Modeling HIV transmission among persons who inject drugs (PWID) at the "End of the HIV Epidemic" and during the COVID-19 pandemic

Abstract

Background: We explore injecting risk and HIV incidence among PWID in New York City (NYC), from 2012 to 2019, when incidence was extremely low, <0.1/100 person-years at risk, and during disruption of prevention services due to the COVID-19 pandemic.

Methods: We developed an Agent-Based model (ABM) to simulate sharing injecting equipment and measure HIV incidence in NYC. The model was adapted from a previous ABM model developed to compare HIV transmission with "high" versus "low" dead space syringes. Data for applying the model to NYC during the period of very low HIV incidence was taken from the "Risk Factors" study, a long-running study of participants entering substance use treatment in NYC. Injecting risk behavior had not been eliminated in this population, with approximately 15 % reported recent syringe sharing. Data for possible transmission during COVID-19 disruption was taken from previous HIV outbreaks and early studies of the pandemic in NYC.

Results: The modeled incidence rates fell within the 95 % confidence bounds of all of the empirically observed incidence rates, without any additional calibration of the model. Potential COVID-19 disruptions increased the probability of an outbreak from 0.03 to 0.25.

Conclusions: The primary factors in the very low HIV incidence were the extremely small numbers of PWID likely to transmit HIV and that most sharing occurs within small, relatively stable, mostly seroconcordant groups. Containing an HIV outbreak among PWID during a continuing pandemic would be quite difficult. Pre-pandemic levels of HIV prevention services should be restored as quickly as feasible.

Keywords: Agent Based Modeling (ABM); COVID-19; Covid; New York city; Person who inject drugs (PWID); Risk factors study.

Fig. 1

HIV prevalence trajectories for 200 simulated communities of 10,000 PWIDs with the baseline parameter values.