Effects of naloxone distribution to likely bystanders: Results of an agent based model
Authored by Christopher Keane, James E Egan, Mary Hawk
Date Published: 2018
DOI: 10.1016/j.drugpo.2018.02.008
Sponsors:
No sponsors listed
Platforms:
NetLogo
Model Documentation:
Other Narrative
Model Code URLs:
https://ars-els-cdn-com.ezproxy1.lib.asu.edu/content/image/1-s2.0-S0955395918300434-mmc1.docx
Abstract
Background: Opioid overdose deaths in the US rose dramatically in the
past 16 years, creating an urgent national health crisis with no signs
of immediate relief. In 2017, the President of the US officially
declared the opioid epidemic to be a national emergency and called for
additional resources to respond to the crisis. Distributing naloxone to
community laypersons and people at high risk for opioid overdose can
prevent overdose death, but optimal distribution methods have not yet
been pinpointed.
Methods: We conducted a sequential exploratory mixed methods design
using qualitative data to inform an agent-based model to improve
understanding of effective community-based naloxone distribution to
laypersons to reverse opioid overdose. The individuals in the model were
endowed with cognitive and behavioral variables and accessed naloxone
via community sites such as pharmacies, hospitals, and urgent-care
centers. We compared overdose deaths over a simulated 6-month period
while varying the number of distribution sites (0, 1, and 10) and number
of kits given to individuals per visit (1 versus 10). Specifically, we
ran thirty simulations for each of thirteen distribution models and
report average overdose deaths for each. The baseline comparator was no
naloxone distribution. Our simulations explored the effects of
distribution through syringe exchange sites with and without secondary
distribution, which refers to distribution of naloxone kits by
laypersons within their social networks and enables ten additional
laypersons to administer naloxone to reverse opioid overdose.
Results: Our baseline model with no naloxone distribution predicted
there would be 167.9 deaths in a six month period. A single distribution
site, even with 10 kits picked up per visit, decreased overdose deaths
by only 8.3\% relative to baseline. However, adding secondary
distribution through social networks to a single site resulted in 42.5\%
fewer overdose deaths relative to baseline. That is slightly higher than
the 39.9\% decrease associated with a tenfold increase in the number of
sites, all distributing ten kits but with no secondary distribution.
This suggests that, as long as multiple kits are picked up per visit,
adding secondary distribution is at least as effective as increasing
sites from one to ten. Combining the addition of secondary distribution
with an increase in sites from one to ten resulted in a 61.1\% drop in
deaths relative to the baseline. Adding distribution through a syringe
exchange site resulted in a drop of approximately 65\% of deaths
relative to baseline. In fact, when enabling distribution through a
clean-syringe site, the secondary distribution through networks
contributed no additional drops in deaths.
Conclusion: Community-based naloxone distribution to reverse opioid
overdose may significantly reduce deaths. Optimal distribution methods
may include secondary distribution so that the person who picks up
naloxone kits can enable others in the community to administer naloxone,
as well as targeting naloxone distribution to sites where individuals at
high-risk for opioid overdose death are likely to visit, such as
syringe-exchange programs. This study design, which paired exploratory
qualitative data with agent-based modeling, can be used in other
settings seeking to implement and improve naloxone distribution
programs.
Tags
Attitudes
Personal Networks
intervention
Strategies
United-states
San-francisco
Programs
Harm reduction
Agent-based
modeling
Opioid overdose
Naloxone distribution
Take-home naloxone
Opioid overdose prevention
Injection-drug users
Distribution programs
Intranasal naloxone
Heroin
overdose
Deaths
Heroin overdose