There are computer models that help gauge the likely outcomes of any number of decisions – whether it’s the Federal Reserve raising interest rates, a new climate policy, or even what you choose to eat for breakfast.
That hasn't been the case for the opioid epidemic. Now, researchers at Stanford University have developed a computer model of the epidemic that they hope can help point policymakers toward effective strategies.
But by running the model, the researchers uncovered some discouraging news.
“Looking out 10 years, it was disheartening to see that through all the combinations of interventions we tested it was still going to take a lot more to see a really big dip in the deaths caused by this epidemic,” said Allison Pitt, a Ph.D. candidate in the department of management science and engineering at Stanford University and lead author of the new study.
The study modeled what would happen if doctors prescribed 25 percent fewer opioid drugs, drug companies reformulated the pills to make them less addictive, and the government invested in drug-assisted addiction treatment and increased access to naloxone, the overdose reversing medication.
“We were seeing a roughly 10 percent reduction in the expected death toll,” with all of those actions, Pitt said.
The relatively small reduction in the death toll shown by the model shows that there is a lot of work to be done before the epidemic is under control, Pitt said. Still, she believes that the model can be helpful in that work.