Margaret Brandeau may carry a business card that reads Professor of Management Science and Engineering, but her expertise is in using complex systems models to solve challenges in public health policy.
For instance, she recently created a sophisticated computer model of the national opioid crisis, which led her to the stark — and surprising — conclusion that it may take a short-term rise in deaths to ultimately reduce them.
She didn’t come to that conclusion lightly, but made no less than 10 models of drug-user behaviors to analyze interventions. Nonetheless, each model led her to the same basic conclusions. First, policies are needed that lead to cutbacks in the number of prescriptions of opioids for pain management. Second, fewer prescriptions of opioids for pain management will cause some individuals to turn to more-deadly heroin. Third, because of this unintended consequence, it is essential to also scale up treatment for opioid-addicted individuals. But her fourth finding was the most sobering of all: No one of these policies will suffice; they must all be combined if we are to curb the opioid epidemic — and the epidemic is not likely to abate significantly anytime soon.
Mathematical modeling is an art, Brandeau says, but it’s a powerful art that is only going to grow in influence. Her advice for those looking to solve big problems — from reducing sodium intake to battling the return of measles — is to start out simple. Know what question you want to answer and create a model that captures just the most salient elements of the problem. Things will flow from there.
Join host Russ Altman and mathematical modeling expert Margaret Brandeau for a deep look at the the many ways algorithms are changing our understanding of and approaches to the challenges of public health.