Animal and Plant Health Inspection Service
Epidemiologic and Economic Modelling
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The Modeling Team leads the evaluation, acquisition, and enhancement of applied animal disease models based on supportable epidemiologic and economic principles, effectively communicates modeling results through training and outreach, and supports Federal and State emergency management in animal disease outbreak response and preparedness. Specifically, the models address animal diseases that are highly contagious and may cause disruption to the food supply.
M&M uses several software applications to accomplish its objectives. InterSpread Plus® (ISP) and the North American Animal Disease Spread Model/Animal Disease Spread Model (NAADSM/ADSM) are the most commonly used applications to simulate animal disease spread and control. Both applications are stochastic state-transition models and provide a flexible SIR (susceptible/infected/removed) framework for users to simulate disease progression and spread by contact or air. Outbreak control measures such as vaccination and depopulation can be implemented while accounting for resource limitations in personnel or supplies.
The economic impacts of an animal disease outbreak are broad. Response costs associated with control of the outbreak include human resources needed for an emergency response, indemnity for animals which are depopulated to control disease, and the costs of eliminating the pathogen from the farm. There are also costs, such as trade restrictions and changes in consumer demand, which often have further-reaching consequences on the U.S. economy than the response costs.
Parameter Documentation
The applications used by the Modeling Team create a framework for the development of epidemiologic models that can simulate the spread and control of a variety of infectious diseases. User-defined input parameters broadly represent animal populations, disease dynamics within herd/flocks, disease transmission between herds/flocks, disease detection and surveillance, and disease control. Parameter values are derived from multiple sources, often including a review of the literature, available data, data generated from separate modeling tools, and subject matter elicitation.
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