World trade is a boon to economic development but it also increases the risk of dispersing human, animal, and plant diseases. Disease impacts on crop yields and livestock put global food supplies at risk and newly emergent diseases that move from animals to humans can threaten human health. But because trade is also one of the main drivers of economic development, it is important that it not be disrupted unnecessarily by measures to protect against disease risk. Striking the right balance is currently difficult to achieve, however, because trade impacts are not systematically incorporated into national and international disease risk assessments. This award supports an interdisciplinary and international team who seek to solve that problem by developing new tools for evaluating the disease risks of world trade. The risk assessment tools produced by the project will provide animal, plant, and human health authorities at national and international levels with the capacity to make improved assessment of the disease risks associated with imports, and of the consequences of alternative trade responses. Improving disease risk management will enhance national security and economic well-being by reducing both disease dispersal and the losses caused by trade interdictions. The project also will strengthen collaborations between US and UK scientists and train graduate students and post-doctoral scientists in research.
The researchers will compile data from multiple secondary sources. Data on plant diseases, livestock and wildlife diseases, disease outbreaks, and global emerging diseases, will be provided by such sources as the National Plant Protection Organizations in the United States and the United Kingdom, the United States Department of Agriculture's Animal and Plant Health Inspection Service, and the UK Food and Environment Research Agency. Public domain databases will provide time series data on trade, including trade volumes, trade values, sanitary and phtyosanitary conditions along trade pathways in exporting and importing countries, as well as Gross Domestic Product (GDP) data to estimate national value at risk. These data will be used to parameterize econometric profit maximization risk models to assess the effects of trader decisions and trade networks on the transmission of disease. The models will consider the intervention in trade at three spatial scales (local, national, and global) on incidence of disease transport and effects of altered trade on economic development. The models will be incorporated into a virtual laboratory decision support system to help evaluate alternative incentive-based trade management practices and the effects of decisions on the risk of disease spread.
