@article{Hasgul2025,

title = {Stimulant-involved overdose deaths: Constructing dynamic hypotheses},

author = {Zeynep Hasgul and Arielle R Deutsch and Mohammad S Jalali and Erin J Stringfellow},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2025/01/Hasgul_stimulant_overdose_2025.pdf

https://mj-lab.mgh.harvard.edu/wp-content/uploads/2025/03/Stimulant-Involved-ODs.pdf

},

year  = {2025},

date = {2025-01-27},

urldate = {2025-01-27},

journal = {International Journal of Drug Policy},

volume = {136},

pages = {104702},

abstract = {The overdose epidemic in the United States is evolving, with a rise in stimulant (cocaine and/or methamphetamine)-only and opioid and stimulant-involved overdose deaths for reasons that remain unclear. We conducted interviews and group model building workshops in Massachusetts and South Dakota. Building on these data and extant research, we identified six dynamic hypotheses, explaining changes in stimulant-involved overdose trends, visualized using causal loop diagrams. For stimulant- and opioid-involved overdose deaths, three dynamic hypotheses emerged: (1) accidental exposure to fentanyl from stimulants; (2) primary stimulant users increasingly using opioids, often with resignation; (3) primary opioid (especially fentanyl) users increasingly using stimulants to balance the sedating effect of fentanyl. For stimulant-only overdose deaths, three additional dynamic hypotheses emerged: (1) disbelief that death could occur from stimulants alone, and doubt in testing capabilities to detect fentanyl; (2) the stimulant supply has changed, leading to higher unpredictability and thus higher overdose risk; and (3) long-term stimulant use contributing to deteriorating health and increasing overdose risk. These hypotheses likely each explain a portion of the recent trends in stimulant-involved overdoses. However, confusion and uncertainty around the drug supply emerged as a central theme, underscoring the chaotic and unpredictable nature of the stimulant market. Our findings indicate the need for research to develop targeted public health interventions, including analyzing the extent of the effect of contamination on overdoses, reducing confusion about the stimulant supply, and examining historical stimulant use trends.},

keywords = {Methods, Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Dong2024b,

title = {State-level Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the United States},

author = {Huiru Dong and Erin J. Stringfellow and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/12/Dong_disparities_2024.pdf},

year  = {2025},

date = {2025-01-04},

urldate = {2024-07-31},

journal = {The American Journal on Addictions},

abstract = {Background and objectives: National trends reveal a concerning escalation in racial and ethnic disparities in buprenorphine treatment duration for opioid use disorder. However, the extent of such disparities at the state level remains largely unexplored. This study aims to examine such disparities at the state level.

Methods: We analyzed 9,040,620 buprenorphine prescriptions dispensed between January 2011 and December 2020 from IQVIA Longitudinal Prescription data. The primary outcome was the difference in median treatment duration between White people and racial and ethnic minorities. We also included a second outcome measurement to quantify the difference in median treatment duration among episodes lasting ≥180 days. Using quantile regressions, we examined racial and ethnic disparities in treatment duration, adjusting for the patient's age, sex, payment type, and calendar year of the treatment episode. All analyses were conducted at the state level.

Results: Our study revealed substantial statewide variations in racial and ethnic disparities. Specifically, 21 states showed longer treatment durations for White people across all episodes, and eight states displayed similar trends among episodes lasting ≥180 days. Five states exhibited longer treatment durations for White people in both overall and long-term episodes. Fifteen states showed no racial and ethnic disparities.

Conclusion and scientific significance: These results are among the first to indicate substantial statewide variations in racial and ethnic disparities in buprenorphine treatment episode duration, providing a critical foundation for targeted interventions to enhance buprenorphine treatment, especially in states confronting such pronounced racial and ethnic disparities.},

keywords = {Disparity and equity, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Herman2024,

title = {Dynamics of prescribing and accessing medications for opioid use disorder: a community-based systems analysis},

author = {Tianna Herman and Zeynep Hasgul and Tse Yang Lim and Mohammad S. Jalali and Erin J. Stringfellow},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/11/Herman_2024.pdf},

year  = {2024},

date = {2024-11-12},

journal = {Addiction Research & Theory},

abstract = {Background

Although medications for opioid use disorder (MOUD) are effective for treating opioid use disorder (OUD), persistent barriers still prevent patients from accessing this life-saving care. Policies to increase MOUD access have produced suboptimal results. This study presents a qualitative system dynamics model that elucidates the complexities of accessing and staying in MOUD treatment.



Methods

We utilized a community-based system dynamics approach to modeling the MOUD treatment system. We engaged a cohort of system experts/stakeholders, including individuals who had received MOUD, treatment providers, and policymakers, in interviews and group model building to develop and refine a simulation model. We then created a qualitative causal loop diagram based on insights gained while developing the simulation model and a review of interview transcripts.



Results

The causal loop diagram captures four key factors affecting treatment initiation, retention, and leaving: (1) fraught interactions between patients and healthcare providers; (2) stigma-driven regulation of MOUD creating a culture of fear and defensive medicine; (3) a punitive culture in clinics and opioid treatment programs offering MOUD; and (4) the internalization of the abstinence narrative contributing to premature termination of treatment.



Conclusions

Our analysis highlights how interdependent and non-linear feedback processes diminish or counteract the effectiveness and sustainability of MOUD policy interventions. Due to system memory and cultural resistance to change, even rolling back reactionary policies may do little to curb established behavioral patterns. In addition, conflicting and competing strategies among various actors within the system contribute to goal misalignment and a lack of standardization of care.},

keywords = {Participatory modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Dong2024,

title = {Impacts of State Laws Mandating Co-Prescribing Naloxone with Opioids on Naloxone Prescription Dispensing in the U.S.	},

author = {Huiru Dong and Erin J. Stringfellow and Alton Russell and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/09/dong-et-al-2024-state-mandates-on-naloxone.pdf},

year  = {2024},

date = {2024-09-03},

urldate = {2024-04-16},

journal = {Health Affairs},

volume = {43},

issue = {9},

abstract = {In the midst of the opioid crisis in the US, efforts to mitigate overdose risks have become paramount, leading some states to introduce mandates for coprescribing the life-saving overdose reversal drug naloxone. These mandates were designed to specifically address people receiving opioid analgesics who had an elevated risk for overdose. This included people receiving high opioid dosages, those concurrently using benzodiazepines, or those with a history of substance use disorder or overdose. Using a nationally representative, multipayer cohort of patients receiving prescription opioids, we investigated how naloxone codispensing rates changed at the state level from 2016 to 2021 among patients with an elevated risk for overdose. Then we used controlled interrupted time series analyses to assess mandates’ longitudinal impact on naloxone codispensing in ten states that implemented mandates. We observed an immediate and significant increase in the naloxone codispensing rates in eight states after the implementation of mandates. Nevertheless, in five of these states, the codispensing rates exhibited a subsequent downward trend after the initial increase. State mandates show potential for improving naloxone codispensing; however, mandates alone might not be adequate for sustained change. Further research is needed to identify strategies complementing and enhancing the impact of mandates in combating the overdose crisis.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Lim2024,

title = {Improving estimates of the prevalence of opioid use disorder in the United States: Revising Keyes et al.},

author = {Tse Yang Lim and Katherine M. Keyes and Jonathan P. Caulkinsd and Erin J. Stringfellow and Magdalena Cerdá and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/09/prevalence_of_oud.pdf},

year  = {2024},

date = {2024-09-02},

urldate = {2024-09-02},

journal = {Journal of Addiction Medicine},

abstract = {Objectives 

The United States faces an ongoing drug overdose crisis, but accurate information on the prevalence of opioid use disorder (OUD) remains limited. A recent analysis by Keyes et al used a multiplier approach with drug poisoning mortality data to estimate OUD prevalence. Although insightful, this approach made stringent and partly inconsistent assumptions in interpreting mortality data, particularly synthetic opioid (SO)–involved and non–opioid-involved mortality. We revise that approach and resulting estimates to resolve inconsistencies and examine several alternative assumptions.



Methods 

We examine 4 adjustments to Keyes and colleagues’ estimation approach: (A) revising how the equations account for SO effects on mortality, (B) incorporating fentanyl prevalence data to inform estimates of SO lethality, (C) using opioid-involved drug poisoning data to estimate a plausible range for OUD prevalence, and (D) adjusting mortality data to account for underreporting of opioid involvement.



Results 

Revising the estimation equation and SO lethality effect (adj. A and B) while using Keyes and colleagues’ original assumption that people with OUD account for all fatal drug poisonings yields slightly higher estimates, with OUD population reaching 9.3 million in 2016 before declining to 7.6 million by 2019. Using only opioid-involved drug poisoning data (adj. C and D) provides a lower range, peaking at 6.4 million in 2014–2015 and declining to 3.8 million in 2019.



Conclusions 

The revised estimation equation presented is feasible and addresses limitations of the earlier method and hence should be used in future estimations. Alternative assumptions around drug poisoning data can also provide a plausible range of estimates for OUD population.},

keywords = {Methods, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Sung2024,

title = {Assessment of Epidemiologic Data and Surveillance in South Korean Substance Use Research: Insights and Future Directions},

author = {Meekang Sung and Vaughan W Rees and Hannah Lee and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/12/Sung_Korea_2024.pdf},

year  = {2024},

date = {2024-03-01},

urldate = {2024-03-01},

journal = {Journal of Preventive Medicine and Public Health},

abstract = {Objectives

Effective data collection and surveillance of epidemiological trends are essential in confronting the growing challenges associated with substance use (SU), especially in light of emerging trends and underreporting of cases. However, research and data are scarce regarding SU and substance use disorder (SUD) in Korea.

Methods

We conducted a scoping review to identify data sources and surveillance methods used in SU research in Korea up to December 2023. This review was complemented by semi-structured consultations with experts in this area in Korea, whose feedback led to revisions of previously identified data sources and assessments.

Results

Our review identified 32 publications conducting secondary analyses on existing data to examine the epidemiology of SU and SUD in Korea. Of these, 14 studies utilized clinical databases to explore the prescription patterns of addictive substances, particularly opioids. Eleven data sources showed promise for advancing SU research; however, they face substantial limitations, including a lack of available data, missing data, the absence of key variables, the exclusion of marginalized populations not captured within the clinical system, and complexities in matching individual-level data across time points and datasets.

Conclusions

Current surveillance methods for SU in Korea face considerable challenges in accessibility, usability, and standardization. Moreover, existing data repositories may fail to capture information on populations not served by clinical or judicial systems. To systematically improve surveillance approaches, it is necessary to develop a robust and nationally representative survey, refine the use of existing clinical data, and ensure the availability of data on treatment facilities.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Factors Associated With Abrupt Discontinuation of Long-Term High-Dose Opioid Treatment},

author = {Carolina Vivas-Valencia and Huiru Dong and Erin J. Stringfellow and W. Alton Russell and Jake R. Morgan and Mina Tadrous and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/11/vivasvalencia_2023.pdf},

year  = {2023},

date = {2023-11-03},

journal = {JAMA Network Open},

volume = {6},

issue = {11},

pages = {e2341416},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Stringfellow2023b,

title = {The association between longitudinal trends in receipt of buprenorphine for opioid use disorder and buprenorphine-waivered providers in the United States},

author = {Erin Stringfellow and Tse Yang Lim and Huiru Dong and Ziyuan Zhang and Mohammad S. Jalali

},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/07/Stingfellow_et_al_Addiction_2023.pdf},

year  = {2023},

date = {2023-07-11},

urldate = {2023-07-11},

journal = {Addiction},

abstract = {Aims, Design and Setting

We sought to describe longitudinal trends in buprenorphine receipt and buprenorphine-waivered providers in the United States from 2003 to 2021 and measure whether the relationship between the two differed after capacity-building strategies were enacted nationally in 2017. This was a retrospective study of two separate cohorts covering the years 2003–21, testing whether the association between two trends in these cohorts changed comparing 2003 to 2016 and from 2017 to 2021, among buprenorphine providers in the United States, regardless of treatment setting. Patients receiving dispensed buprenorphine at retail pharmacies.



Participants

All providers who have obtained a waiver to prescribe buprenorphine in the United States, and an estimate of the annual number of patients who had buprenorphine for opioid use disorder (OUD) dispensed to them at a retail pharmacy.



Measurements

We synthesized and summarized data from multiple sources to assess the cumulative number of buprenorphine-waivered providers over time. We used national-level prescription data from IQVIA to estimate annual buprenorphine receipt for OUD.



Findings

From 2003 to 2021, the number of buprenorphine-waivered providers in the United States increased from fewer than 5000 in the first 2 years of Food and Drug Administration (FDA) approval to more than 114 000 in 2021, while patients receiving buprenorphine products for OUD increased from approximately 19 000 to more than 1.4 million. The strength of association between waivered providers and patients is significantly different before and after 2017 (P < 0.001). From 2003 to 2016, for each additional provider, there was an average increase of 32.1 [95% confidence interval (CI) = 28.7–35.6] patients, but an increase of only 4.6 (95% CI= 3.5–5.7) patients for each additional provider, beginning in 2017.



Conclusions

In the United States, the relationship between the rates of growth in buprenorphine providers and patients became weaker after 2017. While efforts to increase buprenorphine-waivered providers were successful, there was less success in translating that into significant increases in buprenorphine receipt.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Claypool2023,

title = {Cost-effectiveness of increasing buprenorphine treatment initiation, duration, and capacity among individuals who use opioids},

author = {Anneke Claypool and Catherine DiGennaro and W. Alton Russell and Melike Yildirim and Alan Zhang and Zuri Reid and Erin Stringfellow and Benjamin Bearnot and Bruce Schackman and Keith Humphreys and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/07/Claypool_2023.pdf},

year  = {2023},

date = {2023-05-19},

urldate = {2023-05-19},

journal = {JAMA Health Forum},

volume = {4},

issue = {5},

pages = {e231080},

abstract = {Importance: Buprenorphine is an effective and cost-effective medication to treat opioid use disorder (OUD), but is not readily available to many people with OUD in the US. The current cost-effectiveness literature does not consider interventions that concurrently increase buprenorphine initiation, duration, and capacity.

Objective: To conduct a cost-effectiveness analysis and compare interventions associated with increased buprenorphine treatment initiation, duration, and capacity.

Design and Setting: This study modeled the effects of 5 interventions individually and in combination using SOURCE, a recent system dynamics model of prescription opioid and illicit opioid use, treatment, and remission, calibrated to US data from 1999 to 2020. The analysis was run during a 12-year time horizon from 2021 to 2032, with lifetime follow-up. A probabilistic sensitivity analysis on intervention effectiveness and costs was conducted. Analyses were performed from April 2021 through March 2023. Modeled participants included people with opioid misuse and OUD in the US.

Interventions: Interventions included emergency department buprenorphine initiation, contingency management, psychotherapy, telehealth, and expansion of hub-and-spoke treatment programs, individually and in combination.

Main Outcomes and Measures: Total national opioid overdose deaths, quality-adjusted life years (QALYs) gained, and costs from the societal and health care perspective.

Results: Projections showed that contingency management expansion would avert 3530 opioid overdose deaths over 12 years, more than any other single-intervention strategy. Interventions that increased buprenorphine treatment duration initially were associated with an increased number of opioid overdose deaths in the absence of expanded treatment capacity. With an incremental cost- effectiveness ratio of $19 381 per QALY gained (2021 USD), the strategy that expanded contingency management, hub-and-spoke training, emergency department initiation, and telehealth was the preferred strategy for any willingness-to-pay threshold from $20 000 to $200 000/QALY gained, as it was associated with increased treatment duration and capacity simultaneously.

Conclusion and Relevance: This modeling analysis simulated the effects of implementing several intervention strategies across the buprenorphine cascade of care and found that strategies that were concurrently associated with increased buprenorphine treatment initiation, duration, and capacity were cost-effective.},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{669757,

title = {Social Vulnerability Predictors of Drug Poisoning Mortality: A Machine Learning Analysis in the United States},

author = {Moosa Tatar and Mohammad R. Faraji and Katherine Keyes and Fernando A. Wilson and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/07/Tatar_et_al_AJA_2023.pdf},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {The American Journal on Addictions},

abstract = {Background and Objectives

Drug poisoning is a leading cause of unintentional deaths in the United States. Despite the growing literature, there are a few recent analyses of a wide range of community-level social vulnerability features contributing to drug poisoning mortality. Current studies on this topic face three limitations: often studying a limited subset of vulnerability features, focusing on small sample sizes, or solely including local data. To address this gap, we conducted a national-level analysis to study the impacts of several social vulnerability features in predicting drug mortality rates in the United States.



Methods

We used machine learning to investigate the role of 16 social vulnerability features in predicting drug mortality rates for US counties in 2014, 2016, and 2018—the most recent available data. We estimated each vulnerability feature's gain relative contribution in predicting drug poisoning mortality.



Results

Among all social vulnerability features, the percentage of noninstitutionalized persons with a disability is the most influential predictor, with a gain relative contribution of 18.6%, followed by population density and the percentage of minority residents (13.3% and 13%, respectively). Percentages of households with no available vehicles, mobile homes, and persons without a high school diploma are the following features with gain relative contributions of 6.3%, 5.8%, and 5.1%, respectively.



Conclusion and Scientific Significance

We identified social vulnerability features that are most predictive of drug poisoning mortality. Public health interventions and policies targeting vulnerable communities may increase the resilience of these communities and mitigate the overdose death and drug misuse crisis.},

keywords = {Artificial intelligence, Disparity and equity, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Deutsch2023b,

title = {Grounding alcohol simulation models in empirical and theoretical alcohol research: a model for a Northern Plains population in the United States},

author = {Arielle Deutsch and Nikki Motabar and Edward Chang and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/alcohol-misuse-model

https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/06/Deutsch_SDR_2023.pdf},

year  = {2023},

date = {2023-05-01},

urldate = {2023-05-01},

journal = {System Dynamics Review},

abstract = {The growing number of systems science simulation models for alcohol use (AU) are often disconnected from AU models within empirical and theoretical alcohol research. As AU prevention/intervention efforts are typically grounded in alcohol research, this disconnect may reduce policy testing results, impact, and implementation. We developed a simulation model guided by AU research (accounting for the multiple AU stages defined by AU behavior and risk for harm and diverse transitions between stages). Simulated projections were compared to historical data to evaluate model accuracy and potential policy leverage points for prevention and intervention at risky drinking (RD) and alcohol use disorder (AUD) stages. Results indicated prevention provided the greatest RD and AUD reduction; however, focusing exclusively on AUD prevention may not be effective for long-term change, given the continued increase in RD. This study makes a case for the strength and importance of aligning subject-based research with systems science simulation models.},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Stringfellow2023,

title = {Enumerating contributions of fentanyls and other factors to the unprecedented 2020 rise in opioid overdose deaths: model-based analysis},

author = {Erin J. Stringfellow and Tse Yang Lim and Catherine DiGennaro and Zeynep Hasgül and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/04/fent_effect_2023.pdf},

year  = {2023},

date = {2023-04-12},

urldate = {2023-04-12},

journal = {PNAS Nexus},

volume = {2},

number = {4},

pages = {pgad064},

abstract = {In 2020, the ongoing US opioid overdose crisis collided with the emerging COVID-19 pandemic. Opioid overdose deaths (OODs) rose an unprecedented 38%, due to a combination of COVID-19 disrupting services essential to people who use drugs, continued increases in fentanyls in the illicit drug supply, and other factors. How much did these factors contribute to increased OODs? We used a validated simulation model of the opioid overdose crisis, SOURCE, to estimate excess OODs in 2020 and the distribution of that excess attributable to various factors. Factors affecting OODs that could have been disrupted by COVID-19, and for which data were available, included opioid prescribing, naloxone distribution, and receipt of medications for opioid use disorder. We also accounted for fentanyls’ presence in the heroin supply. We estimated a total of 18,276 potential excess OODs, including 1,792 lives saved due to increases in buprenorphine receipt and naloxone distribution and decreases in opioid prescribing. Critically, growth in fentanyls drove 43% (7,879) of the excess OODs. A further 8% is attributable to first-ever declines in methadone maintenance treatment and extended-released injectable naltrexone treatment, most likely due to COVID-19-related disruptions. In all, 49% of potential excess OODs remain unexplained, at least some of which are likely due to additional COVID-19-related disruptions. While the confluence of various COVID-19-related factors could have been responsible for more than half of excess OODs, fentanyls continued to play a singular role in excess OODs, highlighting the urgency of mitigating their effects on overdoses.},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Stringfellow2023bb,

title = {Long-term Effects of Increasing Buprenorphine Treatment-Seeking, Duration, and Capacity on Opioid Overdose Fatalities: a Model-based Analysis},

author = {Erin J. Stringfellow and 

Tse Yang Lim and 

Catherine DiGennaro and 

Ziyuan Zhang and 

Pritika Paramasivam and 

Benjamin Bearnot and 

Keith Humphreys and 

Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/04/Long_Term_Effects_of_Increasing_Buprenorphine.pdf},

year  = {2023},

date = {2023-03-01},

urldate = {2023-03-01},

journal = {Journal of Addiction Medicine},

abstract = {Objectives 

Because buprenorphine treatment of opioid use disorder reduces opioid overdose deaths (OODs), expanding access to care is an important policy and clinical care goal. Policymakers must choose within capacity limitations whether to expand the number of people with opioid use disorder who are treated or extend duration for existing patients. This inherent tradeoff could be made less acute with expanded buprenorphine treatment capacity.



Methods 

To inform such decisions, we used a validated simulation model to project the effects of increasing buprenorphine treatment-seeking, average episode duration, and capacity (patients per provider) on OODs in the United States from 2023 to 2033, varying the start time to assess the effects of implementation delays.



Results 

Results show that increasing treatment duration alone could cost lives in the short term by reducing capacity for new admissions yet save more lives in the long term than accomplished by only increasing treatment seeking. Increasing provider capacity had negligible effects. The most effective 2-policy combination was increasing capacity and duration simultaneously, which would reduce OODs up to 18.6% over a decade. By 2033, the greatest reduction in OODs (≥20%) was achieved when capacity was doubled and average duration reached 2 years, but only if the policy changes started in 2023. Delaying even a year diminishes the benefits. Treatment-seeking increases were equally beneficial whether they began in 2023 or 2025 but of only marginal benefit beyond what capacity and duration achieved.



Conclusions 

If policymakers only target 2 policies to reduce OODs, they should be to increase capacity and duration, enacted quickly and aggressively.},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Dong2022b,

title = {Racial and Ethnic Disparities in Buprenorphine Treatment Duration in the US},

author = {Huiru Dong and Erin J. Stringfellow and W. Alton Russell and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Dong-2022-jamapsychiatry.pdf},

doi = {10.1001/jamapsychiatry.2022.3673},

year  = {2023},

date = {2023-02-01},

urldate = {2023-03-01},

journal = {JAMA Psychiatry},

keywords = {Disparity and equity, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Dong2022,

title = {Impact of Alternative Ways to Operationalize Buprenorphine Treatment Duration on Understanding Continuity of Care for Opioid Use Disorder},

author = {Huiru Dong and Erin J. Stringfellow and W Alton Russell and Benjamin Bearnot and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Dong-2022.pdf},

doi = {10.1007/s11469-022-00985-w},

year  = {2022},

date = {2022-12-10},

urldate = {2022-12-10},

journal = {International Journal of Mental Health and Addiction},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Stringfellow2021,

title = {Reducing Opioid Use Disorder and Overdose in the United States: A Dynamic Modeling Analysis},

author = {Erin J. Stringfellow and Tse Yang Lim and Keith Humphreys and Catherine DiGennaro and Celia Stafford and Elizabeth Beaulieu and Jack Homer and Wayne Wakeland and Benjamin Bearnot and R. Kathryn McHugh and John Kelly and Lukas Glos and Sara Eggers and Reza Kazemi and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Stringfellow_2022_SciAdv.pdf},

doi = {10.1126/sciadv.abm8147},

year  = {2022},

date = {2022-06-24},

journal = {Science Advances},

volume = {8},

number = {25},

abstract = {Opioid overdose deaths remain a major public health crisis. We used a system dynamics simulation model of the U.S. opioid-using population age 12 and older to explore the impacts of 11 strategies on the prevalence of opioid use disorder (OUD) and fatal opioid overdoses from 2022 to 2032. These strategies spanned opioid misuse and OUD prevention, buprenorphine capacity, recovery support, and overdose harm reduction. By 2032, three strategies saved the most lives: (i) reducing the risk of opioid overdose involving fentanyl use, which may be achieved through fentanyl-focused harm reduction services; (ii) increasing naloxone distribution to people who use opioids; and (iii) recovery support for people in remission, which reduced deaths by reducing OUD. Increasing buprenorphine providers’ capacity to treat more people decreased fatal overdose, but only in the short term. Our analysis provides insight into the kinds of multifaceted approaches needed to save lives.

},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{669758,

title = {Identifying Key Risk Factors for Premature Discontinuation of Opioid Use Disorder Treatment in the United States: a Predictive Modeling Study},

author = {Celia Stafford and Wesley Marrero and Rebecca B Naumann and Kristen Hassmiller Lich and Sarah Wakeman and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Stafford_2022_DAD.pdf},

doi = {10.1016/j.drugalcdep.2022.109507},

year  = {2022},

date = {2022-06-01},

urldate = {2022-06-01},

journal = {Drug and Alcohol Dependence},

volume = {237},

number = {1},

pages = {109507},

abstract = {Background

Treatment for opioid use disorder (OUD), particularly medication for OUD, is highly effective; however, retention in OUD treatment is a significant challenge. We aimed to identify key risk factors for premature exit from OUD treatment.



Methods

We analyzed 2,381,902 cross-sectional treatment episodes for individuals in the U.S., discharged between Jan/1/2015 and Dec/31/2019. We developed classification models (Random Forest, Classification and Regression Trees (CART), Bagged CART, and Boosted CART), and analyzed 31 potential risk factors for premature treatment exit, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. We stratified our analysis based on length of stay in treatment and service setting. Models were compared using cross-validation and the receiver operating characteristic area under the curve (ROC-AUC).



Results

Random Forest outperformed other methods (ROC-AUC: 74%). The most influential risk factors included characteristics of service setting, geographic region, primary source of payment, and referral source. Race, ethnicity, and sex had far weaker predictive impacts. When stratified by treatment setting and length of stay, employment status and delay (days waited) to enter treatment were among the most influential factors. Their importance increased as treatment duration decreased. Notably, importance of referral source increased as the treatment duration increased. Finally, age and age of first use were important factors for lengths of stay of 2–7 days and in detox treatment settings.



Conclusions

The key factors of OUD treatment attrition identified in this analysis should be more closely explored (e.g., in causal studies) to inform targeted policies and interventions to improve models of care.},

keywords = {Artificial intelligence, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Lim2021,

title = {Modeling the Evolution of the U.S. Opioid Crisis for National Policy Development},

author = {Tse Yang Lim and Erin J. Stringfellow and Celia A. Stafford and Catherine DiGennaro and Jack Homer and Wayne Wakeland and Sara L. Eggers and Reza Kazemi and Lukas Glos and Emily G. Ewing and Calvin B. Bannister and Keith Humphreys and Douglas C. Throckmorton and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Lim_2022_PNAS.pdf},

doi = {10.1073/pnas.211571411},

year  = {2022},

date = {2022-05-31},

urldate = {2022-05-31},

journal = {PNAS},

volume = {119},

number = {23},

abstract = {The opioid crisis is a major public health challenge in the United States, killing about 70,000 people in 2020 alone. Long delays and feedbacks between policy actions and their effects on drug-use behavior create dynamic complexity, complicating policy decision-making. In 2017, the National Academies of Sciences, Engineering, and Medicine called for a quantitative systems model to help understand and address this complexity and guide policy decisions. Here, we present SOURCE (Simulation of Opioid Use, Response, Consequences, and Effects), a dynamic simulation model developed in response to that charge. SOURCE tracks the US population aged ≥12 y through the stages of prescription and illicit opioid (e.g., heroin, illicit fentanyl) misuse and use disorder, addiction treatment, remission, and overdose death. Using data spanning from 1999 to 2020, we highlight how risks of drug use initiation and overdose have evolved in response to essential endogenous feedback mechanisms, including: 1) social influence on drug use initiation and escalation among people who use opioids; 2) risk perception and response based on overdose mortality, influencing potential new initiates; and 3) capacity limits on treatment engagement; as well as other drivers, such as 4) supply-side changes in prescription opioid and heroin availability; and 5) the competing influences of illicit fentanyl and overdose death prevention efforts. Our estimates yield a more nuanced understanding of the historical trajectory of the crisis, providing a basis for projecting future scenarios and informing policy planning.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{674513,

title = {Identifying and Characterizing Medical Advice-Seekers on a Social Media Forum for Buprenorphine Use},

author = {Gian-Gabriel P. Garcia and Ramin Dehghanpoor and Erin J. Stringfellow and Marichi Gupta and Jillian Rochelle and Elizabeth Mason and Toyya A Pujol and Mohammad S. Jalali},

url = {https://www.mdpi.com/1660-4601/19/10/6281/htm},

year  = {2022},

date = {2022-05-22},

urldate = {2022-05-22},

journal = {Int. J. Environ. Res. Public Health},

volume = {19},

number = {10},

pages = {6281},

abstract = {Background: Online communities such as Reddit can provide social support for those recovering from opioid use disorder. However, it is unclear whether and how advice-seekers differ from other users. Our research addresses this gap by identifying key characteristics of r/suboxone users that predict advice-seeking behavior. Objective: The objective of this analysis is to identify and describe advice-seekers on Reddit for buprenorphine-naloxone use using text annotation, social network analysis, and statistical modeling techniques. Methods: We collected 5258 posts and their comments from Reddit between 2014 and 2019. Among 202 posts which met our inclusion criteria, we annotated each post to determine which were advice-seeking (n = 137) or not advice-seeking (n = 65). We also annotated each posting user’s buprenorphine-naloxone use status (current versus formerly taking and, if currently taking, whether inducting or tapering versus other stages) and quantified their connectedness using social network analysis. To analyze the relationship between Reddit users’ advice-seeking and their social connectivity and medication use status, we constructed four models which varied in their inclusion of explanatory variables for social connectedness and buprenorphine use status. Results: The stepwise model containing “total degree” (p = 0.002), “using: inducting/tapering” (p < 0.001), and “using: other” (p = 0.01) outperformed all other models. Reddit users with fewer connections and who are currently using buprenorphine-naloxone are more likely to seek advice than those who are well-connected and no longer using the medication, respectively. Importantly, advice-seeking behavior is most accurately predicted using a combination of network characteristics and medication use status, rather than either factor alone. Conclusions: Our findings provide insights for the clinical care of people recovering from opioid use disorder and the nature of online medical advice-seeking overall. Clinicians should be especially attentive (e.g., through frequent follow-up) to patients who are inducting or tapering buprenorphine-naloxone or signal limited social support.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Liao2022,

title = {Racial Disparities in Opioid Overdose Deaths in Massachusetts},

author = {Che-Yi Liao and Gian-Gabriel P. Garcia and Catherine DiGennaro and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Liao_2022_JAMA_no.pdf},

doi = {10.1001/jamanetworkopen.2022.9081},

year  = {2022},

date = {2022-05-01},

journal = {JAMA Network Open},

keywords = {Disparity and equity, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Weiner2022,

title = {Evaluating disparities in prescribing of naloxone after emergency department treatment of opioid overdose},

author = {Scott G Weiner and Aleta D Carroll and Nicholas M Brisbon and Claudia P Rodriguez and Charles Covahey and Erin J. Stringfellow and Catherine DiGennaro and Mohammad S. Jalali and Sarah E. Wakeman},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Weiner_2022_JSAT.pdf},

doi = {10.1016/j.jsat.2022.108785},

year  = {2022},

date = {2022-04-22},

urldate = {2022-04-22},

journal = {Journal of Substance Abuse Treatment},

volume = {139},

pages = {108785},

keywords = {Disparity and equity, Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{666820,

title = {Alcohol and Opioid Use Impacts on Road Safety-related Outcomes: Systematic Review},

author = {Elizabeth Beaulieu and Rebecca B Naumann and Genevieve Deveaux and Lindsay Wang and Erin J. Stringfellow and Kristen Hassmiller Lich and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Beaulieu_2022_AAP.pdf},

doi = {10.1016/j.aap.2022.106713},

year  = {2022},

date = {2022-01-02},

urldate = {2022-01-02},

journal = {Accident Analysis & Prevention},

volume = {173},

pages = {106713},

abstract = {Connections between substance use, impairment, and road safety have been frequently researched. Yet, little is known about how simultaneous use of opioids and alcohol affects road safety outcomes, which is an increasingly critical link within the current landscape of the substance use environment and public health. Lack of this understanding is partly due to testing complications and data limitations. We define polysubstance use here as alcohol and opioids consumed together or within a small-time window such that both are present in the system. This polysubstance use is on the rise and produces greater health risks than when the substances are consumed separately. Given the increasing rate of opioid use, high prevalence of alcohol use, and dangers of polysubstance use, we aim to synthesize literature on the prevalence and impact of this polysubstance on road safety-related outcomes. We performed a systematic review of studies published between 1974 and 2020 that examined opioid and alcohol use exposures and road safety-related outcomes. Out of 644 initial findings, 20 studies were included in this review. Outcomes included motor vehicle crash injuries, deaths, or driver culpability; suspected driving under the influence; and simulated driving performance. Evidence from multiple sources showed a significant rise, approximately 1% to 7%, in the prevalence of opioids among fatally injured drivers in the U.S. from 1995 to 2016. Information published on the simultaneous presence of opioids and alcohol in people involved in crashes was scarce. The limited available findings point toward an overlap where up to 30% of opioid-positive people involved in a crash were also positive for alcohol. Studies also suggest a possibly elevated risk presented by this polysubstance use relative to the substances used alone, though the majority of identified studies did not estimate this association. The synthesized research indicates that alcohol and opioid use is not uncommon and may be increasing among people involved in adverse driving events. More research and better data are needed to improve estimates of association with road traffic-related outcomes, potentially improving substance testing in current surveillance systems or using linked data sets and other novel data sources to improve estimates.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{Garcia2021,

title = {Opioid Overdose Decedent Characteristics during COVID-19},

author = {Gian-Gabriel P. Garcia and Erin J. Stringfellow and Catherine DiGennaro and Nicole Poellinger and Jaden Wood and Sarah Wakeman and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2022/12/Garcia_2022_AOM.pdf},

doi = {10.1080/07853890.2022.2067350},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Annals of Medicine},

volume = {54},

issue = {1},

abstract = {Introduction: Alongside the emergence of COVID-19 in the United States, several reports highlighted increasing rates of opioid overdose from preliminary data. Yet, little is known about how state-level opioid overdose death trends and decedent characteristics have evolved using official death records.



Methods: We requested vital statistics data from 2018-2020 from all 50 states and the District of Columbia, receiving data from 14 states. Accounting for COVID-19, we excluded states without data past March 2020, leaving 11 states for analysis. We defined state-specific analysis periods from March 13 until the latest reliable date in each state's data, then conducted retrospective year-over-year analyses comparing opioid-related overdose death rates, the presence of specific opioids and other psychoactive substances, and decedents' sex, race, and age from 2020 to 2019 and 2019 to 2018 within each state's analysis period. We assessed whether significant changes in 2020 vs. 2019 in opioid overdose deaths were new or continuing trends using joinpoint regression.



Results: We found significant increases in opioid-related overdose death rates in Alaska (55.3%), Colorado (80.2%), Indiana (40.1%), Nevada (50.0%), North Carolina (30.5%), Rhode Island (29.6%), and Virginia (66.4%) - all continuing previous trends. Increases in synthetic opioid-involved overdose deaths were new in Alaska (136.5%), Indiana (27.6%), and Virginia (16.5%), whilst continuing in Colorado (44.4%), Connecticut (3.6%), Nevada (75.0%), and North Carolina (14.6%). We found new increases in male decedents in Indiana (12.0%), and continuing increases in Colorado (15.2%). We also found continuing increases in Black non-Hispanic decedents in Massachusetts (43.9%) and Virginia (33.7%).



Conclusion: This research analyzes vital statistics data from 11 states, highlighting new trends in opioid overdose deaths and decedent characteristics across 10 of these states. These findings can inform state-specific public health interventions and highlight the need for timely and comprehensive fatal opioid overdose data, especially amidst concurrent crises such as COVID-19. Key messages:Our results highlight shifts in opioid overdose trends during the COVID-19 pandemic that cannot otherwise be extracted from aggregated or provisional opioid overdose death data such as those published by the Centres for Disease Control and Prevention.Fentanyl and other synthetic opioids continue to drive increases in fatal overdoses, making it difficult to separate these trends from any possible COVID-19-related factors.Black non-Hispanic people are making up an increasing proportion of opioid overdose deaths in some states.State-specific limitations and variations in data-reporting for vital statistics make it challenging to acquire and analyse up-to-date data on opioid-related overdose deaths. More timely and comprehensive data are needed to generate broader insights on the nature of the intersecting opioid and COVID-19 crises.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{666785,

title = {A Systematic Review of Simulation Models to Track and Address the Opioid Crisis},

author = {magdalena Cerdá and Mohammad S. Jalali and A Hamilton and C Digennaro and A Hyder and J Santaella-Tenorio and N Kaur and C Wang and Katherine M. Keyes},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/12/Cerda_sysrevi_opioid_models_2021.pdf},

year  = {2021},

date = {2021-07-30},

urldate = {2021-07-30},

abstract = {The opioid overdose crisis is driven by an intersecting set of social, structural, and economic forces. Simulation models offer a tool to help us understand and address this complex, dynamic, 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. Further, we created a database of model parameters used for model calibration, and evaluated study transparency and reproducibility. Of the 1,381 articles screened, we identified 72 eligible articles. The most frequent types of models were Markov (26%), compartmental (25%), system dynamics (19%), and Agent-Based models (18%). Almost half (46%) evaluated intervention cost-effectiveness, while 29% of studies focused on treatment and harm reduction services for people with opioid use disorder (OUD). More than half (57%) calibrated their models to empirical data, and 31% discussed validation approaches used in their modeling process. From the 51 studies that provided data on model parameters, we mapped out the data sources for parameters on opioid use, OUD, OUD treatment, cessation/relapse, emergency medical services, and mortality. This database offers a tool that future modelers can use to identify model inputs, and to evaluate comparability of their models to prior work.  Future applications of simulation models to this field should actively 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.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Removing The X-Waiver Is One Small Step Toward Increasing Treatment Of Opioid Use Disorder, But Great Leaps Are Needed},

author = {Erin J. Stringfellow and Keith Humphreys and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2023/05/Removing_X_Waiver.pdf},

year  = {2021},

date = {2021-04-22},

journal = {Health Affairs Forefront},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{650798,

title = {Economic Evaluation in Opioids Modeling: Systematic Review},

author = {Elizabeth Beaulieu and Catherine DiGennaro and Erin J. Stringfellow and Ava Connolly and Ava Hamilton and Ayaz Hyder and Magdalena Cerda and Katherine M. Keyes and Mohammad S. Jalali},

url = {https://scholar.harvard.edu/files/jalali/files/economic_evaluation_in_opioid_modeling.pdf

https://scholar.harvard.edu/files/jalali/files/supplement_economic_evaluation_in_opioid_modeling.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Value in Health},

volume = {24},

number = {2},

pages = {158-173},

abstract = {ObjectivesThe rapid increase in opioid overdose and opioid use disorder (OUD) over the past 20 years is a complex problem associated with significant economic costs for healthcare systems and society. Simulation models have been developed to capture and identify ways to manage this complexity and to evaluate the potential costs of different strategies to reduce overdoses and OUD. A review of simulation-based economic evaluations is warranted to fully characterize this set of literature. 

 

 

 

	MethodsA systematic review of simulation-based economic evaluation (SBEE) studies in opioid research was initiated by searches in PubMed, EMBASE, and EbscoHOST. Extraction of a predefined set of items and a quality assessment were performed for each study. 

 

 

 

	ResultsThe screening process resulted in 23 SBEE studies ranging by year of publication from 1999 to 2019. Methodological quality of the cost analyses was moderately high. The most frequently evaluated strategies were methadone and buprenorphine maintenance treatments; the only harm reduction strategy explored was naloxone distribution. These strategies were consistently found to be cost-effective, especially naloxone distribution and methadone maintenance. Prevention strategies were limited to abuse-deterrent opioid formulations. Less than half (39%) of analyses adopted a societal perspective in their estimation of costs and effects from an opioid-related intervention. Prevention strategies and studiestextquoteright accounting for patient and physician preference, changing costs, or result stratification were largely ignored in these SBEEs. 

 

 

 

	ConclusionThe review shows consistently favorable cost analysis findings for naloxone distribution strategies and opioid agonist treatments and identifies major gaps for future research.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{661054,

title = {Data Needs in Opioid Systems Modeling: Challenges and Future Directions},

author = {Mohammad S. Jalali and Emily Ewing and Calvin B. Bannister and Lukas Glos and Sara Eggers and Tse Yang Lim and Erin Stringfellow and Celia Stafford and Rosalie Liccardo Pacula and Hawre Jalal and Reza Kazemi-Tabriz},

url = {https://scholar.harvard.edu/files/jalali/files/slides_data_challenges_in_opioid_systems_modeling.pdf

https://scholar.harvard.edu/files/jalali/files/data_needs_opioids_modeling.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {American Journal of Preventive Medicine},

volume = {60},

number = {2},

pages = {e95-e105},

abstract = {Background: The opioid crisis is a pervasive public health threat in the U.S. Simulation modeling approaches that integrate a systems perspective are used to understand the complexity of this crisis and to analyze what policy interventions can best address it. However, limitations in currently available data sources can hamper the quantification of these models. 

 

 

 

	Methods: To understand and discuss data needs and challenges for opioid systems modeling, a meeting of federal partners, modeling teams, and data experts was held at the U.S. Food and Drug Administration in April 2019. This paper synthesizes the meeting discussions and interprets them in the context of ongoing simulation modeling work. 

 

 

 

	Results: The current landscape of national-level quantitative data sources of potential use in opioid systems modeling is identified, and significant issues within data sources are discussed. Major recommendations on how to improve data sources are to: maintain close collaboration among modeling teams; enhance data collection to better fit modeling needs; focus on bridging the most crucial information gaps; engage in direct and regular interaction between modelers and data experts; and gain a clearer definition of policymakerstextquoteright research questions and policy goals. 

 

 

 

	Conclusions: This article provides an important step in identifying and discussing data challenges in opioid research in general and opioid systems modeling in particular. It also identifies opportunities for systems modelers and government agencies to improve opioid systems models.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{665500,

title = {Changes in Characteristics of Drug Overdose Death Trends during the COVID-19 Pandemic},

author = {Catherine DiGennaro and Gian-Gabriel P Garcia and Erin J. Stringfellow and Sarah Wakeman and Mohammad S. Jalali},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2021/10/Overdoses_COVID19_MA.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {International Journal of Drug Policy},

abstract = {Background: Reports analyzing drug overdose (OD) mortality data during the COVID-19 pandemic are limited. Outcomes across states are heterogenous, necessitating assessments of associations between COVID-19 and OD deaths on a state-by-state level. This report aims to analyze trends in OD deaths in Massachusetts during COVID-19. 

 

Methods: Analyzing 3,924 death records, we characterize opioid-, cocaine-, and amphetamine-involved OD mortality and substance co-presence trends from March 24-November 8 in 2020 as compared to 2018 and 2019. 

 

 

 Results: OD deaths involving amphetamines increased by 85% from 2019 to 2020 (61 vs. 113; P<0.001) but were steady from 2018 to 2019. Herointextquoterights presence continued to decrease (341 in 2018, 247 in 2019, 157 in 2020; P<0.001); however, fentanyl was present in more than 85% of all OD deaths across all periods. Among OD deaths, alcohol involvement consistently increased, present in 250 deaths in 2018, 299 in 2019 (P=0.02), and 350 in 2020 (P=0.04). In 2019, 78% of OD decedents were White and 7% were Black, versus 73% and 10% in 2020 (P=0.02). 

 

 

 

	Conclusion: Increased deaths involving stimulants, alcohol, and fentanyl reflect concerning trends in the era of COVID-19. Rising OD death rates among Black residents underscore that interventions focused on racial equity are necessary. 

 

 

 

	 },

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{666821,

title = {Impact of Florida's Prescription Drug Monitoring Program on Fatal Vehicle Crashes: A Difference-in-Differences Approach},

author = {Moosa Tatar and Mohammad S. Jalali and Hyo Jung Tak and Li-Wu Chen and Ozgur M Araz and Fernando A Wilson},

url = {https://mj-lab.mgh.harvard.edu/wp-content/uploads/2024/12/Tatar_pdmp_2021.pdf},

year  = {2021},

date = {2021-01-01},

urldate = {2021-01-01},

journal = {Injury Prevention},

abstract = {Background Prescription drug use has soared in the USA within the last two decades. Prescription drugs can impair motor skills essential for the safe operation of a motor vehicle, and therefore can affect traffic safety. As one of the epicentres of the opioid epidemic, Florida has been struck by high opioid misuse and overdose rates, and has concurrently suffered major threats to traffic disruptions safety caused by driving under the influence of drugs. To prevent prescription opioid misuse in Florida, Prescription Drug Monitoring Programs (PDMPs) were implemented in September 2011.

Objective To examine the impact of Florida’s implementation of a mandatory PDMP on drug-related MVCs occurring on public roads.

Methods We employed a difference-in-differences approach to estimate the difference in prescription drug-related fatal crashes in Florida associated with its 2011 PDMP implementation relative to those in Georgia, which did not use PDMPs during the same period (2009–2013). The analyses were conducted in 2020.

Results In Florida, there was a significant decline in drug-related vehicle crashes during the 22 months post-PDMP. PDMP implementation was associated with approximately two (−2.21; 95% CI −4.04 to –0.37; p<0.05) fewer prescribed opioid-related fatal crashes every month, indicating 25% reduction in the number of monthly crashes. We conducted sensitivity analyses to investigate the impact of PDMP implementation on central nervous system depressants and stimulants as well as cocaine and marijuana-related fatal crashes but found no robust significant reductions.

Conclusions The implementation of PDMPs in Florida provided important benefits for traffic safety, reducing the rates of prescription opioid-related vehicle crashes.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{637263,

title = {The opioid crisis: a contextual, social-ecological framework},

author = {Mohammad S. Jalali and Michael Botticelli and Rachael Hwang and Howard K Koh and Kathryn R McHugh},

url = {https://scholar.harvard.edu/files/jalali/files/opioid_crisis_social_ecological_framework.pdf},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Health Research Policy and Systems},

volume = {18},

number = {87},

abstract = {The prevalence of opioid use and misuse has provoked a staggering number of deaths over the past two and a half decades. Much attention has focused on individual risks according to various characteristics and experiences. However, broader social and contextual domains are also essential contributors to the opioid crisis such as interpersonal relationships and the conditions of the community and society that people live in. Despite efforts to tackle the issue, the rates of opioid misuse and non-fatal and fatal overdose remain high. Many call for a broad public health approach, but articulation of what such a strategy could entail has not been fully realised. In order to improve the awareness surrounding opioid misuse, we developed a social-ecological framework that helps conceptualise the multivariable risk factors of opioid misuse and facilitates reviewing them in individual, interpersonal, communal and societal levels. Our framework illustrates the multi-layer complexity of the opioid crisis that more completely captures the crisis as a multidimensional issue requiring a broader and integrated approach to prevention and treatment.},

keywords = {Substance use},

pubstate = {published},

tppubtype = {article}

}

@article{661337,

title = {The opioid crisis: need for systems science research},

author = {Mohammad S. Jalali and Michael Botticelli and Rachael Hwang and Howard K Koh and Kathryn R McHugh},

url = {https://scholar.harvard.edu/files/jalali/files/opioid_crisis_systems_science.pdf},

year  = {2020},

date = {2020-01-01},

urldate = {2020-01-01},

journal = {Health Research Policy and Systems},

volume = {18},

number = {88},

abstract = {The opioid epidemic in the United States has had a devastating impact on millions of people as well as on their families and communities. The increased prevalence of opioid misuse, use disorder and overdose in recent years has highlighted the need for improved public health approaches for reducing the tremendous harms of this illness. In this paper, we explain and call for the need for more systems science approaches, which can uncover the complexities of the opioid crisis, and help evaluate, analyse and forecast the effectiveness of ongoing and new policy interventions. Similar to how a stream of systems science research helped policy development in infectious diseases and obesity, more systems science research is needed in opioids.},

keywords = {Simulation modeling, Substance use},

pubstate = {published},

tppubtype = {article}

}