Faculty Bibliography

INTRODUCTION/BACKGROUND:Methadone and buprenorphine are effective treatment for opioid use disorder (OUD), yet they are vastly under-utilized across US hospitals. To inform a national trial assessing the effectiveness of implementation strategies to increase adoption of an inpatient hospital-based opioid treatment (HBOT) model (NCT04921787), we explored barriers and facilitators to expanding medication for opioid use disorder (MOUD) within community hospitals across the United States. METHODS:From November 2021 to March 2022, we used purposeful and snowball sampling to identify and interview participants involved in inpatient care of patients with OUD from twelve community hospitals. We conducted semi-structured interviews on providers' experiences and perspectives on current treatment approaches as well as potential influences on MOUD expansion in their hospitals. We used thematic analysis to identify key barriers and facilitators that could impact implementation of an HBOT model, and organized these findings based on the Consolidated Framework for Implementation Research (CFIR). RESULTS:From qualitative interviews with 57 participants (30 physicians, 7 pharmacists, 6 nurses, and 14 professionals involved in the care of patients with OUD), we identified key barriers and facilitators mapped to CFIR's internal and outer settings. The most salient inner setting domains included tension for change and relative priority, compatibility, available resources, organizational culture, access to knowledge and information, relational connections and communications, and information technology infrastructure. Outer setting domains included policies and laws, financing, and partnerships and connections. CONCLUSIONS:Identifying potential barriers and facilitators can inform hospital-specific strategies to support implementation of HBOT. Implementation strategies that address barriers such as staff availability, knowledge, and attitudes may support increased HBOT adoption. On a broader scale, national policy changes such as increased financing and public reporting of quality metrics would address other barriers we identified and may also encourage hospitals to adopt HBOT models.

BACKGROUND:Offering medications for opioid use disorder (MOUD) in carceral settings significantly reduces overdose. However, it is unknown to what extent individuals in jails continue MOUD once they leave incarceration. We aimed to assess the relationship between in-jail MOUD and MOUD continuity in the month following release. METHODS:We conducted a retrospective cohort study of linked NYC jail-based electronic health records and community Medicaid OUD treatment claims for individuals with OUD discharged from jail between 2011 and 2017. We compared receipt of MOUD within 30 days of release, among those with and without MOUD at release from jail. We tested for effect modification based on MOUD receipt prior to incarceration and assessed factors associated with treatment discontinuation. RESULTS:Of 28,298 eligible incarcerations, 52.8 % received MOUD at release. 30 % of incarcerations with MOUD at release received community-based MOUD within 30 days, compared to 7 % of incarcerations without MOUD (Risk Ratio: 2.62 (2.44-2.82)). Most (69 %) with MOUD claims prior to incarceration who received in-jail MOUD continued treatment in the community, compared to 9 % of those without prior MOUD. Those who received methadone (vs. buprenorphine), were younger, Non-Hispanic Black and with no history of MOUD were less likely to continue MOUD following release. CONCLUSIONS:MOUD maintenance in jail is strongly associated with MOUD continuity upon release. Still, findings highlight a gap in treatment continuity upon-reentry, especially among those who initiate MOUD in jail. In the wake of worsening overdose deaths and troubling disparities, improving MOUD continuity among this population remains an urgent priority.

HIV-related stigma is a well-documented barrier to HIV testing in South Africa, and may be particularly likely to create reluctance to test among South African men, who have reported feeling blamed for HIV by their partners and communities. The present study presents a novel expanded social network recruitment to HIV testing (E-SNRHT) intervention explicitly designed to reduce stigma as a barrier to testing by asking people to recruit anyone they know to testing, thus allowing them to avoid the potential for increased stigma and/or blame associated with direct risk partner recruitment, and helping to normalize openly discussing HIV among social networks. We examined baseline and 6-10-week follow-up data from a 2022-2023 randomized trial in KwaZulu-Natal, South Africa that recruited 110 individuals who had been newly diagnosed with HIV and randomly assigned them to recruit people to HIV testing either via the E-SNRHT intervention or via risk network recruitment. Participants in the E-SNRHT intervention reported significant decreases in anticipated and enacted HIV-related stigma between baseline and follow-up; and the E-SNRHT intervention was more effective at decreasing enacted HIV-related stigma than was risk network recruitment. Individuals newly diagnosed with HIV by the E-SNRHT intervention reported significant increases in social support between intervention enrollment and follow-up, and all of these individuals reported participating in positive conversations about HIV services with peers in the 6-10 weeks after intervention enrollment. These findings suggest that E-SNRHT is a potentially important strategy to reduce HIV-related stigma as a barrier to HIV testing among peer networks in KwaZulu-Natal.

The U.S. population has suffered worse health consequences owing to COVID-19 than comparable wealthy nations. COVID-19 had caused more than 1.1 million deaths in the U.S. as of May 2023 and contributed to a 3-year decline in life expectancy. A coalition of public health workers and community activists launched an external review of the Centers for Disease Control and Prevention's pandemic management from January 2021 to May 2023. The authors used a modified Delphi process to identify core pandemic management areas, which formed the basis for a survey and literature review. Their analysis yields 3 overarching shortcomings of the Centers for Disease Control and Prevention's pandemic management: (1) Centers for Disease Control and Prevention leadership downplays the serious impacts and aerosol transmission risks of COVID-19, (2) Centers for Disease Control and Prevention leadership has aligned public guidance with commercial and political interests over scientific evidence, and (3) Centers for Disease Control and Prevention guidance focuses on individual choice rather than emphasizing prevention and equity. Instead, the agency must partner with communities most impacted by the pandemic and encourage people to protect one another using layered protections to decrease COVID-19 transmission. Because emerging variants can already evade existing vaccines and treatments and Long COVID can be disabling and lacks definitive treatment, multifaceted, sustainable approaches to the COVID-19 pandemic are essential to protect people, the economy, and future generations.

An important challenge to addressing the opioid overdose crisis is the lack of information on the size of the population of people who misuse opioids (PWMO) in local areas. This estimate is needed for better resource allocation, estimation of treatment and overdose outcome rates using appropriate denominators (ie, the population at risk), and proper evaluation of intervention effects. In this study, we used a bayesian hierarchical spatiotemporal integrated abundance model that integrates multiple types of county-level surveillance outcome data, state-level information on opioid misuse, and covariates to estimate the latent (hidden) numbers of PWMO and latent prevalence of opioid misuse across New York State counties (2007-2018). The model assumes that each opioid-related outcome reflects a partial count of the number of PWMO, and it leverages these multiple sources of data to circumvent limitations of parameter estimation associated with other types of abundance models. Model estimates showed a reduction in the prevalence of PWMO during the study period, with important spatial and temporal variability. The model also provided county-level estimates of rates of treatment and opioid overdose using the numbers of PWMO as denominators. This modeling approach can identify the sizes of hidden populations to guide public health efforts in confronting the opioid overdose crisis across local areas. This article is part of a Special Collection on Mental Health.

BACKGROUND:Intervention packages may result in a greater public health impact than single interventions. Understanding the separate impact of each component on the overall package effectiveness can improve intervention delivery. METHODS:We adapted an approach to evaluate the effects of a time-varying intervention package in a network-randomized study. In some network-randomized studies, only a subset of participants in exposed networks receive the intervention themselves. The spillover effect contrasts average potential outcomes if a person was not exposed to themselves under intervention in the network versus no intervention in a control network. We estimated the effects of components of the intervention package in HIV Prevention Trials Network 037, a Phase III network-randomized HIV prevention trial among people who inject drugs and their risk networks using marginal structural models to adjust for time-varying confounding. The index participant in an intervention network received a peer education intervention initially at baseline, then boosters at 6 and 12 months. All participants were followed to ascertain HIV risk behaviors. RESULTS:There were 560 participants with at least one follow-up visit, 48% of whom were randomized to the intervention, and 1,598 participant visits were observed. The spillover effect of the boosters in the presence of initial peer education training was a 39% rate reduction (rate ratio = 0.61; 95% confidence interval = 0.43, 0.87). CONCLUSIONS:These methods will be useful for evaluating intervention packages in studies with network features.

BACKGROUND:New diagnoses of HIV-1 infection among people who inject drugs (PWID) in Athens, Greece, saw a significant increase in 2011 and a subsequent decline after 2013. Despite this, ongoing HIV-1 transmission persisted from 2014 to 2020 within this population. Our objective was to estimate the time of infection for PWID in Athens following the HIV-1 outbreak, explore the patterns of HIV-1 dispersal over time, and determine the duration from infection to diagnosis. METHODS:Time from HIV-1 infection to diagnosis was estimated for 844 individuals infected within 4 PWID-specific clusters and for 8 PWID infected with sub-subtype A6 diagnosed during 2010-2019. Phylogeny reconstruction was performed using the maximum-likelihood method. HIV-1 infection dates were based on molecular clock calculations. RESULTS:In total 86 of 92 (93.5%) sequences from PWID diagnosed during 2016-2019 were either related to the previously identified PWID-specific clusters (n = 81) or belonged to a new A6 cluster (n = 5). The median time between infection and diagnosis was 0.42 years during the outbreak period and 0.70 years during 2016-2019 (p < 0.001). The proportion of clustered sequences from PWID was very low at 5.3% during the pre-outbreak period (1998-2009), saw an increase to 41.7% one year before the outbreak in 2010, and consistently remained high during the whole period after 2011, spanning the post-outbreak period (2016-2019) with a range from 92.9% to 100%. CONCLUSIONS:The substantial proportion of clustered infections (93.5%) during 2016-2019 implies a persistent 'slow burn' HIV outbreak among PWID in Athens, suggesting that the outbreak was not successfully eliminated. The consistently high proportion of clustered sequences since the onset of the outbreak suggests the persistence of ongoing HIV-1 transmission attributed to injection practices. Our findings underscore the importance of targeted interventions among PWID, considering the ongoing transmission rate and prolonged time from infection to diagnosis.

BACKGROUND:Non-fatal overdose is a leading predictor of subsequent fatal overdose. For individuals who are incarcerated, the risk of experiencing an overdose is highest when transitioning from a correctional setting to the community. We assessed if enrollment in jail-based medications for opioid use disorder (MOUD) is associated with lower risk of non-fatal opioid overdoses after jail release among individuals with opioid use disorder (OUD). METHODS:This was a retrospective, observational cohort study of adults with OUD who were incarcerated in New York City jails and received MOUD or did not receive any MOUD (out-of-treatment) within the last three days before release to the community in 2011-2017. The outcome was the first non-fatal opioid overdose emergency department (ED) visit within 1 year of jail release during 2011-2017. Covariates included demographic, clinical, incarceration-related, and other characteristics. We performed multivariable cause-specific Cox proportional hazards regression analysis to compare the risk of non-fatal opioid overdose ED visits within 1 year after jail release between groups. RESULTS:MOUD group included 8660 individuals with 17,119 incarcerations; out-of-treatment group included 10,163 individuals with 14,263 incarcerations. Controlling for covariates and accounting for competing risks, in-jail MOUD was associated with lower non-fatal opioid overdose risk within 14 days after jail release (adjusted HR=0.49, 95% confidence interval=0.33-0.74). We found no significant differences 15-28, 29-56, or 57-365 days post-release. CONCLUSION/CONCLUSIONS:MOUD group had lower risk of non-fatal opioid overdose immediately after jail release. Wider implementation of MOUD in US jails could potentially reduce post-release overdoses, ED utilization, and associated healthcare costs.