Modeling approaches, challenges, and preliminary results for the opioid and heroin co-epidemic crisis

The U.S. is in the grips of a devastating opioid and heroin co-epidemic affecting nearly all socio-economic populations at great human (~7,800 new users/day) and financial ($78.5 billion/year) costs but with no obvious solution. We describe recent work and challenges to develop, integrate, and use several analytic multi-scale simulation models of these epidemics to develop insight into the epidemic's complex underlying dynamics, generate causal hypotheses, and inform effective policy interventions. We developed preliminary agent-based, differential equation, network spread, and cellular automata models that reasonably replicate at multiple scales the past 17 years of this epidemic's growth and spread at town, county, state, and national levels. Results suggest that some current approaches are unlikely to be very effective, some in fact may worsen the epidemic, and ultimately only certain combinations and sequences of policies are likely to have value, with important implications on both model architecture and policy optimization.