Discussion of Biosecurity, Diseases, and Invasive Species: Implications of Bioterrorism for Agriculture

Article excerpt

Both papers in this session illustrate a growing trend among agricultural economists to let go of their comfort zones and move beyond the bounds of the traditional market analysis and a world of certainty into the less familiar and more challenging world of uncertainty. This trend augurs well for the profession and demonstrates the imperialistic tendency of economics to deal with all kinds of issues.

The problem of invasive species is one of enormous concern, not only because they may cause disruption and losses to agriculture, forestry, and other parts of the economy, but also because of their potential use in bioterrorism. A country's biosecurity therefore depends on its ability to prevent incursion of new species, early detection of those species that escape border controls, and management of established populations. The issue however is that resources available to manage pest incursions are limited, and there is a need to prioritize the threats and allocate such resources in a manner that will yield the highest return on investment, i.e., minimize the costs and maximize the benefits. Both papers address this issue, starting with the underlying premise that while it is clear that the threat of invasive species can never be eliminated, it is certainly possible to manage the threats posed through a combination of pre- and postevent responses.

The first paper by Elbakidze and McCarl examines the economic trade-off between the costs of pre-event preparedness and postevent response to potential introduction of an infectious animal disease. The optimization problem addressed by the authors can be viewed from an insurance perspective as trying to determine the optimal amount (premium) that a decision maker should invest up front in the costs of pre-event actions so as to minimize the consequences of the risk. Specifically, the paper notes that pre-event actions impose costs regardless of event occurrence, while postevent costs are only incurred when the incident occurs and thus depend on the probability of the event when computing expected annual costs.

The authors use a simple theoretical model to analyze what they call the "balance problem" and subsequently conduct an empirical investigation using data drawn from the Foot and Mouth Disease (FMD) literature in the context of possible introduction into Texas. The paper does a nice job in setting out the issues and providing a discussion of an expanded framework for decision making in the context of an animal disease event. It identifies six basic categories including: anticipation, prevention, detection, installation, response, and recovery. The modeling approach is that of discrete stochastic programming and is suitable given that it can accommodate the notion that later decisions depend on both earlier decisions and on the outcomes of earlier uncertain events.

To my mind, the main contribution of the paper to the literature is the insight gained from attempting to apply the framework to data on FMD. The difficulties of modeling biological invasion are apparent and show up in the several assumptions that have to be made in order for the problem to lend itself to an optimization solution. The approach, however, does highlight the type of data that would be required when conducting an investigation of this type. While it is a fact that real world situations will involve making several decisions, most of which are contingent on previous ones, the results from the case study are encouraging. Although preliminary, the results provide a set of rules of thumb that decision makers might consider using in the absence of undertaking detailed investigations. For example, it is advisable to limit the level of preevent investments (insurance premium) in situations where information at hand suggests that the disease spread rate is small, the probability of disease introduction is small, and the response strategy is known to be effective. The main drawback to the study, as conceded by the authors, is the sensitivity of the analysis to the functional form and the parameters chosen. …