International Journal of Drug Policy

BackgroundOpioid overdose mortality in the United States remains a severe public health crisis, with the burden distributed unequally across communities that differ in epidemic trajectory, baseline resources, and local context. While harm reduction through naloxone distribution and treatment through buprenorphine are both evidence-based strategies, how their effectiveness varies across county-level contexts has received limited quantitative study, limiting the ability of local policymakers to prioritize resources across counties. MethodsWe developed a simulation model of opioid use disorder (OUD) progression, calibrated separately to three Pennsylvania counties spanning large urban (Allegheny), mid-sized (Erie), and rural (Clearfield) settings using Bayesian calibration. We projected county-specific overdose mortality trajectories under three levels of proportional increase in dispensing rates of buprenorphine and naloxone (10%, 20%, and 30% above each countys observed baseline dispensing levels), over a 2025-2029 projection horizon. ResultsA 30% increase in naloxone dispensing above observed county baseline levels was projected to reduce cumulative overdose deaths over 2025-2029 by approximately 50% in Allegheny County (large urban), modestly in Erie County (mid-sized), and only slightly in Clearfield County (rural). Projected reductions were consistently smaller for buprenorphine across all three counties, except in Erie, where buprenorphine produced larger projected reductions than the other counties. Heterogeneity in naloxone responsiveness was strongly associated with each countys historical naloxone dispensing variability. ConclusionsThe same proportional increase in naloxone dispensing yields substantially different projected mortality reductions across counties depending on each countys baseline distribution history, a pattern invisible from mortality statistics alone. County-level context must inform harm reduction and treatment prioritization rather than uniform, population-proportional approaches.

BackgroundThe opioid epidemic remains an emergent health issue in the United States, as opioid-related deaths continue to rise in the second year of COVID-19. The introduction of synthetic opioids into the illicit supply began causing deaths in 2015, however, data describing the illicit opioid supply is scarce. MethodsWe used a newly available national dataset of drug seizure reports, aggregated from law enforcement agencies across the United States, to describe changes in fentanyl, heroin, and other opioid presence in the national illicit supply from 2011-2017, by state and geographic region. We assessed the relationship between drug seizures and opioid-related deaths at the state level using linear regression. ResultsNational and state increases in opioid seizure rates from 2011-2017 were entirely due to increased fentanyl and heroin seizures, as other opioid seizure rates remained constant. Most increases in seizures occurred in the Northeast, Midwest, and Appalachia, where fentanyl seizures and heroin seizures were highest and increased most sharply along with opioid deaths. The composition of drugs seized was similar within geographic regions, but did vary across regions. State opioid seizures of all types were strongly associated with state opioid deaths. The strongest relationship was between fentanyl seizures and fentanyl deaths. ConclusionsThe association between opioid seizures and deaths means seizure data has potential as an early-warning system to predict overdose, although national level data requires quality improvement. Regional variation in seizure rates supports existing evidence that illicit fentanyl and heroin supplies differ between regions, producing distinct regional risk environments, causing varying mortality rates.

BackgroundDrug checking services (DCS) promote drug supply awareness among people who use drugs (PWUD) by detecting adulterants such as fentanyl and xylazine that are associated with overdose morbidity and mortality. However, there is limited research on DCS implementation in Latin America (LA). MethodsWe conducted a survey of 38 DCS across LA (n=10) and the US (n=28) and compared program characteristics and barriers between these two regions. We also conducted a focus group discussion (FGD) with staff representing six organizations implementing DCS in LA. FGD themes were mapped to constructs quantitatively assessed in the survey. ResultsCompared to US DCS, LA DCS more frequently reported funding gaps as a major implementation barrier (80% vs. 54%), law enforcement confiscating DCS supplies (38% vs. 11%), as well as offering supervised drug consumption (30% vs. 4%) and mental health/counseling (40% vs. 18%), but less frequently reported that DCS equipment was legal (44% vs. 75%). DCS on the Mexico-US border focused on people who inject drugs and offered syringe services, supervised consumption, and rapid sexually transmitted infection testing. DCS in central Mexico, Colombia, Peru, and Chile primarily provided DCS for the nightlife community (e.g., attendees of concerts/raves). Barriers to DCS implementation cited by FGD discussants included inadequate funding, DCS legal ambiguities, lack of government support, and cartel violence. ConclusionDCS in LA would benefit from increased funding, government support, and a more permissive legal environment, thereby strengthening harm reduction efforts and improving safety for PWUD.

ObjectiveThis study investigated associations between social determinants of health (SDoH) and time to MOUD initiation across care settings, providing insights for targeted interventions to promote equitable care for OUD patients. Material and MethodsWe linked patient-level electronic health records (EHRs) from a regional integrated health system with census-tract-level SDoH from the Population Level Analysis and Community Estimates (PLACES) database. The study cohort included patients newly diagnosed with OUD (including overdose) between 2000 and 2024. We assessed temporal trends in newly diagnosed OUD cases and MOUD prescriptions, mapped the spatial correlation between OUD cases and the Area Deprivation Index, and used multivariable regression models to quantify associations between SDoH and MOUD initiation, adjusting for demographics, insurance type, and comorbidities. Analyses were stratified by care setting (emergency department, inpatient, and outpatient) to examine setting-specific associations. ResultsDuring 2000-2024, 51,521 patients with OUD or opioid overdose, among whom 14,858 (28.8%) received MOUD. OUD diagnoses peaked at 3,787 cases in 2017, then declined by 42.1% to 2,191 cases in 2024. MOUD initiation, especially buprenorphine, steadily increased throughout the study period. Geospatial analyses revealed more OUD cases in high-ADI neighborhoods. In multivariate analyses, older age and Black or African American race were associated with slower MOUD initiation. In the stratified analyses by care setting, significant associations between SDoH and MOUD initiation were primarily observed in the outpatient setting, though effect sizes were modest. ConclusionsIntegrating neighborhood-level SDoH with EHRs can uncover care-setting-specific disparities in treatment initiation and identify neighborhoods with unmet treatment needs.

BACKGROUNDThis study evaluates the reach, scalability, and implementation of a large-scale, multi-site tele-buprenorphine program designed to treat opioid use disorder (OUD) within rural carceral settings. Given that individuals transition frequently between jails and the community, these facilities represent a critical window for OUD intervention, yet they often face significant provider shortages and logistical barriers. We conducted a retrospective chart review of 842 unique patients (1,321 treatment episodes) enrolled in the University of Marylands tele-buprenorphine program across six rural county jails between June 2020 and May 2025. Data extracted from jail records and electronic health records were used to analyze patient demographics, prescribing patterns, and program retention. RESULTSThe patient population was primarily male (71.1%) and White (75.7%), with a mean age of 35.4 years. Participants reported high-severity OUD, with an average of 12.6 years of opioid use. Reflecting broad admission criteria, 55.2% of participants were new treatment initiates not receiving MOUD prior to booking. Patients spent a mean of 35.6 days incarcerated before initiation and were retained in the program for an average of 66 days. Buprenorphine doses were titrated from a mean initiation dose of 8.8 mg to 16.2 mg at discharge. The program demonstrated a 99.5% adherence rate among retained patients. Only 3% of the total sample were discharged for medication diversion or hoarding. CONCLUSIONSTelemedicine is a highly feasible and scalable model for delivering evidence-based MOUD in rural jails. By utilizing a "liberal admission policy" that prioritizes both treatment initiation and maintenance, programs can successfully reach high-risk individuals who lack access to community-based care. These findings suggest that tele-buprenorphine can effectively bridge the treatment gap in underserved jurisdictions, potentially reducing the risk of overdose during the high-risk post-release period.

BackgroundBetween 1979 and 2016, US overdose death rates rose in a smooth fashion, described by Jalal and Burke using an exponential growth curve that fit observed data nearly perfectly. Fluctuations above this curve have subsequently been seen during shocks related to drug supply and the COVID-19 pandemic. However, large-magnitude dips below the curve have never been demonstrated. Given that overdose mortality began sharply falling during 2023-2024, we assess updated overdose trends against the Jalal-Burke curve. MethodsWe examined US overdose deaths from the National Vital Statistics System between January 1979-December 2024. We recreated the Jalal-Burke curve, fitting an exponential growth curve to overdose rates from 1979 to 2016, linearly projecting through 2024, with 95% confidence intervals. We also examined trends by specific substance involvement. ResultsAfter precipitously surpassing exponential growth predictions in 2020-2023, overdose deaths decreased sharply from approximately 32 per 100,000 in 2021-2023 to 23.7 in 2024, falling below the lower bound of Jalal-Burke curve (24.98 per 100,000) for the first time since 2001. These decreases reflected declining illicit fentanyl-involved deaths (with and without stimulants); however, deaths involving stimulants without fentanyl, and those involving xylazine, represent an increasing share of deaths in 2024. ConclusionsRather than simply representing a return to the Jalal-Burke exponential growth curve, recent decreases in overdose deaths represent the first significant, large-magnitude deviation below exponential growth projections. These trends represent a very positive development. However, challenges in the US drug crisis are shifting, requiring a tailored public health response.

AimsTo characterize decreases in overdose mortality in the United States between 2023 and 2024 by substance involvement, geography, race/ethnicity, demographic, and other key dimensions. DesignPopulation-based study of national death records. SettingUnited States. Participants/casesAll individuals who died from drug overdose between January 1999 and December 2024. MeasurementsAnnual or monthly (annualized) overdose deaths per 100,000 population. Year and month of occurrence of overdose death; substance involvement; census region and division; state; county; race/ethnicity, age, and sex. FindingsAfter over two decades of mostly exponential increases, monthly data show consistent decreases in overdose deaths between June 2023 and December 2024. Decreases reflected declining illicit fentanyl-involved deaths (with and without stimulants); however, increasing trends through 2024 were still seen in deaths involving stimulants without fentanyl, and those involving xylazine. Death rates in the Northeast, South and Midwest fell to 19.5, 19.4 and 17.3 per 100,000, respectively, in December 2024, but remained elevated in the West, compared with other regions, at 27.2 per 100,000. Non-Hispanic Black and African Americans had the largest decrease in death rates in 2023-2024 falling 29.3%, but remained elevated at 36.0 per 100,000, compared to the national average of 23.7 per 100,000. Non-Hispanic American Indian and Alaska Native individuals had the highest overdose mortality rate in 2024, at 50.8 per 100,000. ConclusionsRecent decreases in overdose deaths are encouraging and unprecedented. Racial gaps remained large but shrunk by a modest margin. The geography of the overdose crisis has shifted, with the West now the most affected region, which may have implications for the targeting of funding. The nature of the crisis is also shifting, as stimulants and xylazine continue to represent increasingly important public health challenges, and renewed attention to nonfatal aspects of addiction in the US is needed.

PurposeExplore the potential role of a social contagion factor of opioid use disorder by attempting to replicate the exponential rise in opioid overdose mortality rates using agent-based simulation modeling. MethodsWe utilized an agent-based simulation model built using the Framework for Reconstructing Epidemiological Dynamics software to implement the social contagion component. This updated model was run in Allegheny County for a 21-year period for this pilot study. ResultsThe opioid overdose death rate trend was closely replicated by adding the social contagion component to our model. LimitationsThe original model does not account for individual-specific risk factors. Furthermore, our model does not capture the effect of a social contagion on success in treatment. ConclusionsOur findings show that a social contagion component of opioid use disorder is potentially important in understanding the driving factors behind the exponential increase in opioid overdose death rates. There are likely other factors that are also partly responsible for these trends. ImplicationsSocial contagion could help explain the trends in opioid epidemic, but more research is warranted to understand its interaction with other factors, such as age, sex, race, opioid prescription rate etc.

ObjectivesTo examine the extent to which heat-related causes of death are recorded in fatal drug overdoses, how these patterns vary across states and over time, and how overdose characteristics differ between deaths with, versus without, heat involvement recorded. MethodsDeath certificate data for all drug overdose deaths in US residents from 2001 to 2024 (from the National Center for Health Statistics) were analyzed to identify whether a heat-related cause of death was also listed on the death certificate. Joinpoint regression, descriptive statistics, and nonparametric tests were used to examine temporal trends and compare overdose deaths with versus without recorded heat involvement. ResultsIn 2001, fewer than 10 drug overdose deaths with recorded heat involvement were identified, but this number increased to 558 in 2024. From 2013 to 2024, mortality rates increased significantly, with an estimated annual percent change of 30.1 (95% Confidence Interval, 26.5-47.1). The highest mortality rates and numbers of deaths were observed in residents of Arizona and Nevada. American Indian/Alaska Native, Mexican-heritage, and foreign-born populations accounted for larger shares of overdose deaths with, compared to without, heat involvement recorded. A street or highway was more frequently identified as the place of injury in overdose deaths with (18.9%), versus without (2.2%) heat involvement reported. Psychostimulants such as methamphetamine were involved in 85.9% of overdose deaths with, compared to 28.9% without, recorded heat involvement. ConclusionsAlthough representing only a fraction of all overdose deaths, fatal overdoses involving heat exposure have increased markedly over time and disproportionately impact certain states and demographic groups.

IntroductionMedical cannabis use is increasing worldwide, and information about its use could aid clinicians in decision making. A Prescription Drug Monitoring Program (PDMP) is an electronic database designed to track controlled substance (CII-CV) prescriptions; the use evolved to support patient care. We analyzed the perceived impact of cannabis information in the PDMP within an integrated health system in Pennsylvania and state PDMP policies around cannabis. MethodsWe conducted a sub-analysis of 50 semi-structured interview transcripts. Interviews were conducted March-July 2023 with a multidisciplinary group of clinicians and administrators to understand cannabis use documentation. Twenty-four participants were asked if cannabis in the PDMP would impact their work. Additionally, we asked PDMP administrators of 50 US states and the District of Columbia (D.C.) if cannabis is in their PDMP. If yes, we inquired about software, timeframe, and data sharing. ResultsAlmost two-thirds of 26 participants (N = 17, 65.4%) believed cannabis in the PDMP would positively impact patient care. Fifty states and D.C. replied to our survey. Six states (i.e., CT, LA, NY, OH, MS, and VA) have medical cannabis dispensations. Four states (i.e., AZ, IL, ND, and UT) have a medical cannabis card indicator in the PDMP. Conclusions: Participants perceive medical cannabis in the PDMP could enhance clinical decisions, but inclusion requires policy changes in 40 states and D.C. Rescheduling of cannabis could accelerate adoption of medical cannabis into the PDMP. The PDMP is an underutilized tool that could provide crucial information to clinicians, but substantial policy changes are necessary. HighlightsO_LIUnrecognized drug interactions with cannabis can be harmful C_LIO_LIMinimal research exists on the impact on patient care with cannabis in the PDMP C_LIO_LIThis research offers an examination of state legislation to patient care C_LIO_LIClinicians suggest medical cannabis in the PDMP could benefit patient care C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/25332003v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@44ebdorg.highwire.dtl.DTLVardef@cd6dcaorg.highwire.dtl.DTLVardef@e31c79org.highwire.dtl.DTLVardef@6282c1_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO Themes from clinician interviews and heat map showing the ten states that have medical cannabis in their Prescription Drug Monitoring Program (PDMP) along with the characteristics of other states. Cannabidiol: CBD; Kansas: KS: Idaho: ID; Tetrahydrocannabinol: THC. C_FIG

Background and aimsExtended release buprenorphine injection (INJ-BUP) has been available in the United States since 2018. INJ-BUP has the potential to positively impact OUD treatment outcomes by providing additional treatment options and patient choice. We aimed to describe the availability and prescribing of INJ-BUP for Medicaid beneficiaries since its availability, nationwide and by state. MethodsTo assess availability, we measured the number of substance use disorder (SUD) facilities that offered INJ-BUP and accepted Medicaid insurance in 2018-2021 and calculated the percentage of all facilities offering medications of OUD. To assess prescribing, we measured the number of prescriptions for INJ-BUP paid by Medicaid 2018-2022 and calculated the percentage of all buprenorphine prescriptions paid by Medicaid. Data sources were publicly available. ResultsThe number of facilities that offered INJ-BUP and accepted Medicaid insurance increased from 360 (2.5% of all SUD facilities offering medication) in 2018 to 2,257 (13.3%) in 2021. The number of prescriptions for INJ-BUP paid by Medicaid increased from 4,322 (0.1% of all buprenorphine prescriptions) in 2018 to 186,861 (2.0%) in 2022. There was notable variability in the number of facilities and prescriptions by state. ConclusionsThere has been exponential increase in the number of INJ-BUP prescriptions but uptake is much less than observed in other countries in shorter time periods. Limited availability at SUD treatment facilities that accept Medicaid may be one barrier to access.

BackgroundIn a profound reversal of prior trends, U.S. drug overdose deaths declined by 26.9% in 2024. Two proposed explanations are: (1) expansion of prevention, treatment, and harm-reduction infrastructure and (2) changes in the illicit fentanyl supply. This study evaluated which hypothesis best aligns with observed changes in drug involvement in overdose mortality. MethodsCDC WONDER multiple-cause-of-death data for 2023 and 2024 were analyzed using complementary approaches. In a preliminary analysis, overdose deaths involving cocaine, methamphetamine, prescription opioids, heroin, and methadone were stratified by fentanyl involvement, and 2024/2023 mortality rate ratios were calculated. The primary analysis used a parsimonious 2x2 design (year x fentanyl involvement) to estimate differential mortality changes. A secondary analysis classified deaths into mutually exclusive strata defined by fentanyl, non-fentanyl opioid, and stimulant involvement, and estimated year-by-drug interaction effects using log-linear Poisson regression. ResultsBetween 2023 and 2024, fentanyl-involved deaths declined by 36.5%; non-fentanyl-involved deaths declined by only 5.3% (p < 0.001). Regression models identified a large year x fentanyl interaction (RR = 0.65), consistent with a fentanyl-specific decline. In contrast, non-fentanyl opioid-involved (RR = 1.04) and stimulant-involved deaths (RR = 1.03) exhibited small relative increases. ConclusionsThe 2023-2024 decline in overdose mortality was confined to fentanyl-involved deaths. These findings are most consistent with supply-side changes affecting fentanyl toxicity rather than more uniform effects of infrastructure expansion. Continued investment in prevention and surveillance, with attention to potential market adaptation toward highly potent synthetic opioids, remains essential.

BackgroundRecreational cannabis legalization has expanded rapidly across US states. The regulatory approaches states adopt vary widely, with varying implications for public health. This study aimed to characterize heterogeneity in recreational cannabis laws (RCLs) across US states and to identify state-level characteristics associated with these regulatory models. MethodsWe conducted Latent Class Analysis (LCA) of state-year RCL provisions from 2013 to 2024 (n=612) to identify distinct RCL approaches. Descriptive analyses and exploratory multinomial regression analyses were used to examine correlations between state characteristics and RCL approaches from 2020 to 2024, when sufficient cross-state variation in RCL adoption was available. Eleven recreational cannabis policy provisions spanning governance, potency limits, consumption restrictions, access controls, taxation, marketing regulations, and driving prohibitions are primarily from the Alcohol Policy Information System. State-level characteristics included cannabis use prevalence, market conditions, medical cannabis history, political factors, demographic, and socioeconomic covariates obtained from multiple secondary data sources. ResultsWe identified four latent classes of state-year RCL provisions representing different regulatory approaches: No RCL, Pre-commercial, Full Access, and Dispensary Access. The No RCL corresponded to state-years without RCL. The Pre-commercial class represented state-years in early-stage legalization with a minimal regulated approach in terms of commercial infrastructure. The Full Access class was characterized by permitting on-site retail consumption and home delivery and restricting (but not prohibiting) public use. In contrast, the Dispensary Access class limited retail sales to off-site consumption only, prohibited public use, and imposed stricter market controls. Higher past-month cannabis use prevalence was associated with a greater likelihood of membership in the Full Access class (RRR = 1.78; 95% CI: 1.21-2.62), relative to No RCL. A longer duration since medical cannabis legalization was associated with a higher likelihood of membership in the Dispensary access class (RRR = 1.47; 95% CI: 1.02-2.12). Higher beer excise taxes were associated with a lower likelihood of membership in any RCL class relative to No RCL. ConclusionsFrom 2013 to 2024, US recreational cannabis regulations clustered into four distinct regulatory approaches, with two distinct commercial models: one permitting on-site retail consumption and home delivery, the other restricting sales to off-premises only and prohibiting public use. Higher cannabis use prevalence and longer medical cannabis history were associated with more access-oriented and more restrictive commercial approaches, respectively.

BackgroundThe COVID-19 pandemic amplified the risk environment for people who inject drugs (PWID), making continued access to harm reduction services imperative. Research has shown that some harm reduction service providers were able to continue to provide services throughout the pandemic. Most of these studies, however, focused on staff perspectives, not those of PWID. Our study examines changes in perceptions of access to harm reduction services among PWID participating in a longitudinal study conducted through the University of Illinois-Chicagos Community Outreach Intervention Project field sites during the COVID-19 pandemic. MethodsResponses to a COVID-19 module added to the parent study survey that assessed the impact of COVID-19 on PWID participating in an ongoing longitudinal study were analyzed to understand how study participants self-reported access to harm reduction services changed throughout the pandemic. Mixed effects logistic regression was used to examine difficulty in syringe access as an outcome of COVID-19 phase. ResultsMost participants reported that access to syringes and naloxone remained the same as prior to the pandemic. Participants had significantly higher odds of reporting difficulty in accessing syringes earlier in the pandemic. ConclusionsThe lack of perceived changes in harm reduction access by PWID and the decrease in those reporting difficulty accessing syringes as the pandemic progressed suggests the efficacy of adaptations to harm reduction service provision (e.g., window and mobile service) during the pandemic. Further research is needed to understand how the COVID-19 pandemic may have impacted PWIDs engagement with harm reduction services.

IntroductionDrug abuse has reached alarming levels in Nigeria, with systemic vulnerabilities exacerbating the crisis. This systematic review evaluates the prevalence and patterns of drug abuse, examines the impact of collective actions and inactions, and identifies socio-economic and gender-specific barriers to treatment. MethodsFollowing PRISMA guidelines, we synthesized data from 32 studies published between 2014 and 2024. Inclusion criteria focused on drug abuse in Nigeria, comprising observational, qualitative, and mixed-methods studies. Data extraction encompassed study details, methodologies, key findings, and quality assessments via the Mixed Methods Appraisal Tool (MMAT). ResultsThe pooled prevalence of drug abuse stands at 14.4% among individuals aged 15-64, with significant regional disparities. Urban areas, particularly among youth, exhibited higher rates of opioid misuse, driven by poverty and accessibility. Policy inaction, exemplified by underfunded rehabilitation services, and stigma further compound the issue. Gender-specific barriers, particularly for women, are marked by stigma, lack of childcare support, and socio- economic vulnerabilities. Collective actions have shown some success, yet limited implementation undermines overall impact. ConclusionThe review highlights a pressing need for coordinated efforts across sectors to combat drug abuse effectively. Addressing systemic issues such as poverty, stigma, and inadequate healthcare access is crucial. Implementing the National Drug Control Master Plan and prioritizing gender-sensitive policies will enhance treatment accessibility. Collaborative initiatives must focus on education, stigma reduction, and integrated healthcare to reverse the devastating trends of drug abuse in Nigeria.

BackgroundDrug overdose deaths have surged over the past two decades, disproportionately impacting racial/ethnic minority populations. Yet, little is known about drug overdose patterns among Asian American and Native Hawaiian/Pacific Islander (AANHPI) populations. MethodsWe obtained data on drug overdose deaths and population totals from the CDC WONDER Multiple Cause of Death database and American Community Survey between 2018 and 2022. We calculated crude mortality rates per 100,000, stratified by sex, US Census Division, and drug types--prescription opioids, heroin, fentanyl, cocaine, methamphetamine, and benzodiazepines. Additionally, we conducted disaggregated analyses for six Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese) and three NHPI subgroups (Hawaiian, Guamanian, Samoan). ResultsIn 2022, there were 1226 drug overdose deaths among Asian Americans and 154 among NHPI individuals. The crude mortality rate for NHPI individuals (17.52 per 100,000; 95% CI: 14.76- 20.29) tripled that of Asian Americans (5.85 per 100,000; 95% CI: 5.52-6.18). Fentanyl was the leading cause of overdose deaths among Asian Americans (3.17 per 100,000; 95% CI: 2.93- 3.41), whereas methamphetamine was predominant among NHPI individuals (11.38 per 100,000; 95% CI: 9.15-13.61). Among Asian American subgroups, Japanese Americans had the highest mortality rate (9.90 per 100,000; 95% CI: 9.61-10.2), and among NHPI subgroups, Guamanians had the highest rates (43.16 per 100,000; 95% CI: 39.05-48.24). ConclusionsThese findings underscore the urgent need for culturally competent harm reduction services, mental health and addiction treatment, and social services, addressing structural barriers that perpetuate drug overdose disparities in AANHPI communities.

Opioid-related deaths are a national problem that have increased over the past two decades. Multiple policy interventions have been enacted to decrease opioid misuse and expand treatment. The Comprehensive Addiction and Recovery Act (CARA) was passed in July 2016, just before declaring the opioid epidemic a National Emergency in 2017. CARA was enacted to combat the opioid epidemic by providing more funding yearly for items including but not limited to prevention, treatment, and opioid overdose reversal. To evaluate the impact of these policy changes, we carried out secondary data analysis for the period 2011-2019 using the CDCs Wide-ranging Online Data for Epidemiologic Research and National Survey of Substance Abuse Treatment Services databases. Research variables included: a comparison of the 50 states across the 2011-2019 timeframe, the number of opioid treatment centers, the percentage of government funding for facilities per state, percentage of opioid treatment facilities which offer free/low-income services and the opioid death rate. We also assessed differences in low-income access to opioid treatment services by comparing Medicaid expansion states versus non-Medicaid expansion states. While both the number of treatment facilities per state and opioid death rates nearly doubled during this time, there was little to no association between them (R2 ranging from: 0.094-0.188 for years 2013-2019). Our research suggests that while state-level differences in opioid use disorder treatment facility characteristics related to access to care, they were only weakly associated with opioid-related deaths. This analysis may be used in the planning of subsequent actions against the national opioid epidemic and invites further inquiry into the impact of state Medicaid expansion on drug-specific opioid usage and mortality.

In 2017, the Acting U. S. Secretary of Health and Human Services declared the "opioid crisis" a nation-wide health emergency. However, the crisiss geography was not nation-wide. Many counties and towns had no overdose deaths, whereas others were home to hundreds. According to many influential research reports and news stories, geographic variation in overdose deaths was due to geographic variation in opioid prescription rates and/or geographic variation in socioeconomic factors, such as unemployment. Our goal was to test the degree to which prescription rates and socioeconomic correlates of income inequality predicted overdose deaths in the 1055 U.S. Midwest ("Heartland") counties over the years 2006 to 2020. We used multilevel regression models to gauge the predictive strength of overdose rates and six socioeconomic measures that are correlated with income inequality. There were significant state-level and county-level differences. Intergenerational income mobility was the strongest predictor of overdose deaths, with regression coefficients that averaged about twice as large as the coefficients for opioid prescription rates. Every year, counties with greater upward intergenerational income mobility had lower overdose death rates. Social capital had the second largest regression coefficients, albeit by a small margin. Counties are the smallest demographic unit for which drug overdose rates are available; the results of this study link growing income inequality and drug overdose deaths at the county level.

Opioid use disorder (OUD) is a major public health concern in the United States (US), resulting in high rates of overdose and other negative outcomes. Methadone, a treatment for OUD, has been shown to be effective in reducing the risk of overdose and improving overall health and quality of life. This study analyzed the distribution of methadone for the treatment of OUD across the US using data from the Drug Enforcement Administrations Automated Reports and Consolidated Ordering System, Medicaids State Drug Utilization Data, and the US Census Bureau. Analysis revealed that methadone distribution for OUD has expanded significantly over the past decade, with an average state increase of +96.96% from 2010 to 2020, and there was a significant increase in overall distribution of methadone to opioid treatment programs (OTP) in the US from 2010 to 2020 (+61.00%) and from 2015 to 2020 (+26.22%). However, the distribution to OTPs did not significantly change from 2019 to 2021 (-5.15%). Furthermore, pronounced variation in methadone distribution among states were observed, with some states having no OTPs or Medicaid coverage. New policies are urgently needed to increase access to methadone treatment and address the opioid overdose crisis in the US.

This study explored whether law enforcement/first responder-reported fentanyl overdose response actions (such as administration of the opioid overdose reversal agent naloxone) differed between overdoses in which xylazine was, versus was not, suspected to be co-involved. Data were drawn from the Pennsylvania State Polices Overdose Information Network (ODIN) for 11,478 suspected fentanyl-involved overdoses, 137 reportedly co-involving xylazine, recorded across Pennsylvania, excluding Philadelphia, January 2018-January 16, 2025. We used relative frequencies, Fishers exact tests, and binomial logistic regression to compare first responders overdose response actions in suspected fentanyl overdoses cases in which xylazine was, versus was not, reportedly co-involved. Naloxone was administered at the scene of 46.0% of the overdoses reportedly involving fentanyl and xylazine, vs. 67.3% of the reported fentanyl-no-xylazine overdoses. Multivariable regression results (among the suspected fentanyl overdoses in ODIN, adjusting for age, sex, race/ethnicity, year, county rurality, and other drugs suspected to be involved) indicated that suspected xylazine co-involvement was associated with 60% lower odds of naloxone administration (Adjusted Odds Ratio, 0.40; 95% Confidence Interval, 0.28-0.57). Observed differences in overdose response based on suspected xylazine co-involvement support the importance of equipping first responders with the tools and training to recognize/manage the distinct challenges of xylazine-fentanyl-involved overdose.