Estimating naloxone need in the USA across fentanyl, heroin, and prescription opioid epidemics: a modelling study

Abstract

Background: The US overdose crisis is driven by fentanyl, heroin, and prescription opioids. One evidence-based policy response has been to broaden naloxone distribution, but how much naloxone a community would need to reduce the incidence of fatal overdose is unclear. We aimed to estimate state-level US naloxone need in 2017 across three main naloxone access points (community-based programmes, provider prescription, and pharmacy-initiated distribution) and by dominant opioid epidemic type (fentanyl, heroin, and prescription opioid).

Methods: In this modelling study, we developed, parameterised, and applied a mechanistic model of risk of opioid overdose and used it to estimate the expected reduction in opioid overdose mortality after deployment of a given number of two-dose naloxone kits. We performed a literature review and used a modified-Delphi panel to inform parameter definitions. We refined an established model of the population at risk of overdose by incorporating changes in the toxicity of the illicit drug supply and in the naloxone access point, then calibrated the model to 2017 using data obtained from proprietary data sources, state health departments, and national surveys for 12 US states that were representative of each epidemic type. We used counterfactual modelling to project the effect of increased naloxone distribution on the estimated number of opioid overdose deaths averted with naloxone and the number of naloxone kits needed to be available for at least 80% of witnessed opioid overdoses, by US state and access point.

Findings: Need for naloxone differed by epidemic type, with fentanyl epidemics having the consistently highest probability of naloxone use during witnessed overdose events (range 58-76% across the three modelled states in this category) and prescription opioid-dominated epidemics having the lowest (range 0-20%). Overall, in 2017, community-based and pharmacy-initiated naloxone access points had higher probability of naloxone use in witnessed overdose and higher numbers of deaths averted per 100 000 people in state-specific results with these two access points than with provider-prescribed access only. To achieve a target of naloxone use in 80% of witnessed overdoses, need varied from no additional kits (estimated as sufficient) to 1270 kits needed per 100 000 population across the 12 modelled states annually. In 2017, only Arizona had sufficient kits to meet this target.

Interpretation: Opioid epidemic type and how naloxone is accessed have large effects on the number of naloxone kits that need to be distributed, the probability of naloxone use, and the number of deaths due to overdose averted. The extent of naloxone distribution, especially through community-based programmes and pharmacy-initiated access points, warrants substantial expansion in nearly every US state.

Funding: National Institute of Health, National Institute on Drug Abuse.

Figure 1:. Simplified model overview of fatal and non-fatal opioid overdose with naloxone use by US state

Diagram indicates where data are captured in the model (non-blue boxes) with other latent branches suppressed. The at-risk population is stratified by risk type (N₁ to N_k), which are combined together to produce an effective population size of individuals at risk of an opioid overdose. A per-month rate of opioid overdose is dependent on epidemic type and underlying circulation of fentanyl and its derivatives (indicted by the epidemic risk box). Each estimated opioid overdose is then entered into a decision tree to determine the probability of the opioid overdose resulting in death, whether there is a reported use of naloxone, or neither. Whether an opioid overdose is fatal is dependent on whether it is witnessed, whether emergency medical services were called, whether naloxone is used, and the underlying risk of death for an intervened overdose. The probability of naloxone use is dependent on whether an overdose is witnessed, naloxone is available and used by a witness, and whether its use is reported.

Figure 2:. Map of opioid epidemic types and representative states selected for modelling across the USA, 2017

State abbreviations are shown in place of full names.

Figure 3:. Model-derived expected probability of naloxone use in the event of a witnessed opioid overdose and deaths averted for 0 to 1000 distributed naloxone two-dose kits (through community-based access points) per 100 000 total population per year for three modelled states within each of the four dominant opioid epidemic types

Datapoints are observed volumes of distributions of naloxone kits in 2017, with lines showing estimated probabilities of naloxone use and deaths due to opioid overdose averted. Shaded areas show 95% credible intervals. State abbreviations are shown in place of full names.

Figure 4:. Model-derived expected probability of naloxone use in the event of a witnessed opioid overdose with respect to number of naloxone kits distributed, by naloxone source, per year, for 12 US states used in modelling

Datapoints are observed volumes of naloxone kits distributed in 2017, with lines showing estimated probability of naloxone use. 95% credible intervals are not shown here for clarity.