Simulating the Simultaneous Impact of Medication for Opioid Use Disorder and Naloxone on Opioid Overdose Death in Eight New York Counties.

BACKGROUND: The United States is in the midst of an opioid overdose epidemic; 28.3 per 100,000 people died of opioid overdose in 2020. Simulation models can help understand and address this complex, dynamic, and nonlinear social phenomenon. Using the HEALing Communities Study, aimed at reducing opioid overdoses, and an agent-based model, Simulation of Community-Level Overdose Prevention Strategy, we simulated increases in buprenorphine initiation and retention and naloxone distribution aimed at reducing overdose deaths by 40% in New York Counties. METHODS: Our simulations covered 2020-2022. The eight counties contrasted urban or rural and high and low baseline rates of opioid use disorder treatment. The model calibrated agent characteristics for opioid use and use disorder, treatments and treatment access, and fatal and nonfatal overdose. Modeled interventions included increased buprenorphine initiation and retention, and naloxone distribution. We predicted a decrease in the rate of fatal opioid overdose 1 year after intervention, given various modeled intervention scenarios. RESULTS: Counties required unique combinations of modeled interventions to achieve a 40% reduction in overdose deaths. Assuming a 200% increase in naloxone from current levels, high baseline treatment counties achieved a 40% reduction in overdose deaths with a simultaneous 150% increase in buprenorphine initiation. In comparison, low baseline treatment counties required 250-300% increases in buprenorphine initiation coupled with 200-1000% increases in naloxone, depending on the county. CONCLUSIONS: Results demonstrate the need for tailored county-level interventions to increase service utilization and reduce overdose deaths, as the modeled impact of interventions depended on the county's experience with past and current interventions.

Would restricting firearm purchases due to alcohol- and drug-related misdemeanor offenses reduce firearm homicide and suicide? An agent-based simulation.

BACKGROUND: Substance-related interactions with the criminal justice system are a potential touchpoint to identify people at risk for firearm violence. We used an agent-based model to simulate the change in firearm violence after disqualifying people from owning a firearm given prior alcohol- and drug-related misdemeanors. METHODS: We created a population of 800,000 agents reflecting a 15% sample of the adult New York City population. RESULTS: Disqualification from purchasing firearms for 5 years after an alcohol-related misdemeanor conviction reduced population-level rates of firearm homicide by 1.0% [95% CI 0.4-1.6%] and suicide by 3.0% [95% CI 1.9-4.0%]. Disqualification based on a drug-related misdemeanor conviction reduced homicide by 1.6% [95% CI 1.1-2.2%] and suicide by 4.6% [95% CI 3.4-5.8%]. Reductions were generally 2 to 8 times larger for agents meeting the disqualification criteria. CONCLUSIONS: Denying firearm access based on a history of drug and alcohol misdemeanors may reduce firearm violence among the high-risk group. Enactment of substance use-related firearms denial criteria needs to be balanced against concerns about introducing new sources of disenfranchisement among already vulnerable populations.

Age, Period, and Cohort Effects of Internalizing Symptoms Among US Students and the Influence of Self-Reported Frequency of Attaining 7 or More Hours of Sleep: Results From the Monitoring the Future Survey 1991-2019.

Adolescent internalizing symptoms have increased since 2010, whereas adequate sleep has declined for several decades. It remains unclear how self-reported sleep attainment has affected internalizing-symptoms trends. Using 1991-2019 data from the Monitoring the Future Study (n ~ 390,000), we estimated age-period-cohort effects in adolescent internalizing symptoms (e.g., loneliness, self-esteem, self-derogation, depressive affect) and the association with yearly prevalence of a survey-assessed, self-reported measure of attaining ≥7 hours of sleep most nights. We focused our main analysis on loneliness and used median odds ratios to measure variance in loneliness associated with period differences. We observed limited signals for cohort effects and modeled only period effects. The feeling of loneliness increased by 0.83% per year; adolescents in 2019 had 0.68 (95% CI: 0.49, 0.87) increased log odds of loneliness compared with the mean, which was consistent by race/ethnicity and parental education. Girls experienced steeper increases in loneliness than boys (P < 0.0001). The period-effect median odds ratio for loneliness was 1.16 (variance = 0.09; 95% CI: 0.06, 0.17) before adjustment for self-reported frequency of getting ≥7 hours sleep versus 1.07 (variance = 0.02; 95% CI: 0.01, 0.03) after adjustment. Adolescents across cohorts are experiencing worsening internalizing symptoms. Self-reported frequency of <7 hours sleep partially explains increases in loneliness, indicating the need for feasibility trials to study the effect of increasing sleep attainment on internalizing symptoms.

A Systematic Review of Simulation Models to Track and Address the Opioid Crisis.

The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models are a tool to help us understand and address thiscomplex, dynamic, and nonlinear social phenomenon. We conducted a systematic review of the literature on simulation models of opioid use and overdose up to September 2019. We extracted modeling types, target populations, interventions, and findings; created a database of model parameters used for model calibration; and evaluated study transparency and reproducibility. Of the 1,398 articles screened, we identified 88 eligible articles. The most frequent types of models were compartmental (36%), Markov (20%), system dynamics (16%), and agent-based models (16%). Intervention cost-effectiveness was evaluated in 40% of the studies, and 39% focused on services for people with opioid use disorder (OUD). In 61% of the eligible articles, authors discussed calibrating their models to empirical data, and in 31%, validation approaches used in the modeling process were discussed. From the 63 studies that provided model parameters, we extracted the data sources on opioid use, OUD, OUD treatment, cessation or relapse, emergency medical services, and death parameters. From this database, potential model inputs can be identified and models can be compared with prior work. Simulation models should be used to tackle key methodological challenges, including the potential for bias in the choice of parameter inputs, investment in model calibration and validation, and transparency in the assumptions and mechanics of simulation models to facilitate reproducibility.

Trends in cannabis use and attitudes toward legalization and use among Australians from 2001-2016: an age-period-cohort analysis.

BACKGROUND AND AIMS: Changes in cannabis legalization and availability in Australia necessitate monitoring use and attitudes. We estimated age-period-cohort effects of past-year cannabis use and attitudes toward criminalization and legalization. DESIGN: Analysis of six waves of the Australian National Drug Strategy Household Survey (NDSHS) every 3 years (2001-2016). SETTING AND PARTICIPANTS: The study was nationally representative of Australian households using multistage random sampling, totaling 145 168 respondents 18-79 years old. Data were collected using telephone, face-to-face, and drop-and-collect. Sample sizes per analysis varied based on data availability (~107 000-127 000 per model). MEASUREMENTS: Six waves of data for past-year cannabis use (by sex and education), attitudes toward criminalization and legalization. FINDINGS: Past-year cannabis use decreased in young adults ages 18-35 from 2001-2016 (25.1%-18.6%) and increased in middle adults ages 36-55 (8.6%-10.1%) and older adults ages 56-79 (0.6%-3.0%). We observed a positive period effect and negative cohort effect for recent cohorts for past-year use (e.g. 1955 cohort had 1.41 (95% CI: [1.11, 1.70]) increased log odds vs. 1998 cohort had -2.86 (95% CI: [-3.17, -2.55]) increased log odds) compared with the mean across years. Results were consistent by sex and varied by education. We observed a negative period effect for criminalization favorability (0.14 (95% CI: [0.003, 0.28]) increased log odds in 2001 vs. -0.31 (95% CI: [-0.45, -0.17]) increased log odds in 2016) and positive cohort effect for recent cohorts. Last, we observed a positive period effect for legalization support (-0.03 (95% CI: [-0.20, 0.14]) increased log odds in 2001 vs. 0.38 (95% CI: [0.22, 0.55]) increased log odds in 2016) and negative cohort effect for recent cohorts. CONCLUSION: Cannabis use appears to be increasing in Australia among adults over 35, while decreasing among adolescents and young adults. Legalization support also appears to have been increasing since 2007, signaling discordance between use and attitudes among adolescents and young adults, and potentially predicting increases in use over time.

Age, period and cohort effects in frequent cannabis use among US students: 1991-2018.

BACKGROUND AND AIMS: As the legal status of cannabis changes across the United States and modes of administration expand, it is important to examine the potential impact on adolescent cannabis use. This study aimed to assess changes in prevalence of frequent cannabis use in adolescents in the United States and how far this varies by age and cohort. DESIGN: Analysis of Monitoring the Future, a nationally representative annual survey of 8th-, 10th- and 12th-grade students in the United States conducted from 1991 to 2018. SETTING: In-school surveys completed by US adolescents. PARTICIPANTS: A total of 1 236 159 8th-, 10th- and 12th-graders; 51.5% female, 59.6% non-Hispanic white, 12.3% non-Hispanic black, 13.4% Hispanic and 14.7% other race/ethnicity. MEASUREMENTS: Frequent cannabis use (FCU), defined as six or more occasions in the past 30 days, stratified by sex, race/ethnicity and parental education. FINDINGS: FCU among US adolescents increased over the study period; the peak in 2010-18 was 11.4% among 18-year-old students. This increase was best explained by both period and cohort effects. Compared with respondents in 2005, adolescents surveyed in 2018 had period effects in FCU that were 1.6 times greater. Adolescents in younger birth cohorts (those born > 1988) had a lower increase in FCU than those born prior to 1988. Results were consistent across sex, parent education and race/ethnicity, with period effects indicating increasing FCU after 2005 and cohort effects indicating a lower magnitude of increase in more recent birth cohorts. Age and parental education disparities in FCU have increased over time, whereas race/ethnicity differences have converged over time; black students were 0.67 [95% confidence interval (CI) = 0.64-0.70] times as likely to use cannabis frequently as white students from 1991 to 2000, and 1.03 (95% CI = 0.98-1.09) times as likely from 2011 to 2018 (P-value for time interaction < 0.001). CONCLUSIONS: The prevalence of frequent cannabis use (FCU) increased from 1991 to 2018 among older adolescents in the United States. Racial/ethnic differences in FCU converged, whereas parental education differences have diverged.

Frequent Binge Drinking Among US Adolescents, 1991 to 2015.

BACKGROUND AND OBJECTIVES: Scientific understanding of the forces involved in the decades-long decline of adolescent alcohol use in the United States is limited. This study examines specific changes in US adolescent frequent binge drinking (FBD) by age (variation due to maturation), period (variation across time that does not covary across age), and cohort (variation common to adolescents born around the same time). METHODS: We analyzed nationally representative, multicohort data from 8th, 10th, and 12th grade students sampled between 1991 and 2015 from Monitoring the Future (n = 1 065 022) to estimate age, period, and cohort effects on adolescents' FBD (defined as ≥2 occasions of ≥5 drinks in a row during the past 2 weeks). Age-Period-Cohort analyses were stratified by sex, race/ethnicity, and socioeconomic status (SES). Trends in the associations between demographics and FBD across historical time were examined. RESULTS: Decreases in FBD during adolescence were attributable to period and cohort effects independent of age variations. Birth cohorts between 1985 and 1990 showed the greatest decline in FBD. The Age-Period-Cohort results were consistent across sex, race/ethnicity, and SES, with the exception of slower declines seen among African American adolescents compared with white adolescents since 2007. We also found convergence in FBD by sex and divergence by SES. CONCLUSIONS: Recent declines in adolescent FBD have been driven by period and cohort effects. Attention is warranted for the slower declines in FBD seen among African American adolescents since 2007, a narrowing difference by sex, and a growing gap by SES.

Sexual orientation disparities in mental health: the moderating role of educational attainment.

PURPOSE: Mental health disparities between sexual minorities and heterosexuals remain inadequately understood, especially across levels of educational attainment. The purpose of the present study was to test whether education modifies the association between sexual orientation and mental disorder. METHODS: We compared the odds of past 12-month and lifetime psychiatric disorder prevalence (any Axis-I, any mood, any anxiety, any substance use, and comorbidity) between lesbian, gay, and bisexual (LGB) and heterosexual individuals by educational attainment (those with and without a bachelor's degree), adjusting for covariates, and tested for interaction between sexual orientation and educational attainment. Data are drawn from the National Epidemiologic Survey on Alcohol and Related Conditions, a nationally representative survey of non-institutionalized US adults (N = 34,653; 577 LGB). RESULTS: Sexual orientation disparities in mental health are smaller among those with a college education. Specifically, the disparity in those with versus those without a bachelor's degree was attenuated by 100 % for any current mood disorder, 82 % for any current Axis-I disorder, 76 % for any current anxiety disorder, and 67 % for both any current substance use disorder and any current comorbidity. Further, the interaction between sexual orientation and education was statistically significant for any current Axis-I disorder, any current mood disorder, and any current anxiety disorder. Our findings for lifetime outcomes were similar. CONCLUSIONS: The attenuated mental health disparity at higher education levels underscores the particular risk for disorder among LGBs with less education. Future studies should consider selection versus causal factors to explain the attenuated disparity we found at higher education levels.