk assessments for the different countries with their varying FMD statuses in relation to reintroduction of FMD virus into the USA. The program was written in Microsoft Visual Basic 6.0 (Microsoft Corporation, Redmond, Washington, USA). The @Risk 6.1 Developer Kit (RDK) and @Risk 6.1 Best Fit Kit library (Palisade Corporation, Newfield, NY.USA) was used to build Monte Carlo simulation models. Microsoft Access 2000 (Microsoft Corporation, Redmond, Washington, USA) was used and SQL to query the data. Different input probability distributions can be selected for the nodes in the scenario tree and different output for each end-state of the simulation is given in different graphical formats and statistical values are used in describing the likelihood of FMD virus introduction. Sensitivity Analysis in determining which input factor has more effect on the total risk outputs is also given. The developed generic RA tools can be eventually extended and modified to conduct RAs for other animal diseases and animal products.

