Youngyun Chungbaek

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In this paper we describe a multiagent simulation model of human behavior in the aftermath of a hypothetical, largescale, human-initiated crisis in the center of Washington D.C. Prior studies of this scenario have focused on modeling the physical effects of the attack, such as thermal and blast effects, prompt radiation, and fallout. Casualty and mortality(More)
We present a synthetic information and modeling environment that can allow policy makers to study various counter-factual experiments in the event of a large human-initiated crisis. The specific scenario we consider is a ground detonation caused by an improvised nuclear device in a large urban region. In contrast to earlier work in this area that focuses(More)
We use a synthetic population model of Washington DC, including residents and transients such as tourists and business travelers, to simulate epidemics of influenza-like illnesses. Assuming that the population is vaccinated at the compliance levels reported by the CDC, we show that additionally implementing a policy that encourages healthy behaviors (such(More)
Despite the recent advancements in graph partitioning techniques and algorithms, achieving static load balancing in agent-based epidemiological applications is challenging. Input to these simulations is a large agent-location bipartite graph that is highly complex and non-uniform. In this paper, we compare several static load distribution schemes, including(More)
OBJECTIVES This research studies the impact of influenza epidemic in the slum and non-slum areas of Delhi, the National Capital Territory of India, by taking proper account of slum demographics and residents' activities, using a highly resolved social contact network of the 13.8 million residents of Delhi. METHODS An SEIR model is used to simulate the(More)
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