A team of scientists from Massachusetts General Hospital (MGH) has developed a data-driven simulation model designed to help policymakers better understand and address the nation’s rampant opioid crisis. In a study from the journal PNAS, The researchers report that the model, known as SOURCE (Simulating Opioid Use, Response, Consequences, and Effects), provides the most detailed model to date of the crisis by capturing how the stages of drug prescribing and illicit opioid use interrelate, from initiation and treatment of addiction to relapse and dose-related deaths. Excess, may have developed over time.
“The opioid crisis is so complex that it requires a dynamic simulation tool capable of generating reliable data and a comprehensive view of this major public health challenge,” says lead author Mohamed Jalali, PhD, of the MGH Institute for Technology Assessment. “SOURCE provides a dynamic understanding of the course of the opioid crisis that can serve as a framework for planning future scenarios and inform public policy planning.”
Opioid overdoses have been responsible for more than half a million deaths in the United States over the past 21 years. Opioid-related deaths have risen sharply since 2013, claiming nearly 70,000 lives in 2020 alone, in large part due to the illicit spread of fentanyl, a strong opioid often mixed with heroin with a deadly effect. Millions of people suffer from opioid use disorders, with serious health, social, and economic consequences for the country. In 2017, the National Academies of Sciences, Engineering, and Medicine called for the development of a quantitative system model to help understand the crisis and guide policy analysis and decision-making. In response, a team of researchers from MGH and the US Food and Drug Administration (FDA) developed SOURCE.
SOURCE uses national opioid use data from 1999 to 2020 to track stages of opioid use and abuse, including initiation of use, treatment, relapse, and death by overdose. “Unlike other national models of the crisis, SOURCE reiterates how risks of opioid use have evolved over time in response to diverse behavioral and other factors, and how they may change in the future, providing a platform for viewing and analyzing potential policy impacts and solutions,” says co-author Tse Yang. Lim, Ph.D., from the Massachusetts Institute of Technology (MIT).
Among the factors driving these changes are social influence—that is, the prevalence of drug-use behaviors through social exposure—and risk perception, and fear of a perceived risk of death by overdose that can discourage initiation of drug use. The source also identified the effect of the increased distribution of reversible overdose naloxone, as well as the prevalence of the potentially fatal synthetic fentanyl, on overdose mortality rates. Overall, SOURCE predicts that deaths from opioid overdose will increase over the next few years before declining as opioid use disorder declines.
Using SOURCE, researchers study potential strategies for dealing with the opioid crisis as part of an ongoing modeling effort, while continuing to refine the model to reflect the ever-evolving nature of the crisis. “Despite the projected decline, opioid-related deaths over the next 10 years will still exceed half a million people,” notes co-author Erin Stringfellow, PhD, with MGH. “Fentanyl poisoning by the unregulated drug supply will continue to be a serious problem, which is why leaders across the country must work as hard as possible to keep people who use drugs safe.”
Jalali is an assistant professor at Harvard Medical School. Tse Yang Lim recently graduated with a Ph.D. from the Massachusetts Institute of Technology. Stringfellow is a postdoctoral research associate at the MGH Institute for Technology Assessment. Co-authors include Keith Humphreys, professor and director of the Division of Mental Health Policy at Stanford University, and several Food and Drug Administration researchers.
The study was supported by the US Food and Drug Administration.
Material provided by Massachusetts General Hospital. Note: Content can be modified according to style and length.
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