Mason’s Center for Social Complexity is working on a project entitled “A Framework for Modeling the Population’s Response to a Nuclear WMD Event.” WMD is the acronym for “weapon of mass destruction,” and “population” in this context is that of a mega-city such as New York City. The project, funded by a grant from DTRA (Defense Threat Response Agency), uses agent-based modeling to project likely behavior of a large population in the days immediately following a nuclear WMD attack. An agent-based model (ABM) is one of a class of computational models for simulating the actions and interactions of autonomous agents (in this case, individuals) with a view to assessing their behavior in specific contexts. The project has won an additional two years of funding to improve the fidelity of the model.
What Is a WMD?
The Wikipedia definition of a weapon of mass destruction (WMD) is “a nuclear, radiological, chemical, biological or other weapon that can kill and bring significant harm to a large number of humans or cause great damage to human-made structures (e.g., buildings), natural structures (e.g., mountains), or the biosphere.” There is data extant on what specific people have done in very real disaster scenarios in the past. As painful as each of those instances was, the human response information gathered from them is integral to the characterization of human response to disasters of even larger magnitude. The currently available weapons of mass destruction are known, the methods of their delivery are constructed or are at least constructible, and the breadth of their destruction is computable. Because these weapons have not yet been deployed, however, no data is available on how people are likely to respond to their use. To the degree we can anticipate those responses, we can do things that can mitigate the damage, such as more effectively maximizing emergency responder resources and behaviors or designing disaster response educational programs.
The goal of this research is to advance understanding of the behavioral and social effects of a nuclear weapon of mass destruction (WMD) event on a large-city population; in this case New York City provides the large urban area under study. While the physical effects of such an event have been studied, the social effects — obviously more difficult to predict or to measure — are not well understood. Using agent-based modeling, the team reviewed, integrated, and exercised theories about how an affected population might react immediately to a WMD event, including both short term responses (e.g., evacuation/escape) and longer-term needs (e.g., finding water, food, and shelters, and even migrating). The model is not intended to address behavior beyond the immediate 30-day post-event period. So far, the team has modeled the population’s reaction in the first 60 minutes.
Research Team and Support
The project is under the direction of William G. Kennedy (Principal Investigator/PI, Mason Center for Social Complexity; computational social scientist) and Andrew T. Crooks (Mason Center for Social Complexity, and Mason’s Department of Computational and Data Sciences, College of Science). Two graduate research assistants, Annetta Burger and Richard Jiang, are the core of the team, with several others contributing now and in the early months of the project.
DTRA Funding and Support
The project has been funded for $462,094 for the past three years, starting in mid-2016. The two additional years have been funded at $150,00 per year. The DTRA Program Officer for this project will be Paul S. Tandy, PhD. Dr. Tandy is responsible for The Basic and Applied Research Thrust Area 2: Network Sciences, where the fundamental science of cognitive, information and networks results from the convergence of computer, information, mathematical, network, cognitive and social sciences. This research thrust expands our understanding of physical and social networks and advances knowledge of adversarial intent with respect to the acquisition, proliferation, and potential use of WMD. The methods in this DTRA program may include analytical, computational or numerical, or experimental means to integrate knowledge across disciplines and improve rapid processing of intelligence and dissemination of information.