|Abstract:||Drug addiction is a worldwide epidemic. Understanding the nature of addiction, its stages and nuances is crucial to reducing its spread. Recent computational models depicting drug addiction explain why the problem of addiction defies solution. Researchers have also recognized relapse as a major component of addiction that contributes to the difficulties of remedying the condition. Calls for explanatory models have been raised.
Our contribution to the effort of modeling and understanding addiction is a dynamical system approach that describes addiction mathematically. Incorporated into our equations are trends and changes in the addict population, levels of drug use severity, or similarly quantification of the ability of an addict to be rehabilitated and tendencies of addicts to relapse.
Computational simulations are utilized to visually aid the model's comprehensibility and the analysis of the dynamical changes. The scope of our model combined with its visual simulation capabilities, constitutes a superior dynamical tool capable of better explicating trends in addiction and may be useful in evaluating possible treatments and an aid in applying particular treatments relative to the state of the addict at a given time and under varying circumstances.