The “overdose epidemic” that so many Americans are talking about isn’t really a single epidemic. It’s actually several of them, something we began exploring when we graphed the yearly counts of overdose deaths for the last 40 years.
It turns out that, when totaled, these sub-epidemics trace a nearly perfect exponential growth curve. For four decades, overdose deaths have been growing, doubling about every eight years.
To learn what was fueling that growth, we looked at the growth curves for specific drugs, including prescription medications, heroin, fentanyl, cocaine, methamphetamine, and methadone. As we and colleagues describe in an article in Thursday’s issue of Science, none of these independently explain the smooth exponential growth. When we looked at the age groups most affected, there were no clear patterns. Lastly, when we mapped the deaths over space and time, hot spots were scattered across the United States. (You can see animations of these analyses here and here.)
These findings represent a paradox: In the aggregate, overdose deaths have been growing at a remarkably smooth and predictable rate, but the underlying patterns of overdose deaths from specific drugs are heterogeneous and unpredictable. It’s almost as if there is an Adam Smith-like hidden hand at play. Individual drugs come and go, demographic risk groups vary, policies are implemented and enforced, while the overall overdose death curve grows inexorably.
We think that deep forces are holding the multiple sub-epidemics together into a smooth exponential trajectory. Some of these may be economic and technological “push” factors, such as increasingly efficient processes for making drugs, improved communications aiding faster and more targeted delivery of drugs, higher drug purity, and lower prices. At the same time, there are probably strong “pull” factors at work, especially widening economic disparities, loss of a sense of purpose, and dissolution of communities.
How can these factors work together to produce a predictably growing curve? It may be that the overdose curve has some parallels (figuratively and literally) to Moore’s Law, which explains the smooth exponential growth of computing power. The drivers of Moore’s Law are thought to be a combination of techno-push and socio-pull, just as we hypothesize for the overdose epidemic.
New policies to reign in opioid overprescribing and make drug treatment programs more widely available and accessible are urgently needed to deal with the immediate crisis. But if the current epidemic of opioid overdoses is a manifestation of long-term ongoing processes, then policies aimed mainly at opioid control and treatment may not be enough to permanently bend the overdose death curve downward in the future.
Without also focusing on social determinants of economic disparity, reinstating a sense of purpose, and rebuilding communities, history indicates that the growth curve for overdose deaths will look increasingly grim.
Hawre Jalal, M.D., is an assistant professor of health policy in the Department of Health Policy and Management and a researcher in the Public Health Dynamic Laboratory, both at the University of Pittsburgh. Donald S. Burke, M.D., is dean of the University of Pittsburgh’s Graduate School of Public Health, associate vice chancellor for global health, and professor of global health and health science and policy.