Principal Investigator: Robin Dillon-Merrill
Other Researchers: Gary Shiffman, Catherine H. Tinsley
This research intended to (a) develop clear prescriptive recommendations for how to plan and communicate event information (especially regarding near-miss events) to reduce the potential for disproportionate fear and dread; (b) summarize and evaluate the conceptual and practical soundness of alternative risk communication strategies with specific focus on risk communication strategies regarding expedited screening for TSA and preparedness actions for natural disasters in areas subjected to repeated natural hazard events for FEMA; and (c) develop recommendations for how to include near-miss events in economic consequence modeling of terrorist events and natural disasters. For the near-miss effort, as will be described in more detail in the body of this report, we developed and tested experimental materials for risk inoculation messages versus control conditions. Additionally, we researched and published a paper in the Risk Analysis journal, “Airline Safety Improvement through Experience with Near-Misses: A Cautionary Tale,” that examined empirical data available about commercial airline incidents. The DARMS study while related did not clearly focus on near-miss events. Instead, in the DARMS study, objectives and attributes were identified for the TSA following procedures used to develop multi-attribute utility models (MAU). The search began broadly beginning with the TSA’s overarching strategic objective “Protect the Nation's transportation systems to ensure freedom of movement for people and commerce.” and then focused more narrowly on objectives pertaining to aviation security and specifically the DARMS initiative. Attribute measures, scales and consequences were selected and assessed based on informal conversations with colleagues from TSA and their contractor, Deloitte, and publically available information. Uncertainty about credible threats and flight vulnerability (the probability a security system can be defeated assuming a credible threat) was explored by decomposing the assessment of the probability of a successful attack into relevant component parts (e.g. risk classification, threat detection during screening) using probability trees. A probability function was derived to calculate system wide risk. A multi-attribute utility function was used as an illustration of how to compare the Current and DARMS approaches across attribute measures. Probability trees were also constructed as an illustration of how flight vulnerability could be decomposed and its component parts assessed. Assessment of branch probabilities was guided not by sensitive information but rather by a reasonable ordering of relative probability magnitudes (e.g. passengers posing a threat will be much less likely to received expedited screening, standard screening lanes will have a higher rate of threat detection than expedited screening lanes, DARMS with its proposed sophisticated countermeasures will reduce flight vulnerability overall). As it turned out, vulnerabilities using the probability trees calculations were similar to TSSRA assessments, with the current system being slightly higher than DARMS.