The study examines how best to estimate terrorism risk in cities that receive funding through the Department of Homeland Security's (DHS) Urban Areas Security Initiative. The initiative provides grants to help cities prepare for, respond to and recover from acts of terrorism. Most of these funds are currently allocated based on a formula that combines rough indicators of the risk of terrorism, such as the size of the population in the area.
The report argues that the DHS' goal should be to allocate funds where they can most effectively reduce terrorism risk, rather than simply spending money in areas facing the greatest risk. However, until the department assesses the cost-effectiveness of most counter-terrorism measures, it is appropriate to allocate some or all such funds in proportion to estimated risk, the report says.
"While many people support the idea of risk-based allocation for homeland security, no one has clearly described how to do it effectively," said Henry Willis, a RAND policy researcher and lead author of the study. "We've demonstrated a way to combine the best available information to measure terrorism risk. We use not just the results of one model, but the results of many, because the chance of any one prediction being right is quite small."
Researchers say the proposed method produces risk estimates that reflect a wide range of perspectives on terrorism. This is important because it is impossible to predict future terrorist events with precision.
If risk estimates are to guide how homeland security funds are distributed, inaccurate calculations could mean that some communities would not receive the funding needed to adequately guard against a possible attack, according to the RAND study. To reduce the chance of underestimating risks, RAND researchers propose a method to combine models that addresses uncertainties about three components of risk.
"There are three questions to ask when measuring the risk of a terrorist attack in a particular community," said Andrew Morral, another author, along with Terrence Kelly and Jamison Medby of RAND, of the study. "What are the known or suspected terrorist threats? What are the vulnerabilities of people and facilities to these threats? And finally, what could be the consequences of a terrorist attack?"
He added many people look at just one or two indicators of possible risk – like population size, location of government buildings or the presence of nuclear power plants – and conclude that their communities are at especially high risk of terrorist attack. Instead, the RAND study recommends that DHS use reliable event-based models of risk that provide a framework for judging how threat, vulnerability and consequences affect terrorism risk.
Event-based models are built upon detailed analysis of consequences from specific attack scenarios. Using this approach could provide important insights into questions such as: How are current programs reducing risk? When and where may new terrorist threats be emerging? And, how do changes in levels of threat, vulnerability and consequences affect risk levels?
Most commonly, federal assistance has been distributed based on a community's population. The presumption is that the bigger the population, the larger the risk. Although easy to understand and measure, this approach does not take into account issues such as an area's vulnerability and the potential threat of an attack, according to researchers.
Until DHS adopts a reliable event-based model, the RAND study advises policymakers to use density-weighted population as a risk indicator, because it is more closely correlated to estimates of risk than one based purely on population.
The analyses in the report were built upon an event-based terrorism risk model developed by Risk Management Solutions, a provider of products and services to the insurance industry for the quantification and management of catastrophe risks.
Printed copies of "Estimating Terrorism Risk" (ISBN 0-8330-3834-6) can be ordered from by calling (877) 584-8642.