An agent-based model of urban insurgence: Effect of gathering sites and Koopman mode analysis.

The paper investigates the effect of preferential gathering sites on urban insurgency in an agent-based model (ABM). The ABM model was proposed in earlier work and has been validated using FBI data. There is a nonlinear tradeoff between the local density of citizens due to the number of preferential gathering sites and the ability of law enforcement officers (LEOs) to adequately patrol that leads to a non-monotonic behavior in the number of large scale outburst of insurgency with respect to the number of gathering sites. The inclusion of a moderate number of sites decreases the number of large-scale outbursts. Having no gathering sites or a large number of gathering sites has a dilutive effect on the number of large-scale outbursts. Thus, this non-monotonicity indicates that a small number of organized units produces a larger insurgency effect than a larger number of distributed units. It is also shown, using Koopman mode analysis, that the spatial morphology of agents due to the gathering sites gives rise to temporal organization of the model dynamics; there is a prominent quasi-periodic component in the number of active and intimidated citizens and in the spatial distribution of the LEOs.

Agent-based modeling of drinking behavior: a preliminary model and potential applications to theory and practice.

OBJECTIVES: We developed a preliminary agent-based simulation model designed to examine agent-environment interactions that support the development and maintenance of drinking behavior at the population level. METHODS: The model was defined on a 1-dimensional lattice along which agents might move left or right in single steps at each iteration. Agents could exchange information about their drinking with each other. In the second generation of the model, a "bar" was added to the lattice to attract drinkers. RESULTS: The model showed that changes in drinking status propagated through the agent population as a function of probabilities of conversion, rates of contact, and contact time. There was a critical speed of population mixing beyond which the conversion rate of susceptible nondrinkers was saturated, and the bar both enhanced and buffered the rate of propagation, changing the model dynamics. CONCLUSIONS: The models demonstrate that the basic dynamics underlying social influences on drinking behavior are shaped by contacts between drinkers and focused by characteristics of drinking environments.

Implications of systems dynamic models and control theory for environmental approaches to the prevention of alcohol- and other drug use-related problems.

The approach described in this article is premised on the idea that drug and alcohol use-related problems are heterogeneously distributed with respect to population and geography, and therefore, are essentially local problems. More specifically, it is argued that viewing a local community as an interacting set of systems that support or buffer the occurrence of specific substance misuse outcomes, opens up to research two important prospects. The first of these involves creating adequate systems models that can capture the primary community structures and relationships that support public health problems such as alcohol and drug misuse and related outcomes. The second entails rationally testing control strategies that have the potential to moderate or reduce these problems. Understanding and controlling complex dynamic systems models nowadays pervades all scientific disciplines, and it is to research in areas such as biology, ecology, engineering, computer sciences, and mathematics that researchers in the field of addictions must turn to in order to better study the complexity that confronts them as they try to understand and prevent problems resulting from alcohol and drug use and misuse. Here we set out what such a systems-based understanding of alcohol- and drug use-related problems will require and discuss its implications for public policy and prevention programming.