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Naloxone

Naloxone is a highly effective treatment of opiate drug overdoses, nearing 100% effectiveness for prevention of an overdose death. Naloxone is administered after someone has overdosed, effectively knocking opiates off of the receptors in the brain and reversing the overdose effects. Overdose is a major cause of morbidity and mortality among opiate drug users. In the European Union, overdose is one of the leading causes of death among young people and among people who inject drugs, exceeding deaths from AIDS-related illnesses.1 PSI often integrates naloxone education and distribution into its HIV prevention work with people who inject drugs.

Unit of intervention1 ampoule of naloxone

Contents2mg of Naloxone

Target populationPeople who inject drugs

For more information about how PSI is increasing access to Naloxone to improve health and save lives, visit our website at:
http://www.psi.org/program/needle-and-syringe-distribution-intervention/

Model Overview

PSI’s naloxone impact model estimates the number of DALYs averted and deaths averted per unit of naloxone.

The model is designed with two core components: a baseline scenario in which the PSI naloxone distribution program is NOT present, and an intervention scenario in which naloxone coverage for all heroin overdoses is universal.

The model then subtracts the intervention scenario from the baseline scenario to estimate how many deaths and DALYs would be averted under the intervention scenario.

Finally, the model estimates the per unit impact of naloxone under the intervention scenario. This is done by dividing the death and DALY burden that would be averted under the intervention scenario by the number of units of naloxone that would be needed to achieve universal coverage. This allows us to move from a hypothetical model of universal coverage to a model which estimates the impact of a single unit of naloxone.

Model Outputs (impact metrics)

Estimates of DALYs averted, deaths averted, CYPs provided, and unintended pregnancies averted represent the projected health impact of the intervention. It is projected because it has not been directly measured.

Examples based on distribution of naloxone in Tajikistan Statement of modeled results, examples:

In 2015, an estimated 242 deaths and 13,644 DALYs would be averted if 10,000 units of naloxone were distributed in Tajikistan.

Model Details

Baseline scenario
Step 1: In the baseline scenario, when no PSI naloxone distribution program is present, the model runs a one-year projection to estimate the number of IDU overdoses in a given year and the proportion of those overdoses that would receive naloxone assuming no PSI distribution. This is done by taking into account several parameters, including:

Output:
Probability of death due to overdose among IDUs assuming baseline coverage of naloxone (i.e. no PSI intervention).

Step 2: The model uses an average age at death per heroin overdose, based on peer-reviewed literature, to estimate the number of years of life lost per IDU death based on an age-specific life expectancy taken from the 2010 Global Burden of Disease study (GBD 2010).

Output:
Number of years of life lost per death due to heroin overdose

Step 3: Finally, the number of years of life lost per IDU death is multiplied by the number of new IDU deaths over the course of one year to estimate the number of years lost due to death from heroin overdose in a given country.

Output:
Number of years of life lost due to heroin overdose assuming baseline coverage of naloxone

Intervention scenario
Step 1: In the intervention scenario, the model estimates the probability of death due to heroin overdose assuming universal coverage of naloxone. This is done by taking into account several parameters, including:

(Notice the difference in the last bullet here as compared to the last bullet under Step 1 of the baseline scenario.)

Output:
Probability of death due to heroin overdose assuming universal coverage of naloxone

Step 2: The model then subtracts the probability of death due to heroin overdose under the intervention scenario from the probability of death due to heroin overdose under the baseline scenario. This results in an estimate of the net reduction in the probability of death due to heroin overdose under an intervention scenario.

Output:
Net reduction in the probability of death due to heroin overdose assuming universal coverage of naloxone

Step 3: The model estimates the net reduction in the probability of death due to heroin overdose per unit of naloxone. This is the ‘deaths averted coefficient’ and represents the number of deaths each unit of naloxone is estimated to avert. This coefficient is calculated by first estimating the number of units of naloxone needed to achieve universal coverage, assuming 10% wastage of naloxone in the supply chain, and dividing that figure by the net reduction in the probability of death due to heroin overdose under a universal coverage scenario (the step 2 output).

Output:
Deaths averted coefficient (i.e. number of deaths averted per ampoule of naloxone)

Step 4: Finally, the model translates the deaths averted coefficient into a DALYs averted coefficient by multiplying the death averted coefficient by the number of years of life lost due per death due to heroin overdose from GBD 2010.

Output:
DALYs averted coefficient (i.e. number of years of life saved per ampoule of naloxone)