Estimating Weekly National Opioid Overdose Deaths in Near Real Time Using Multiple Proxy Data Sources

Which Social Media Platforms Provide the Most Informative Data for Monitoring the Opioid Crisis?

Background and Aims

Social media can provide real-time insight into trends in substance use, addiction, and recovery. Prior studies have leveraged data from platforms such as Reddit and X (formerly Twitter), but evolving policies around data access have threatened their usability in opioid overdose surveillance systems. Here, we evaluate the potential of a broad set of platforms to detect emerging trends in the opioid crisis.

Design

We identified 72 online platforms with a substantial global user base or prior citations in opioid-related research. We evaluated each platform's fit with our definition of social media, size of North American user base, and volume of opioid-related discourse. We created a shortlist of 11 platforms that met our criteria. We documented basic characteristics, volume and nature of opioid discussion, official policies regulating drug-related discussion, and data accessibility of shortlisted platforms.

Setting

USA and Canada.

Measurements

We quantified the volume of opioid discussion by number of platform-specific Google search hits for opioid terms. We captured informal language by including slang generated using a large language model. We report the number of opioid-related hits and proportion of opioid-related hits to hits for common nouns.

Findings

We found that TikTok, YouTube, and Facebook have the most potential for use in opioid-related surveillance. TikTok and Facebook have the highest relative amount of drug-related discussions. Language on TikTok was predominantly informal. Many platforms offer data access tools for research, but changing company policies and user norms create instability. The demographics of users varies substantially across platforms.

Conclusions

Social media data sources hold promise for detecting trends in opioid use, but researchers must consider the utility, accessibility, and stability of data on each platform. A strategy mixing several platforms may be required to cover all demographics suffering in the epidemic.

National and regional trends in fentanyl seizures in the United States, 2017-2023

BACKGROUND

Rates of synthetic opioid-related deaths over time and across regions have been compared within the US, but other indicator data could help inform prevention and harm reduction as well. We compared regional trends in fentanyl seizures to examine potential shifts in illicit fentanyl availability.

METHODS

Annual trends in fentanyl seizures were examined using data from High Intensity Drug Trafficking Areas for the US overall and by region from 2017 through 2023. Multiple measures included the number of seizures, the number of powder seizures, the number of pill seizures, the total weight of seizures, the number of pills seized, and the percentage of the number of pill seizures relative to the number of total seizures.

RESULTS

The percentage of seizures in pill form in the US increased from 10.3 % in 2017 to 49.0 % in 2023 (adjusted annual percentage change [AAPC]=25.2, 95 % CI: 17.6, 33.2), with 115.6 million individual pills seized in 2023. Pill weight related to total seizure weight also increased from 0.4 % to 54.5 % (AAPC=112.6, 95 % CI: 78.6, 153.2). In 2023, the plurality of seizures was in the West, in seven out of eight of our measures, with 77.8 % of seizures in the West being in pill form. Although the Midwest had lower prevalence of seizures than the West, there were notable increases in the Midwest in the number of pill seizures (AAPC=142.2, 95 % CI: 91.9, 205.8) and number of pills seized (AAPC=421.0, 95 % CI: 272.7, 628.4). Total weight of fentanyl seized increased the most in the West (AAPC=84.6, 95 % CI: 72.3, 97.8).

CONCLUSIONS

The number and size of fentanyl seizures is increasing in the US, with the majority of seizures, especially in pill form, in the West. Continued monitoring of regional shifts in the fentanyl supply can help inform targeted prevention and public health response.

A scoping review of law enforcement drug seizures and overdose mortality in the United States

BACKGROUND

Leveraging law enforcement drug seizure data to better respond to the overdose crisis requires an understanding of available evidence and knowledge gaps regarding relationships between drug seizures and overdose mortality.

OBJECTIVE

This scoping review summarized peer-reviewed literature on associations between law enforcement drug seizures and drug-related mortality in the United States (US) in the era of illicitly-manufactured fentanyl, comparing study data sources, measures, methodologies, settings, and findings.

METHODS

We identified 388 non-duplicate records from three online databases searched on May 23, 2023. After title/abstract and full-text screening by two independent reviewers, 14 studies met the criteria for inclusion. The included studies tested the association between a measure related to law enforcement drug seizures and an overdose mortality outcome in the US and were published in English, in peer-reviewed journals, during or after 2013.

RESULTS

Four of 14 studies (29%) included data from the entire US, while the remaining studies focused on an individual state/city/county or a group of states/cities/counties. Synthetic opioid/fentanyl seizures represented the most frequently examined drug seizure category, and overdose deaths overall (involving any drugs) represented the most frequently examined outcome. Most studies used counts/rates of drug seizures, with fewer studies examining dosage/weight, drug combinations, the proportion of drug seizures involving a specific drug, or spatiotemporal distribution. The majority (86%) of studies reported at least one statistically significant positive association between a law enforcement drug seizure measure and an overdose mortality outcome, most consistently for fentanyl-related seizures. Results were relatively less consistent for seizures involving stimulants and other drugs.

CONCLUSIONS

Studies in this review provided consistent evidence that fentanyl-related seizure measures are positively associated with overdose mortality outcomes, despite the limitations inherent in drug seizure data, even in the absence of available information regarding seizure weight or dosage.

Drug supply measures and drug overdose mortality in the era of fentanyl and stimulants

Background

Illicitly-manufactured fentanyl and stimulants have replaced prescription opioids as the primary contributors to fatal overdoses in the United States (US), yet the street supply of these substances is challenging to quantify. Building on the foundation of prior research on law enforcement drug reports, the present study compares publicly available forensic laboratory drug report measures to identify which measures account for the most variation in drug overdose mortality between states, within states over time, and in various demographic groups.

Methods

Drug reports from the National Forensic Laboratory Information System and drug overdose mortality rates from the Centers for Disease Control and Prevention were examined for all US states and the District of Columbia, 2013-2021 (459 state-years). State- and year- fixed effects models regressed drug overdose mortality rates (in the overall population and subpopulations by sex, age, and race/ethnicity) on various drug report measures, including rates per population and proportional shares of drug reports positive for fentanyl/fentanyl-related compounds, heroin, cocaine, methamphetamine, and xylazine.

Results

For drug overdose death rates in the overall population and nearly all subpopulations examined by sex, race/ethnicity, and age, the model including all drug report proportional measures represented the best-performing model (as identified via the lowest Akaike Information Criterion and highest within R-squared value), followed by the model including only the fentanyl/fentanyl-related compounds proportion.

Conclusions

Findings support the utility of publicly available drug report composition measures, particularly the proportion of fentanyl/fentanyl-related compounds, as predictors of drug overdose mortality in the US and in various subpopulations.

Estimating national and state-level suicide deaths using a novel online symptom search data source

BACKGROUND

Suicide mortality data are a critical source of information for understanding suicide-related trends in the United States. However, official suicide mortality data experience significant delays. The Google Symptom Search Dataset (SSD), a novel population-level data source derived from online search behavior, has not been evaluated for its utility in predicting suicide mortality trends.

METHODS

We identified five mental health related variables (suicidal ideation, self-harm, depression, major depressive disorder, and pain) from the SSD. Daily search trends for these symptoms were utilized to estimate national and state suicide counts in 2020, the most recent year for which data was available, via a linear regression model. We compared the performance of this model to a baseline autoregressive integrated moving average (ARIMA) model and a model including all 422 symptoms (All Symptoms) in the SSD.

RESULTS

Our Mental Health Model estimated the national number of suicide deaths with an error of -3.86 %, compared to an error of 7.17 % and 28.49 % for the ARIMA baseline and All Symptoms models. At the state level, 70 % (N = 35) of states had a prediction error of <10 % with the Mental Health Model, with accuracy generally favoring larger population states with higher number of suicide deaths.

CONCLUSION

The Google SSD is a new real-time data source that can be used to make accurate predictions of suicide mortality monthly trends at the national level. Additional research is needed to optimize state level predictions for states with low suicide counts.

MedSMA℞T Adventures in PharmaCity Game: Youth Experiences and Recommendation for Use in Opioid Safety Education

Adolescents are often excluded from the creation of opioid safety interventions; therefore, it is crucial to design evidence-based interventions tailored for and with youth. Video games are ubiquitous and approachable to adolescents making them an accessible educational modality. MedSMA℞T: Adventures in PharmaCity is a serious game that educates adolescents and their families on the safe, appropriate, and responsible use of opioid prescriptions. The first objective of the study was to elucidate adolescents' experiences and perceptions of the game. The second objective was to elicit their recommendations for use and suggestions for improvement. Adolescents were recruited through Qualtrics research panels, social media, listservs, and snowball sampling. Recruitment occurred between April 2021 and October 2021. Eligible adolescents played the game and completed a follow-up virtual semi-structured interview with a study team member. Interviews were transcribed verbatim and uploaded to NVivo for data analysis. A thematic content analysis was performed. A total of seventy-two adolescents participated. Analysis yielded four themes: prior gaming experience, educational salience, game design impressions, and recommendations for improvement. Most adolescents approached MedSMA℞T with prior gaming experience. The youth correctly identified the game's intended objective: the promotion of opioid medication safety. Adolescents had overarchingly positive impressions of the game's levels, characters, and graphics. Study participants suggested expanded game levels, improved controls, and more instructions for gameplay. In summary, adolescents had favorable experiences using the MedSMA℞T game which allude to the wide-spread acceptability of this intervention among young people.

Associations between opioid overdose deaths and drugs confiscated by law enforcement and submitted to crime laboratories for analysis, United States, 2014-2019: an observational study

Background

The overdose epidemic in the United States (US) continues to generate unprecedented levels of mortality. There is urgent need for a national data system capable of yielding high-quality, timely, and actionable information on existing and emerging drugs. Public health researchers have started using law enforcement forensic laboratory data to obtain surveillance information on illicit drugs. This study is the first to use drug reports from the entire US to examine correlations between a changing drug supply and increasing opioid-involved overdose deaths (OOD) on a national scale.

Methods

This study is observational and investigates associations between law enforcement drug reports and OOD for the US from 2014 to 2019. OOD data are from the Centers for Disease Control and Prevention's National Vital Statistics System restricted-use multiple cause of death files. The US Drug Enforcement Administration's National Forensic Laboratory Information System (NFLIS) contains forensic laboratory-tested drug exhibit information for the entire US (NFLIS-Drug). Counts of forensic laboratory reports and OOD were aggregated for each state by month, quarter, and year. A difference-in-differences framework was used to estimate contemporaneous and lagged associations.

Findings

Between 2014 and 2019 in the US, 249,522 OOD were reported, with the annual number nearly doubling from 28,723 to 50,179. OOD involving illicitly manufactured fentanyls (IMF) also increased substantially during this period, from 19.4% to 72.9%. In addition, 3,817,438 forensic laboratory reports in the US that were reported to NFLIS-Drug contained an opioid, stimulant, or benzodiazepine. Reports of fentanyl and fentanyl-related compounds (FFRC) had the strongest association with OOD. Each additional FFRC exhibit was associated with a 2.97% (95% CI: 1.7%, 4.1%) increase in OOD per 100,000 persons per quarter.

Interpretation

Adding to the emerging consensus, protracted growth in IMF supply was more strongly associated with OOD than all other illicit drugs reported to NFLIS-Drug over the study time period. Findings demonstrate NFLIS-Drug data usefulness for research that require proxy indicators for the illicit drugs supply. A concerted effort between public health and public safety to make NFLIS-Drug more timely could strengthen its utility as a national, public health, drug surveillance system.

Funding

Sangeetha Arctic Slope Mission Services, LLC, ASMS Contract No. ASM5-00017.

Xylazine in Drug Seizure Reports and Overdose Deaths in the US, 2018-2022

Xylazine is increasingly reported in street drugs and fatal overdoses in the United States (US), often in combination with synthetic opioids, yet state-level xylazine data are limited, hampering local public health responses. The present study analyzed 2018-2022 state-level data from the National Forensic Laboratory Information System (xylazine-positive reports of seized drugs analyzed by forensic laboratories), the Centers for Disease Control and Prevention (population estimates, synthetic opioid overdose mortality rates), and individual states' medical examiner/public health agency reports (numbers of xylazine-involved overdose deaths). An ordinary least squares regression model predicted state-level synthetic opioid overdose mortality rates by xylazine seizure report rates, adjusting for US Census Region. In 2018, relatively low rates of xylazine seizure reports were observed, with 21 states reporting zero xylazine seizures. In 2022, only three states reported zero xylazine seizures, and the highest xylazine seizure report rates (per 100,000 residents) were observed in New Jersey (30.4), Rhode Island (22.7), Maryland (18.9), Virginia (15.5), New Hampshire (13.0), and Ohio (10.9). Data on 2019-2022 xylazine-involved overdose deaths were available for 21 states/DC (60 state-years), with the highest 2022 xylazine-involved overdose death rates (per 100,000 residents) in Vermont (10.5) and Connecticut (9.8). Finally, in 2021, at the state level, each additional reported xylazine seizure per 100,000 residents was associated with a 2% higher synthetic opioid overdose mortality rate (b=0.02, robust standard error=0.01; p=0.049). Overall, study results emphasize xylazine's increasing involvement in US law enforcement drug seizure reports and overdose deaths, primarily in the East, yet also extending across the country.

Trends in stigmatizing language about addiction: A longitudinal analysis of multiple public communication channels

INTRODUCTION

Stigma associated with substance use and addiction is a major barrier to overdose prevention. Although stigma reduction is a key goal of federal strategies to prevent overdose, there is limited data to assess progress made in reducing use of stigmatizing language about addiction.

METHODS

Using language guidelines published by the federal National Institute on Drug Abuse (NIDA), we examined trends in use of stigmatizing terms about addiction across four popular public communication modalities: news articles, blogs, Twitter, and Reddit. We calculate percent changes in the rates of articles/posts using stigmatizing terms over a five-year period (2017-2021) by fitting a linear trendline and assess statistically significant trends using the Mann-Kendall test.

RESULTS

The rate of articles containing stigmatizing language decreased over the past five years for news articles (-68.2 %, p < 0.001) and blogs (-33.6 %, p < 0.001). Among social media platforms, the rate of posts using stigmatizing language increased (Twitter [43.5 %, p = 0.01]) or remained stable (Reddit [3.1 %, p = 0.29]). In absolute terms, news articles had the highest rate of articles containing stigmatizing terms over the five-year period (324.9 articles per million) compared to 132.3, 18.3, and 138.6 posts per million for blogs, Twitter, and Reddit, respectively.

CONCLUSIONS

Use of stigmatizing language about addiction appears to have decreased across more traditional, longer-format communication modalities such as news articles. Additional work is needed to reduce use of stigmatizing language on social media.

Medicaid expansion and access to naloxone in metropolitan and nonmetropolitan areas

PURPOSE

The opioid crisis remains a major public health concern in the United States. Naloxone is used to reverse opioid overdoses. This study examined Medicaid expansion on naloxone prescriptions in retail pharmacies in metropolitan (metro) and nonmetropolitan (nonmetro) areas (2011-2017).

METHODS

We used population average models to evaluate the association of Medicaid expansion at the state level on the number of naloxone prescriptions dispensed and the percentage paid by Medicaid, including adjustment for opioid-related and state-level policy covariates. Difference-in-difference modeling was performed as a sensitivity analysis.

FINDINGS

States that expanded Medicaid had higher unadjusted naloxone dispensing rates and Medicaid-paid percentage of naloxone in metro and nonmetro areas. Medicaid expansion was not associated with the number of naloxone dispensed in either metro (adjusted rate ratio (ARR) = 1.26, 95% CI: [0.80, 1.97]) or nonmetro (ARR = 0.67, 95% CI: [0.37, 1.19]) areas after covariate adjustment. In metro areas, Medicaid expansion was associated with a significant increase of 3.86 percentage points (95% CI: [0.09, 7.63]) in the Medicaid-paid percentage of naloxone dispensing compared to nonexpansion states, but this association was not significant in nonmetro areas. There was also a significant time by Medicaid expansion interaction on the Medicaid-paid percentage of naloxone dispensed (metro: estimate = 0.74, 95% CI: [0.36, 1.12]; nonmetro: estimate = 0.68, 95% CI: [0.17, 1.18]).

CONCLUSIONS

Medicaid expansion increased naloxone access by increasing the Medicaid-paid percentage of naloxone prescriptions in metro areas. States with Medicaid expansion had a faster rate of increase in the Medicaid-paid percentage of naloxone than states without Medicaid expansion in nonmetro areas.

Development of a Machine Learning Model to Estimate US Firearm Homicides in Near Real Time

Importance

Firearm homicides are a major public health concern; lack of timely mortality data presents considerable challenges to effective response. Near real-time data sources offer potential for more timely estimation of firearm homicides.

Objective

To estimate near real-time burden of weekly and annual firearm homicides in the US.

Design, Setting, and Participants

In this prognostic study, anonymous, longitudinal time series data were obtained from multiple data sources, including Google and YouTube search trends related to firearms (2014-2019), emergency department visits for firearm injuries (National Syndromic Surveillance Program, 2014-2019), emergency medical service activations for firearm-related injuries (biospatial, 2014-2019), and National Domestic Violence Hotline contacts flagged with the keyword firearm (2016-2019). Data analysis was performed from September 2021 to September 2022.

Main Outcomes and Measures

Weekly estimates of US firearm homicides were calculated using a 2-phase pipeline, first fitting optimal machine learning models for each data stream and then combining the best individual models into a stacked ensemble model. Model accuracy was assessed by comparing predictions of firearm homicides in 2019 to actual firearm homicides identified by National Vital Statistics System death certificates. Results were also compared with a SARIMA (seasonal autoregressive integrated moving average) model, a common method to forecast injury mortality.

Results

Both individual and ensemble models yielded highly accurate estimates of firearm homicides. Individual models' mean error for weekly estimates of firearm homicides (root mean square error) varied from 24.95 for emergency department visits to 31.29 for SARIMA forecasting. Ensemble models combining data sources had lower weekly mean error and higher annual accuracy than individual data sources: the all-source ensemble model had a weekly root mean square error of 24.46 deaths and full-year accuracy of 99.74%, predicting the total number of firearm homicides in 2019 within 38 deaths for the entire year (compared with 95.48% accuracy and 652 deaths for the SARIMA model). The model decreased the time lag of reporting weekly firearm homicides from 7 to 8 months to approximately 6 weeks.

Conclusions and Relevance

In this prognostic study of diverse secondary data on machine learning, ensemble modeling produced accurate near real-time estimates of weekly and annual firearm homicides and substantially decreased data source time lags. Ensemble model forecasts can accelerate public health practitioners' and policy makers' ability to respond to unanticipated shifts in firearm homicides.

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

BACKGROUND

There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information.

OBJECTIVE

This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change.

METHODS

We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database.

RESULTS

Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05).

CONCLUSIONS

This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders.