Faculty Bibliography

OBJECTIVES/OBJECTIVE:To investigate the validity of the apparent downward trend in the national case-fatality rate for gunshot wounds from assault. METHODS:We reanalyzed the estimated annual number of nonfatal firearm injuries the National Electronic Injury Surveillance System reported from 2003 to 2012. We adjusted the estimates for discontinuities created by the substitution of 1 hospital for another in the sample and for a downward trend in the percentage of gunshot injuries classified as "unknown circumstance." Firearm homicide data are from the Centers for Disease Control and Prevention, Web-based Injury Statistics Query and Reporting System. RESULTS:The unadjusted National Electronic Injury Surveillance System estimate increased by 49%, yielding a decline in the case-fatality rate from 25% to 18%. Our adjustments eliminated these trends; the case-fatality rate was 22% in both 2003 and 2012. CONCLUSIONS:With reasonable adjustments, the trend in nonfatal injuries from interpersonal firearms assault tracks the flat trend in firearms homicides, suggesting that there was no increase in firearms violence during this period. The case-fatality rate did not change, and trauma care improvements did not influence the firearms homicide trend.

BACKGROUND:People who inject drugs (PWID) are at continued risk for HIV in the U.S., and experience disparities across the HIV care continuum compared to other high-risk groups. Estimates of the risk of HIV transmission at each stage of the care continuum may assist in identifying public health priorities for averting incident infections among PWID, in addition to transmissions to sexual partners of PWID. METHODS:We created an agent-based model simulating HIV transmission and the HIV care continuum for PWID in New York City (NYC) in 2012. To account for sexual transmission arising from PWID to non-PWID, the simulation included the entire adult NYC population. Using surveillance data and estimates from the National HIV Behavioral Surveillance system, we simulated a dynamic sexual and injecting network. We estimated the proportion of HIV transmission events attributable to PWID in the following categories, those: without an HIV diagnosis ('Undiagnosed'); diagnosed but not on antiretroviral therapy (ART) ('Diagnosed - not on ART'); those who initiated ART but were not virally suppressed ('Unsuppressed'); and, those who achieved viral suppression ('Suppressed'). RESULTS:We estimated HIV incidence among PWID to be 113 per 100,000 person-years in 2012, with an overall incidence rate for the entire adult NYC population of 33 per 100,000 person-years. Despite accounting for only 33% of the HIV-infected PWID population, the Undiagnosed were associated with 52.6% (95% simulation interval [95% SI]: 47.1-57.0%) of total transmission events. The Diagnosed - not on ART population contributed the second-largest proportion of HIV transmissions, with 36.6% (95% SI: 32.2-41.5%). The Unsuppressed population contributed 8.7% (95% SI: 5.6-11.8%), and Suppressed 2.1% (95% SI: 1.1-3.9%), relatively little of overall transmission. CONCLUSIONS:Among PWID in NYC, more than half (53%) of transmissions were from those who were unaware of their infection status and more than 36% were due to PWID who knew their status, but were not on treatment. Our results indicate the importance of early diagnosis and interventions to engage diagnosed PWID on treatment to further suppress population-level HIV transmission. Future HIV prevention research should focus on the elimination of identified and potential barriers to the testing, diagnosis, and retention of PWID on HIV treatment.

Agent-based models (ABMs) have grown in popularity in epidemiologic applications, but the assumptions necessary for valid inference have only partially been articulated. In this issue, Murray et al. (Am J Epidemiol. 2017;186(2):131-142) provided a much-needed analysis of the consequence of some of these assumptions, comparing analysis using an ABM to a similar analysis using the parametric g-formula. In particular, their work focused on the biases that can arise in ABMs that use parameters drawn from distinct populations whose causal structures and baseline outcome risks differ. This demonstration of the quantitative issues that arise in transporting effects between populations has implications not only for ABMs but for all epidemiologic applications, because making use of epidemiologic results requires application beyond a study sample. Broadly, because health arises within complex, dynamic, and hierarchical systems, many research questions cannot be answered statistically without strong assumptions. It will require every tool in our store of methods to properly understand population dynamics if we wish to build an evidence base that is adequate for action. Murray et al.'s results provide insight into these assumptions that epidemiologists can use when selecting a modeling approach.

BACKGROUND:Recently, social movements across the world have demanded reforms to education systems and other institutions. Although such movements have affected large numbers of people across multiple countries, we know little about the impacts they have had on population health. We focus on one example: the massive strikes and collective occupation of secondary schools across Chile, which occurred contemporaneously with a large increase in marijuana use among students in this age group. We aimed to evaluate the causal effects that the 2011 Chilean school strikes had on adolescent substance use, including the initiation of marijuana use and the use of alcohol and marijuana. METHODS:School-level, aggregated panel design using data from the National Drug Surveys among Secondary Students from 2005 to 2015 for students in grades 9-12. We used a fixed-effects difference-in-difference model to estimate the effect of school occupations on prevalence of self-reported indicators of drug use. RESULTS:Reported marijuana use doubled between 2009 and 2013 among Chilean adolescents. After controlling for secular trends in outcomes and for school characteristics, there was no evidence of increased marijuana initiation, alcohol and marijuana use, or of an increase in heavy use among adolescents being directly attributable to school strikes and occupations in 2011. CONCLUSIONS:The 2011 Occupy school movement in Chile had no detectable causal effect on substance use among Chilean adolescents. The increase in marijuana use from 2009 to 2013 seems to be part of broader social changes occurring among the school-age population.

Calls to address crack-cocaine use in Brazil among homeless and street-frequenting populations who are in urgent need of health services have questioned the capacity of the Brazilian Unified Health System to attend to the nation's most marginalized citizens. In recent years, Brazil has launched several actions to escalate care for substance users, yet many obstacles hindering accessibility and effectiveness of services remain. Paradoxically, these actions have been implemented in the context of a growing economic crisis, and expanding services for a population of poor and stigmatized substance users while cutting other government programs tends to elicit harsh criticism from citizens. In consequence of such prospects, this commentary aims to discuss barriers marginalized substance users face in accessing health services that are at risk of worsening with government cutbacks. Using Rio de Janeiro as an example, we explore two primary issues: the resource-strained, under-staffed and decentralized nature of the Brazilian Unified Health System and the pervading stigma that bars vulnerable citizens from official structures and services. Abandoning initiated government efforts to increase access to health services would risk maintaining vulnerable citizens at the margins of public structures, inhibiting the opportunity to offer this population humane and urgently needed treatment and care.

OBJECTIVES:To examine whether racial/ethnic disparities persist at the "end of the HIV epidemic" (prevalence of untreated HIV infection < 5%; HIV incidence < 0.5 per 100 person-years) among persons who inject drugs (PWID) in New York City. METHODS:We recruited 2404 PWID entering New York City substance use treatment in 2001 to 2005 and 2011 to 2015. We conducted a structured interview, and testing for HIV and herpes simplex virus 2 (HSV-2; a biomarker for high sexual risk). We estimated incidence by using newly diagnosed cases of HIV. Disparity analyses compared HIV, untreated HIV, HIV-HSV-2 coinfection, HIV monoinfection, and estimated HIV incidence among Whites, African Americans, and Latinos. RESULTS:By 2011 to 2015, Whites, African Americans, and Latino/as met both criteria of our operational "end-of-the-epidemic" definition. All comparisons that included HIV-HSV-2-coinfected persons had statistically significant higher rates of HIV among racial/ethnic minorities. No comparisons limited to HIV monoinfected persons were significant. CONCLUSIONS:"End-of-the-epidemic" criteria were met among White, African American, and Latino/a PWID in New York City, but elimination of disparities may require a greater focus on PWID with high sexual risk.

BACKGROUND:Housing instability has been associated with poor health outcomes among people who inject drugs (PWID). This study investigates the associations of local-level housing and economic conditions with homelessness among a large sample of PWID, which is an underexplored topic to date. METHODS:PWID in this cross-sectional study were recruited from 19 large cities in the USA as part of National HIV Behavioral Surveillance. PWID provided self-reported information on demographics, behaviours and life events. Homelessness was defined as residing on the street, in a shelter, in a single room occupancy hotel, or in a car or temporarily residing with friends or relatives any time in the past year. Data on county-level rental housing unaffordability and demand for assisted housing units, and ZIP code-level gentrification (eg, index of percent increases in non-Hispanic white residents, household income, gross rent from 1990 to 2009) and economic deprivation were collected from the US Census Bureau and Department of Housing and Urban Development. Multilevel models evaluated the associations of local economic and housing characteristics with homelessness. RESULTS:Sixty percent (5394/8992) of the participants reported homelessness in the past year. The multivariable model demonstrated that PWID living in ZIP codes with higher levels of gentrification had higher odds of homelessness in the past year (gentrification: adjusted OR=1.11, 95% CI=1.04 to 1.17). CONCLUSIONS:Additional research is needed to determine the mechanisms through which gentrification increases homelessness among PWID to develop appropriate community-level interventions.

Importance/UNASSIGNED:Over the last 25 years, illicit cannabis use and cannabis use disorders have increased among US adults, and 28 states have passed medical marijuana laws (MML). Little is known about MML and adult illicit cannabis use or cannabis use disorders considered over time. Objective/UNASSIGNED:To present national data on state MML and degree of change in the prevalence of cannabis use and disorders. Design, Participants, and Setting/UNASSIGNED:Differences in the degree of change between those living in MML states and other states were examined using 3 cross-sectional US adult surveys: the National Longitudinal Alcohol Epidemiologic Survey (NLAES; 1991-1992), the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC; 2001-2002), and the National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III; 2012-2013). Early-MML states passed MML between NLAES and NESARC ("earlier period"). Late-MML states passed MML between NESARC and NESARC-III ("later period"). Main Outcomes and Measures/UNASSIGNED:Past-year illicit cannabis use and DSM-IV cannabis use disorder. Results/UNASSIGNED:Overall, from 1991-1992 to 2012-2013, illicit cannabis use increased significantly more in states that passed MML than in other states (1.4-percentage point more; SE, 0.5; P = .004), as did cannabis use disorders (0.7-percentage point more; SE, 0.3; P = .03). In the earlier period, illicit cannabis use and disorders decreased similarly in non-MML states and in California (where prevalence was much higher to start with). In contrast, in remaining early-MML states, the prevalence of use and disorders increased. Remaining early-MML and non-MML states differed significantly for use (by 2.5 percentage points; SE, 0.9; P = .004) and disorder (1.1 percentage points; SE, 0.5; P = .02). In the later period, illicit use increased by the following percentage points: never-MML states, 3.5 (SE, 0.5); California, 5.3 (SE, 1.0); Colorado, 7.0 (SE, 1.6); other early-MML states, 2.6 (SE, 0.9); and late-MML states, 5.1 (SE, 0.8). Compared with never-MML states, increases in use were significantly greater in late-MML states (1.6-percentage point more; SE, 0.6; P = .01), California (1.8-percentage point more; SE, 0.9; P = .04), and Colorado (3.5-percentage point more; SE, 1.5; P = .03). Increases in cannabis use disorder, which was less prevalent, were smaller but followed similar patterns descriptively, with change greater than never-MML states in California (1.0-percentage point more; SE, 0.5; P = .06) and Colorado (1.6-percentage point more; SE, 0.8; P = .04). Conclusions and Relevance/UNASSIGNED:Medical marijuana laws appear to have contributed to increased prevalence of illicit cannabis use and cannabis use disorders. State-specific policy changes may also have played a role. While medical marijuana may help some, cannabis-related health consequences associated with changes in state marijuana laws should receive consideration by health care professionals and the public.

BACKGROUND:Psychiatric disorders are highly comorbid with substance use disorders and play an important role in their course and recovery. However, the impact of comorbidity on treatment outcomes has not been examined in a U.S. national sample. This study explores the impact of psychiatric comorbidity on treatment completion among individuals admitted to publicly funded substance use treatment facilities across the United States. METHODS:Using data on first-time treatment episodes in the U.S. from the Treatment Episode Dataset-Discharges (TEDS-D) for the years 2009-2011, logistic regression was used to assess the association between psychiatric comorbidity and treatment non-completion, and Cox proportional hazards regression was used to assess the association between comorbidity and rate of attrition. Analyses were performed for all substances together and then stratified by primary substance of abuse (alcohol, cannabis, stimulants, or opioids). RESULTS:Of 856,385 client treatment episodes included in our analysis, 28% had a psychiatric comorbidity and 38% did not complete treatment. After adjusting for socio-demographic and treatment characteristics, clients with psychiatric comorbidity had higher odds of not completing treatment relative to those without comorbidity [OR=1.28 (1.27-1.29)], and had an earlier time to attrition [HR=1.14 (1.13-1.15)]. Psychiatric comorbidity was most strongly associated with treatment non-completion and rate of attrition in those admitted primarily for alcohol [OR=1.37 (1.34-1.39); HR=1.19 (1.17-1.21), respectively]. CONCLUSIONS:Individuals with psychiatric comorbidities receiving treatment for substance use disorders face unique challenges that impact their ability to complete treatment. The findings call for further efforts to integrate treatment for psychiatric comorbidities in substance use treatment settings.