Sharp Increases in Drug Overdose Deaths Among High-School-Age Adolescents During the US COVID-19 Epidemic and Illicit Fentanyl Crisis

Although overdose deaths in the US have increased exponentially for the past four decades, these shifts have historically affected adults, while pediatric overdose rates remained stable. However, this may be changing, given that the illicit drug supply has become increasingly hazardous in recent years, as illicitly-manufactured-fentanyls (IMFs) and other synthetic opioid and benzodiazepine analogues are increasingly sold as heroin and counterfeit prescription pills. We calculated drug overdose deaths per 100,000 population by 5-year age groups for the 2010-2021 period. For high-school-aged adolescents (age 14-18), we stratified rates by race/ethnicity, census region, associated substance, and ICD-10 cause-of-death intent categories. Adolescent overdose mortality saw a sharp increase between 2019 and 2020, from 2.35 per 100,000 to 4.58 per 100,000, representing a 94.3% increase, the largest percent increase of any 5-year age group. American Indian or Alaska Native (AIAN) adolescents, Latinx adolescents, and adolescents in the West census region were disproportionately affected, overdose death rates 2.15, 1.31, and 1.68 times the national average in 2021, respectively. Trends were driven by fatalities involving IMFs, which nearly tripled from 2019 to 2020, and represented 76.6% of adolescent overdose deaths in 2021. Sharp increases in adolescent drug overdose deaths, despite flat or declining drug use rates, and no increase in deaths from alcohol or most drugs, reinforce that rising fatalities are likely driven by an increasingly toxic, IMF-contaminated drug supply. Rising racial disparities in overdose require a prevention approach that ameliorates deep-seated social and economic inequalities as well as poor access to mental and physical healthcare and social services for AIAN and Latinx adolescents. Our results should also be understood in the context of rising rates of adolescent mental illness during the COVID-19 pandemic. These findings highlight the urgent need for accurate, harm-reduction-oriented education for early adolescents about the risks of an evolving drug supply, as well as greater access to naloxone and services that check drugs for the presence of IMFs.

Black and Native Overdose Mortality Overtook that of White Individuals During the COVID-19 Pandemic

Drug overdose mortality rates have increased sharply during the COVID-19 pandemic. In recent years, overdose death rates were rising most rapidly among racial/ethnic minority communities. The pandemic has disproportionately affected communities of color in a wide swath of health, social, and economic outcomes. Careful attention is therefore warranted to trends in overdose mortality by race/ethnicity during COVID-19. We calculated total drug overdose death rates per 100,000 population by race/ethnicity for the 1999-2020 time period. We find that Black overdose mortality overtook that of White individuals in 2020 for the first time since 1999. Between 2019 and 2020 Black individuals had the largest percent increase in overdose mortality, of 48.8%, compared to 26.3% among White individuals. In 2020, Black overdose death rates rose to 36.8 per 100,000, representing 16.3% higher than the rate for White individuals for the same period. American Indian and Alaska Native (AI/AN) individuals experienced the highest rate of overdose mortality in 2020, of 41.4 per 100,000, representing 30.8% higher than the rate among White individuals. Our findings suggest that drug overdose mortality is increasingly becoming a racial justice issue in the United States and appears to have been exacerbated by the COVID-19 pandemic. Providing individuals with a safer supply of drugs, closing gaps in access to MOUD and harm reductions services, and ending routine incarceration of individuals with substance use disorders represent urgently needed, evidence-based strategies that can be employed to reduce rising inequalities in overdose.

Predictive performance of international COVID-19 mortality forecasting models

BackgroundForecasts and alternative scenarios of the COVID-19 pandemic have been critical inputs into a range of important decisions by healthcare providers, local and national government agencies and international organizations and actors. Hundreds of COVID-19 models have been released. Decision-makers need information about the predictive performance of these models to help select which ones should be used to guide decision-making. MethodsWe identified 383 published or publicly released COVID-19 forecasting models. Only seven models met the inclusion criteria of: estimating for five or more countries, providing regular updates, forecasting at least 4 weeks from the model release date, estimating mortality, and providing date-versioned sets of previously estimated forecasts. These models included those produced by: a team at MIT (Delphi), Youyang Gu (YYG), the Los Alamos National Laboratory (LANL), Imperial College London (Imperial) the USC Data Science Lab (SIKJalpha), and three models produced by the Institute for Health Metrics and Evaluation (IHME). For each of these models, we examined the median absolute percent error--compared to subsequently observed trends--for weekly and cumulative death forecasts. Errors were stratified by weeks of extrapolation, world region, and month of model estimation. For locations with epidemics showing a clear peak, each models accuracy was also evaluated in predicting the timing of peak daily mortality. ResultsAcross models, the median absolute percent error (MAPE) on cumulative deaths for models released in June rose with increased weeks of extrapolation, from 2.3% at one week to 32.6% at ten weeks. Globally, ten-week MAPE values were lowest for IHME-MS-SEIR (20.3%) and YYG (22.1). Across models, MAPE at six weeks were the highest in Sub-Saharan Africa (55.6%), and the lowest in high-income countries (7.7%). Median absolute errors (MAE) for peak timing also rose with increased forecasting weeks, from 14 days at one week to 30 days at eight weeks. Peak timing MAE at eight weeks ranged from 24 days for the IHME Curve Fit model, to 48 days for LANL. InterpretationFive of the models, from IHME, YYG, Delphi, SIKJalpha and LANL, had less than 20% MAPE at six weeks. Despite the complexities of modelling human behavioural responses and government interventions related to COVID-19, predictions among these better-performing models were surprisingly accurate. Forecasts and alternative scenarios can be a useful input to decision-makers, although users should be aware of increasing errors with a greater amount of extrapolation time, and corresponding steadily widening uncertainty intervals further in the future. The framework and publicly available codebase presented can be routinely used to evaluate the performance of all publicly released models meeting inclusion criteria in the future, and compare current model predictions.

Excess Out-Of-Hospital Mortality and Declining Oxygen Saturation Documented by EMS During the COVID-19 Crisis in Tijuana, Mexico

ObjectiveEmergency medical services (EMS) may serve as a key source of real-time data about the evolving health of COVID-19 affected populations, especially in low-and-middle-income countries (LMICs) with less rapid and reliable vital statistic registration systems. Although official COVID-19 statistics in Mexico report almost exclusively in-hospital mortality events, excess out-of-hospital mortality has been identified in other settings, including one EMS study in Italy that showed a 58% increase. EMS and hospital reports from several countries have suggested that silent hypoxemia--low oxygen saturation (SpO2) in the absence of dyspnea--is associated with COVID-19 outbreaks. It is unclear, however, how these phenomena can be generalized to LMICs. We assess how EMS data can be used in a sentinel capacity in Tijuana, a city on the Mexico-United States border with earlier exposure to COVID-19 than many LMIC settings. MethodsWe calculated numbers of weekly out-of-hospital deaths and respiratory cases seen by EMS in Tijuana, and estimate the difference between peak-epidemic rates (during April 14th-May 11th) and forecasted 2014-2019 trends. Results were compared with official COVID-19 statistics, stratified by neighborhood socioeconomic status (SES), and examined for changing demographic or clinical features, including mean (SpO2). ResultsAn estimated 194.7 (95%CI: 135.5-253.9) excess out-of-hospital deaths events occurred, representing an increase of 145% (70%-338%) compared to forecasted trends. During the same window, only 8 COVID-19-positive, out-of-hospital deaths were reported in official statistics. This corresponded with a rise in respiratory cases of 274% (119%-1142%), and a drop in mean SpO2 to 77.7%, from 90.2% at baseline. The highest out-of-hospital death rates were observed in low-SES areas, although respiratory cases were more concentrated in high-SES areas. ConclusionsEMS systems may play an important sentinel role in monitoring excess out-of-hospital mortality and other trends during the COVID-19 crisis in LMICs. Using EMS data, we observed increases in out-of-hospital deaths in Tijuana that were nearly threefold greater magnitude than increases reported using EMS data in Italy. Increased testing in out-of-hospital settings may be required to determine if excess mortality is being driven by COVID-19 infection, health system saturation, or patient avoidance of healthcare. We also found evidence of worsening rates of hypoxemia among respiratory patients seen by EMS, suggesting a rise in silent hypoxemia, which should be met with increased detection and clinical management efforts. Finally, we observed that social disparities in out-of-hospital death that warrant monitoring and amelioration.

Planning an intersectoral network of healthcare and community leaders to advance trans-affirming care for sexual assault survivors.

Sexual assault against transgender (trans) persons is a complex public health issue requiring the coordinated effort of multiple sectors to address. In response to a global call to improve health equity for persons of diverse gender identities, leaders across health and social service sectors need to enhance collaboration to champion trans-affirming care for sexual assault survivors. In collaboration with Egale Canada Human Rights Trust and the Ontario Network of Sexual Assault/Domestic Violence Treatment Centres, we have undertaken the development of an intersectoral network to connect trans-positive community organizations with hospital-based violence treatment centres to improve support services for trans survivors across Ontario. Guided by the Lifecycle Model for network development outlined by the National Collaborating Centre for Methods and Tools, we describe our approach to planning the intersectoral network, including key insights learned thus far and the potential of the network moving forward.