Faculty Bibliography

BACKGROUND:American Indians and Alaska Natives (AI/ANs) are disproportionately affected by the opioid overdose crisis. Treatment with medications for opioid use disorder (MOUD) can significantly reduce overdose risk, but no national studies to date have reported on the extent to which AI/ANs access these treatments overall and in relation to other groups. METHODS:The current study used two national databases - the 2018 National Survey on Substance Abuse Treatment Services and the 2017 Treatment Episode Dataset - to estimate the extent to which MOUD is available and used among AI/ANs across the U.S. RESULTS:We found that facilities serving AI/ANs (N = 1,532) offered some MOUD at similar rates as other facilities (N = 13,277) (39.6 vs. 40.6 %, p = 0.435) but were less likely to offer the standard of care with buprenorphine or methadone maintenance (22.4 % vs. 27.6 %, p < 0.001). AI/AN clients in specialty treatment (N = 8,136) exhibited slightly higher MOUD use (40.0 % vs. 38.6 %, p = 0.009) relative to other race groups (N = 673,938). AI/AN clients were also more likely to exhibit greater prescription opioid use and methamphetamine co-use relative to other groups. AI/AN clients in the South (aOR:0.23[95 %CI: 0.19-0.28] or referred by criminal justice sources (aOR:0.13[95 %CI: 0.11-0.16] were least likely to receive MOUD. CONCLUSIONS:We conclude that most AI/ANs in specialty treatment do not receive medications for opioid use disorder, and that rates of MOUD use are similar to those of other race groups. Efforts to expand MOUD among AI/ANs that are localized and cater to unique characteristics of this population are gravely needed.

PURPOSE/OBJECTIVE:To assess cross-population linkages in HIV/AIDS epidemics, we tested the hypothesis that the number of newly diagnosed AIDS cases among Black people who inject drugs (PWID) was positively related to the natural log of the rate of newly diagnosed HIV infections among Black non-PWID heterosexuals in 84 large U.S. metropolitan statistical areas (MSAs) in 2008-2016. METHODS:We estimated a multilevel model centering the time-varying continuous exposures at baseline between the independent (Black PWID AIDS rates) and dependent (HIV diagnoses rate among Black heterosexuals) variables. RESULTS:At MSA level, baseline (standardized β = 0.12) Black PWID AIDS rates and change in these rates over time (standardized β = 0.11) were positively associated with the log of new HIV diagnoses rates among Black heterosexuals. Thus, MSAs with Black PWID AIDS rates that were 1 standard deviation= higher at baseline also had rates of newly diagnosed HIV infections among Black non-PWID heterosexuals that were 10.3% higher. A 1 standard deviation increase in independent variable over time corresponded to a 7.8% increase in dependent variable. CONCLUSIONS:Black PWID AIDS rates may predict HIV rates among non-PWID Black heterosexuals. Effective HIV programming may be predicated, in part, on addressing intertwining of HIV epidemics across populations.

Stigma is a known barrier to treating substance use disorders and dramatically diminishes the quality of life of people who use drugs (PWUD) nonmedically. Stigma against PWUD may be especially pronounced in rural areas due to their decreased anonymity and residents' limited access, or resistance, to "neutralizing" information on factors associated with drug use. Stigma often manifests in the attitudes of professionals whom stigmatized individuals regularly interact with and often materially impact. We analyzed interviews conducted between July 2018 and February 2019 with professional stakeholders in rural southern Illinois who interact with PWUD, specifically those who use opioids nonmedically or who inject drugs (n = 30). We further analyzed interview data from a complementary PWUD sample (n = 22). Interviews addressed perspectives around nonmedical drug use and treatment/harm reduction, with analysis centered around the Framework Integrating Normative Influences on Stigma and its focus on micro, meso and macro level stigmatization processes. Stakeholder participants included professionals from local law enforcement, courts, healthcare organizations, emergency management services, and faith-based and social services organizations. Most stakeholders, particularly law enforcement, negatively perceived PWUD and nonmedical drug use in general, questioned the character, agency and extrinsic value of PWUD, and used labels (e.g. "addict," "abuser," etc.) that may be regarded as stigmatizing. Further, most respondents, including PWUD, characterized their communities as largely unaware or dismissive of the bio-medical and sociocultural explanations for opioid use, drug injection and towards harm reduction services (e.g., syringe exchanges) and naloxone, which were frequently framed as undeserved usages of taxpayer funds. In conclusion, rural stigma against PWUD manifested and was framed as a substantial issue, notably activating at micro, meso and macro levels. Stigma prevention efforts in these communities should aim to improve public knowledge on the intricate factors contributing to opioid use and drug injection and harm reduction programming's moral and fiscal value.

BACKGROUND:Evidence suggests that individuals with history of substance use disorder (SUD) are at increased risk of COVID-19, but little is known about relationships between SUDs, overdose and COVID-19 severity and mortality. This study investigated risks of severe COVID-19 among patients with SUDs. METHODS:We conducted a retrospective review of data from a hospital system in New York City. Patient records from 1 January to 26 October 2020 were included. We assessed positive COVID-19 tests, hospitalizations, intensive care unit (ICU) admissions and death. Descriptive statistics and bivariable analyses compared the prevalence of COVID-19 by baseline characteristics. Logistic regression estimated unadjusted and sex-, age-, race- and comorbidity-adjusted odds ratios (AORs) for associations between SUD history, overdose history and outcomes. RESULTS:Of patients tested for COVID-19 (n = 188 653), 2.7% (n = 5107) had any history of SUD. Associations with hospitalization [AORs (95% confidence interval)] ranged from 1.78 (0.85-3.74) for cocaine use disorder (COUD) to 6.68 (4.33-10.33) for alcohol use disorder. Associations with ICU admission ranged from 0.57 (0.17-1.93) for COUD to 5.00 (3.02-8.30) for overdose. Associations with death ranged from 0.64 (0.14-2.84) for COUD to 3.03 (1.70-5.43) for overdose. DISCUSSION/CONCLUSIONS:Patients with histories of SUD and drug overdose may be at elevated risk of adverse COVID-19 outcomes.

This paper presents a framework that may help explain the interactions among capitalism, infectious disease, and environmental change in the world and in the Mediterranean region. Capitalism and the longevity of national governments require continued investment and economic growth. This disrupts the environment, most urgently in terms of climate change, which is expected to single out the Mediterranean region for droughts and heat and to lead to mass migrations of people and animals. Capitalism also disrupts the habitats of fauna, and creates factory farming and markets for the sale of animals from local ecologies that are being "opened up" for profitable use-all of which leads to increased interaction between potential vectors of infectious diseases and humans. Capitalist globalization has encouraged widespread international and other travel of people and goods, which can carry infectious people or animal vectors across long distances very rapidly. In sum, capitalism requires development, which creates environmental and infectious disease crises. Solving this problem will require profound political and economic change. In the immediate term, public health and medical institutions need to be protected against the pressures of austerity.

Coronavirus disease 2019 (COVID-19) will have a lasting impact on public health. In addition to the direct effects of COVID-19 infection, physical distancing and quarantine interventions have indirect effects on health. While necessary, physical distancing interventions to control the spread of COVID-19 could have multiple impacts on people living with opioid use disorder, including impacts on mental health that lead to greater substance use, the availability of drug supply, the ways that people use drugs, treatment-seeking behaviors, and retention in care. The degree to which COVID-19 will impact the opioid epidemic and through which of the possible mechanisms that we discuss is important to monitor. We employed simulation modeling to demonstrate the potential impact of physical distancing on overdose mortality.

More than 750,000 people in the United States died from an overdose between 1999 and 2018; two-thirds of those deaths involved an opioid. In this review, we present trends in opioid overdose rates during this period and discuss how the proliferation of opioid prescribing to treat chronic pain, changes in the heroin and illegally manufactured opioid synthetics markets, and social factors, including deindustrialization and concentrated poverty, contributed to the rise of the overdose epidemic. We also examine how current policies implemented to address the overdose epidemic may have contributed to reducing prescription opioid overdoses but increased overdoses involving illegal opioids. Finally, we identify new directions for research to understand the causes and solutions to this critical public health problem, including research on heterogeneous policy effects across social groups, effective approaches to reduce overdoses of illegal opioids, and the role of social contexts in shaping policy implementation and impact. Expected final online publication date for the Annual Review of Public Health, Volume 42 is April 1, 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

OBJECTIVES/OBJECTIVE:To examine patient characteristics and outcomes among opioid use disorder patients enrolled in low-threshold buprenorphine treatment during the COVID-19 pandemic. METHODS:This paper describes the adaptation of the Project Connections (PC) program, a low-threshold buprenorphine program in Baltimore, in response to the COVID-19 pandemic. This paper examines patient characteristics and initial outcomes of patients served during a rapid protocol shift to telehealth that allowed buprenorphine initiation without an in-person encounter following a state-mandated stay-at-home order. Patient characteristics were compared to a subsample of patients enrolled in the program before the COVID-19 pandemic. RESULTS:In March 2020, there was a sharp increase in new enrollments to the PC program. A total of 143 patients completed an intake assessment between March and May 2020 and 140 began treatment with buprenorphine/naloxone. Those who completed an intake assessment were primarily male (68.5%), Black (83.2%), had a mean age of 43.2 years (SD = 11.7), and reported a mean of 17.0 years of opioid use (SD = 12.9). The majority of patients were unemployed (72.7%) and reported previous criminal justice involvement (69.2%). Of those who completed an intake assessment, 96.5% returned for a second visit. Among those for whom 30-day retention data was available (n = 113), 63.7% were engaged for 30 days or longer. CONCLUSIONS:The PC program illustrates that offering on-demand, flexible treatment is an opportunity to increase opioid use disorder treatment access, even during a public health emergency that disrupted access to services. Relaxation of buprenorphine telehealth regulations allowed for flexibility in treatment and benefits vulnerable populations.

PURPOSE/OBJECTIVE:The challenges of producing adequate estimates of HIV prevalence among men who have sex with men (MSM) are well known. No one, to our knowledge, has published annual estimates of HIV prevalence among MSM over an extended period and across a wide range of geographic areas. METHODS:This article applies multilevel modeling to data integrated from numerous sources to estimate and validate trajectories of HIV prevalence among MSM from 1992 to 2013 for 86 of the largest metropolitan statistical areas in the United States. RESULTS:Our estimates indicate that HIV prevalence among MSM increased, from an across-metropolitan statistical area mean of 11% in 1992 to 20% in 2013 (S.D. = 3.5%). Our estimates by racial/ethnic subgroups of MSM suggest higher mean HIV prevalence among black and Hispanic/Latino MSM than among white MSM across all years and geographic regions. CONCLUSIONS:The increases found in HIV prevalence among all MSM are likely primarily attributable to decreases in mortality and perhaps also to increasing HIV incidence among racial/ethnic minority MSM. Future research is needed to confirm this. If true, health care initiatives should focus on targeted HIV prevention efforts among racial/ethnic minority MSM and on training providers to address cross-cutting health challenges of increased longevity among HIV-positive MSM.

BACKGROUND:The rapid growth of opioid abuse and related mortality across the United States has spurred the development of predictive models for the allocation of public health resources. These models should characterize heterogeneous growth across states using a drug epidemic framework that enables assessments of epidemic onset, rates of growth, and limited capacities for epidemic growth. METHODS:We used opioid overdose mortality data for 146 North and South Carolina counties from 2001 through 2014 to compare the retrodictive and predictive performance of a logistic growth model that parameterizes onsets, growth, and carrying capacity within a traditional Bayesian Poisson space-time model. RESULTS:In fitting the models to past data, the performance of the logistic growth model was superior to the standard Bayesian Poisson space-time model (deviance information criterion: 8088 vs. 8256), with reduced spatial and independent errors. Predictively, the logistic model more accurately estimated fatality rates 1, 2, and 3 years in the future (root mean squared error medians were lower for 95.7% of counties from 2012 to 2014). Capacity limits were higher in counties with greater population size, percent population age 45 to 64, and percent white population. Epidemic onset was associated with greater same-year and past-year incidence of overdose hospitalizations. CONCLUSION/CONCLUSIONS:Growth in annual rates of opioid fatalities was capacity limited, heterogeneous across counties, and spatially correlated, requiring spatial epidemic models for the accurate and reliable prediction of future outcomes related to opioid abuse. Indicators of risk are identifiable and can be used to predict future mortality outcomes.