Heroin type, injecting behavior, and HIV transmission. A simulation model of HIV incidence and prevalence

Abstract

Background and aims: Using mathematical modeling to illustrate and predict how different heroin source-forms: "black tar" (BTH) and powder heroin (PH) can affect HIV transmission in the context of contrasting injecting practices. By quantifying HIV risk by these two heroin source-types we show how each affects the incidence and prevalence of HIV over time. From 1997 to 2010 PH reaching the United States was manufactured overwhelmingly by Colombian suppliers and distributed in the eastern states of the United States. Recently Mexican cartels that supply the western U.S. states have started to produce PH too, replacing Colombian distribution to the east. This raises the possibility that BTH in the western U.S. may be replaced by PH in the future.

Design: We used an agent-based model to evaluate the impact of use of different heroin formulations in high- and low-risk populations of persons who inject drugs (PWID) who use different types of syringes (high vs. low dead space) and injecting practices. We obtained model parameters from peer-reviewed publications and ethnographic research.

Results: Heating of BTH, additional syringe rinsing, and subcutaneous injection can substantially decrease the risk of HIV transmission. Simulation analysis shows that HIV transmission risk may be strongly affected by the type of heroin used. We reproduced historic differences in HIV prevalence and incidence. The protective effect of BTH is much stronger in high-risk compared with low-risk populations. Simulation of future outbreaks show that when PH replaces BTH we expect a long-term overall increase in HIV prevalence. In a population of PWID with mixed low- and high-risk clusters we find that local HIV outbreaks can occur even when the overall prevalence and incidence are low. The results are dependent on evidence-supported assumptions.

Conclusions: The results support harm-reduction measures focused on a reduction in syringe sharing and promoting protective measures of syringe rinsing and drug solution heating.

Fig 1. HIV prevalence and incidence in year 2000 vs. percentage of black tar heroin used in several major U.S. cities.

Blue cities correspond to eastern US, green cities to western US. Prevalence is depicted with circles and city names are centered around it. Squares denote 1996 incidence per 500 person-years in cities where it was reported in Holmberg [9]. Prevalence and incidence in the same city are liked with a segment. Horizontal line represents 5% prevalence and incidence per 500 person years. Incidence was scaled to 500 person-years to get numeric values within the same numeric range as the prevalence. HIV prevalence and incidence from Tempalski et al. [8]; prevalence of black tar in the cities as reported in Ciccarone and Bourgois [6], from Domestic Monitoring Program 1991–1993. Drug Enforcement Administration, U.S. Department of Justice.

Fig 2. A depiction of factors affecting HIV transmission through sharing syringes and the role of BTH/PH in the probability of transmission.

BTH/PH factors are overlaid with the oval.

Fig 3. A screenshot copy of the simulation model that describes the spread of HIV among PWID.

Each injecting network can be high or low risk in terms of frequency of syringe sharing (large pink or yellow squares) and using HDS or LDS syringes (small pink or yellow squares inside the large squares).

Fig 4. Simulated HIV prevalence in eastern cities (5% BTH) and western cities (95% BTH) for different percent (10%, 20%, 50%, 80%) of high-risk networks.

Bars denote 95% range of simulated prevalences.

Fig 5. An example of high variability of 100 possible HIV trajectories when a community of PWID with 80% of high-risk networks switches to PH.

The mean trajectory is shown in a thick solid black line. Variability of trajectories around the mean is high with a few trajectories (8 in this example) reaching a prevalence of over 25%. When HIV reaches a large high-risk cluster, the trajectory shows a fast increase in prevalence.