Optimizing naloxone kit distribution to prevent opioid deaths

A new study from University of Toronto Engineering researchers points to practical strategies to prevent deaths from opioid poisoning by optimizing the distribution of naloxone kits. 

In a paper published in the Canadian Medical Association Journal, Professor Timothy Chan and his team showed that placing naloxone kits in transit stations could help ensure that these potentially life-saving tools are present where they are most needed. 

The opioid epidemic is a profound public health crisis, and it may not be obvious at first how engineering researchers can help. 

In collaboration with doctors and other medical professionals, we can apply techniques from our field - operations research and mathematical optimization - to develop new solutions." 

Professor Timothy Chan, University of Toronto Engineering

Chan and his team have previously collaborated with medical researchers to look at the distribution of automated external defibrillators, or AEDs, in urban areas. 

Using computer models, they were able to analyze spatial data on past cardiac arrests. They could then optimize AED placement to maximize the number that would be accessible from those locations. 

"Naloxone kits are somewhat analogous to AEDs in that they can reverse the effects of an opioid poisoning event, but only if they are available quickly, which means they need to be in the right locations," says Chan. 

In their latest work, Chan and his team collaborated with emergency physicians and researchers, including Dr. Brian Grunau and Dr. Jim Christenson at St. Paul's Hospital in Vancouver, B.C. 

They began by analyzing data from more than 14,000 opioid poisoning incidents that were recorded by BC Emergency Health Services between December 2014 and August 2020 in Metro Vancouver. 

They then built a computer model that could simulate how many of those incidents would have taken place within a 3-minute walk from a naloxone kit, based on several distribution strategies. 

"The first strategy was to look at locations that already have free naloxone distribution programs, such as pharmacies and health clinics," says Ben Leung, lead author on the paper. 

Leung built the model while working as a PhD student in Chan's lab; he is now a research fellow at the Duke Clinical Research Institute in Durham, N.C. 

"Our second strategy was to look at chain restaurants or similar businesses. And our third strategy was to look at transit, including both SkyTrain stations and bus stops." 

Leung's analysis showed that more than a third of past opioid poisonings took place within about 150 metres of locations where naloxone is being distributed. 

Switching to a strategy focusing on chain restaurants and similar businesses did not noticeably improve coverage: depending on how many different chains were included and how many kits distributed, coverage only reached a maximum of about 20%. 

But the third strategy of leveraging transit stops was the most promising. 

"Right now, there are about 650 locations with take-home naloxone distribution programs," says Leung. 

"What we found was that if we used transit stops instead, we could get the same amount of coverage with only about 60 kits. If we increase the number of kits to 1000, we could cover more than half of the opioid poisonings that we analyzed." 

Leung points out that different strategies can be used in combination to further improve coverage. He hopes that the insights that have been generated by the new study will help public health officials make better strategic decisions in the future. 

"There have been a few small pilot programs putting naloxone kits in public locations, but to our knowledge, this is the first time anyone has analyzed what large-scale distribution would look like using mathematical optimization techniques," he says. 

"By presenting these results, I think we can make a strong case for doing that." 

Chan hopes that these kinds of studies can seed broader changes as well. 

"For example, in Japan, AEDs are widely available at vending machines," he says. 

"That has led to an association: if someone is having a cardiac arrest, you automatically know to go to the nearest vending machine for an AED. 

"If we can do something similar for naloxone, it could help bystanders feel more empowered to step in when they are needed to save lives."