This research is to investigate a prototype of a model framework for the use and abuse of alcohol. The model is intended to provide a tool for the assessment for interventions that are meant to minimize alcohol-related acute outcomes (intentional and unintentional injuries/death) without causing a financial or social burden and without imposing interventions that are ultimately ineffective (or even simply not cost effective). Our framework is ecological (individual agents and interactions are represented), stochastic (neither individual behavior nor consequences of interventions are certain) and very flexible. We have developed a space dependent stochastic digraph model of alcohol use and abuse. The intent is to study potential interventions and investigate their effectiveness at reducing the overall prevalence of acute outcomes. Current interventions focus on one outcome at a time rather than simultaneously considering all outcomes. It is clear that a similar model structure of social networks can be applied to terrorist networks, to computer networks, to syndromic surveillance, and to other applications that are characterized by requiring interventions for the simultaneous suppression of acute outcomes.