Publications

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The objectives of this presentation are: (1) To determine if healthcare settings serve as intensive transmission environments for influenza epidemics, increasing effects on communities; (2) To determine which mitigation strategies are best for use in healthcare settings and in communities to limit influenza epidemic effects; and (3) To determine which mitigation strategies are best to prevent illness in healthcare workers.

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Cigarette smoking presented the most significant public health challenge in the United States in the 20th Century and remains the single most preventable cause of morbidity and mortality in this country. A number of System Dynamics models exist that inform tobacco control policies. We reviewed them and discuss their contributions. We developed a theory of the societal lifecycle of smoking, using a parsimonious set of feedback loops to capture historical trends and explore future scenarios. Previous work did not explain the long-term historical patterns of smoking behaviors. Much of it used stock-and-flow to represent the decline in prevalence in the recent past. With noted exceptions, information feedbacks were not embedded in these models. We present and discuss our feedback-rich conceptual model and illustrate the results of a series of simulations. A formal analysis shows phenomena composed of different phases of behavior with specific dominant feedbacks associated with each phase. We discuss the implications of our society's current phase, and conclude with simulations of what-if scenarios. Because System Dynamics models must contain information feedback to be able to anticipate tipping points and to help identify policies that exploit leverage in a complex system, we expanded this body of work to provide an endogenous representation of the century-long societal lifecycle of smoking.

Loki-Infect 3 is a desktop application intended for use by community-level decision makers. It allows rapid construction of small-scale studies of emerging or hypothetical infectious diseases in their communities and evaluation of the potential effectiveness of various containment strategies. It was designed with an emphasis on modularity, portability, and ease of use. Our goal is to make this program freely available to community workers across the world.

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We develop a parsimonious model of the interbank payment system. The model incorporates an endogenous instruction arrival process, a scale-free topology of payments between banks, a fixed total liquidity which limits banks' capacity to process arriving instructions, and a global market that distributes liquidity. We find that at low liquidity the system becomes congested and payment settlement loses correlation with payment instruction arrival, becoming coupled across the network. The onset of congestion is evidently related to the relative values of three characteristic times: the time for banks' net position to return to 0, the time for a bank to exhaust its liquidity endowment, and the liquidity market relaxation time. In the congested regime settlement takes place in cascades having a characteristic length scale. A global liquidity market substantially attenuates congestion, requiring only a small fraction of the payment-induced liquidity flow to achieve strong beneficial effects. © 2007 Elsevier B.V. All rights reserved.

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This report describes a model Transport Processes Investigation (TPI) where field-scale vadose zone flow and transport processes are identified and verified through a systematic field investigation at a contaminated DOE site. The objective of the TPI is to help with formulating accurate conceptual models and aid in implementing rational and cost effective site specific characterization strategies at contaminated sites with diverse hydrogeologic settings. Central to the TPI are Transport Processes Characterization (TPC) tests that incorporate field surveys and large-scale infiltration experiments. Hypotheses are formulated based on observed pedogenic and hydrogeologic features as well as information provided by literature searches. The field and literature information is then used to optimize the design of one or more infiltration experiments to field test the hypothesis. Findings from the field surveys and infiltration experiments are then synthesized to formulate accurate flow and transport conceptual models. Here we document a TPI implemented in the glacial till vadose zone at the Fernald Environmental Management Project (FEMP) in Fernald, Ohio, a US Department of Energy (DOE) uranium processing site. As a result of this TPI, the flow and transport mechanisms were identified through visualization of dye stain within extensive macro pore and fracture networks which provided the means for the infiltrate to bypass potential aquatards. Such mechanisms are not addressed in current vadose zone modeling and are generally missed by classical characterization methods.

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An infiltration and dye transport experiment was conducted to visualize flow and transport processes in a heterogeneous, layered, sandy-gravelly fluvial deposit adjacent to Rio Bravo Boulevard in Albuquerque, NM. Water containing red dye followed by blue-green dye was ponded in a small horizontal zone ({approx}0.5 m x 0.5 m) above a vertical outcrop ({approx}4 m x 2.5 m). The red dye lagged behind the wetting front due to slight adsorption thus allowing both the wetting front and dye fronts to be observed in time at the outcrop face. After infiltration, vertical slices were excavated to the midpoint of the infiltrometer exposing the wetting front and dye distribution in a quasi three-dimensional manner. At small-scale, wetting front advancement was influenced by the multitude of local capillary barriers within the deposit. However at the scale of the experiment, the wetting front appeared smooth with significant lateral spreading {approx} twice that in the vertical, indicating a strong anisotropy due to the pronounced horizontal layering. The dye fronts exhibited appreciably more irregularity than the wetting front, as well as the influence of preferential flow features (a fracture) that moved the dye directly to the front, bypassing the fresh water between.

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Concepts from Complexity Science are valuable and allow a simulation approach for critical infrastructures that is flexible and has wide ranging applications.

Critical Infrastructures are formed by a large number of components that interact within complex networks. As a rule, infrastructures contain strong feedbacks either explicitly through the action of hardware/software control, or implicitly through the action/reaction of people. Individual infrastructures influence others and grow, adapt, and thus evolve in response to their multifaceted physical, economic, cultural, and political environments. Simply put, critical infrastructures are complex adaptive systems. In the Advanced Modeling and Techniques Investigations (AMTI) subgroup of the National Infrastructure Simulation and Analysis Center (NISAC), we are studying infrastructures as complex adaptive systems. In one of AMTI's efforts, we are focusing on cascading failure as can occur with devastating results within and between infrastructures. Over the past year we have synthesized and extended the large variety of abstract cascade models developed in the field of complexity science and have started to apply them to specific infrastructures that might experience cascading failure. In this report we introduce our comprehensive model, Polynet, which simulates cascading failure over a wide range of network topologies, interaction rules, and adaptive responses as well as multiple interacting and growing networks. We first demonstrate Polynet for the classical Bac, Tang, and Wiesenfeld or BTW sand-pile in several network topologies. We then apply Polynet to two very different critical infrastructures: the high voltage electric power transmission system which relays electricity from generators to groups of distribution-level consumers, and Fedwire which is a Federal Reserve service for sending large-value payments between banks and other large financial institutions. For these two applications, we tailor interaction rules to represent appropriate unit behavior and consider the influence of random transactions within two stylized networks: a regular homogeneous array and a heterogeneous scale-free (fractal) network. For the stylized electric power grid, our initial simulations demonstrate that the addition of geographically unrestricted random transactions can eventually push a grid to cascading failure, thus supporting the hypothesis that actions of unrestrained power markets (without proper security coordination on market actions) can undermine large scale system stability. We also find that network topology greatly influences system robustness. Homogeneous networks that are 'fish-net' like can withstand many more transaction perturbations before cascading than can scale-free networks. Interestingly, when the homogeneous network finally cascades, it tends to fail in its entirety, while the scale-free tends to compartmentalize failure and thus leads to smaller, more restricted outages. In the case of stylized Fedwire, initial simulations show that as banks adaptively set their individual reserves in response to random transactions, the ratio of the total volume of transactions to individual reserves, or 'turnover ratio', increases with increasing volume. The removal of a bank from interaction within the network then creates a cascade, its speed of propagation increasing as the turnover ratio increases. We also find that propagation is accelerated by patterned transactions (as expected to occur within real markets) and in scale-free networks, by the 'attack' of the most highly connected bank. These results suggest that the time scale for intervention by the Federal Reserve to divert a cascade in Fedwire may be quite short. Ongoing work in our cascade analysis effort is building on both these specific stylized applications to enhance their fidelity as well as embracing new applications. We are implementing markets and additional network interactions (e.g., social, telecommunication, information gathering, and control) that can impose structured drives (perturbations) comparable to those seen in real systems. Understanding the interaction of multiple networks, their interdependencies, and in particular, the underlying mechanisms for their growth/evolution is paramount. With this understanding, appropriate public policy can be identified to guide the evolution of present infrastructures to withstand the demands and threats of the future.