Examining buprenorphine diversion through a harm reduction lens: an agent-based modeling study.

BACKGROUND: Recent policies have lessened restrictions around prescribing buprenorphine-naloxone (buprenorphine) for the treatment of opioid use disorder (OUD). The primary concern expressed by critics of these policies is the potential for buprenorphine diversion. However, the population-level effects of increased buprenorphine diversion are unclear. If replacing the use of heroin or fentanyl, use of diverted buprenorphine could be protective. METHODS: Our study aim was to estimate the impact of buprenorphine diversion on opioid overdose using an agent-based model calibrated to North Carolina. We simulated the progression of opioid misuse and opioid-related outcomes over a 5-year period. Our status quo scenario assumed that 50% of those prescribed buprenorphine diverted at least one dose per week to other individuals with OUD and 10% of individuals with OUD used diverted buprenorphine at least once per week. A controlled prescription only scenario assumed that no buprenorphine would be diverted, while an increased diversion scenario assumed that 95% of those prescribed buprenorphine diverted and 50% of individuals with OUD used diverted buprenorphine. We assumed that use of diverted buprenorphine replaced the use of other opioids for that day. Sensitivity analyses increased the risk of overdose when using diverted buprenorphine, increased the frequency of diverted buprenorphine use, and simulated use of diverted buprenorphine by opioid-naïve individuals. Scenarios were compared on opioid overdose-related outcomes over the 5-year period. RESULTS: Our status quo scenario predicted 10,658 (credible interval [CI]: 9699-11,679) fatal opioid overdoses. A scenario simulating controlled prescription only of buprenorphine (i.e., no diversion) resulted in 10,741 (9895-11,650) fatal opioid overdoses versus 10,301 (9439-11,244) within a scenario simulating increased diversion. Compared to the status quo, the controlled prescription only scenario resulted in a similar number of fatal overdoses, while the scenario with increased diversion of buprenorphine resulted in 357 (3.35%) fewer fatal overdoses. Even when increasing overdose risk while using diverted buprenorphine and incorporating use by opioid naïve individuals, increased diversion did not increase overdoses compared to a scenario with no buprenorphine diversion. CONCLUSIONS: A similar number of opioid overdoses occurred under modeling conditions with increased rates of buprenorphine diversion among persons with OUD, with non-statistical trends toward lower opioid overdoses. These results support existing calls for low- to no-barrier access to buprenorphine for persons with OUD.

Disparities in years of potential life lost to Drug-involved overdose deaths in South Carolina.

INTRODUCTION: South Carolina has experienced a surge in fatal overdoses, primarily fueled by opioid-involved overdose deaths. This work aims to quantify the burden of premature mortality due to fatal opioid-involved overdoses in South Carolina while documenting the contribution of synthetic opioids to excess mortality, examining substance specific geographic and demographic patterns of mortality burden, and measuring the effect of fatal opioid and synthetic opioid-involved overdoses on average lifespan. METHODS: We obtained death certificates for fatalities involving opioids, cocaine, benzodiazepines, and psychostimulants (N = 3,726) in South Carolina from 2014 to 2018. Years of Potential Life Lost (YPLL) was used to examine gender, racial, and geographic disparities in mortality burden. We assessed the contribution of synthetic opioid poisoning to the overall opioid mortality burden over time and calculated the effect of fatal opioid and synthetic opioid-involved overdoses on average lifespan. RESULTS: From 2014 to 2018, opioid-involved overdose deaths resulted in 124,451 YPLL. The average age of fatal male and female opioid-involved overdoses decreased 2.8 and 3.9 years, respectively. Synthetic opioids increasingly contributed to opioid YPLL, accounting for 22% in 2014 to 64% in 2018. Mortality burden was not shared equally between races, sexes, or rural/urban counties. The largest change occurred in black male synthetic opioid-involved deaths (2234%). Rural counties comprised 44-48% of the population adjusted YPLL despite containing 34% of the population. CONCLUSION: Opioid-involved overdoses account for a critical cause of mortality in South Carolina, demonstrate significant impact on YPLL and highlight mortality burden disparities in gender, race, and rural/urban settings.

Small area estimation of county-level U.S. HIV-prevalent cases.

PURPOSE: Recent trends of HIV in the United States have indicated that the epidemic is no longer an urban issue; however, HIV data in rural settings are incomplete. Our objective was to estimate HIV prevalence in U.S. counties using small area estimation techniques (SAE) to better assess the burden of HIV nationally. METHODS: We performed SAE modeling to predict the reported number of HIV cases across the continental United States, including unreported counties using source data from the CDC National HIV Surveillance System. Our model borrowed strength from auxiliary HIV risk-indicator data, including geospatial information. Cross-validation was conducted to identify and assess the precision of the estimates. RESULTS: Our findings showed that most of the 677 unreported counties had low HIV prevalence levels (quintiles 1-2). Estimates in the South had high levels of HIV (quintile 4-5). Cross-validation techniques indicated good precision of the estimates, as 42% of the residuals were within ±10 HIV cases. CONCLUSIONS: HIV was highest along the coastlines and in the U.S. South. Cross-validation techniques provided sufficient support of our model. Our study provides a more complete picture of the burden of HIV across the United States and identifies communities in need of future targeted interventions.