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Spence C, Kurz ME, Sharkey TC, Miller BL. Scoping Literature Review of Disease Modeling of the Opioid Crisis. J Psychoactive Drugs 2024:1-14. [PMID: 38909286 DOI: 10.1080/02791072.2024.2367617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 03/28/2024] [Indexed: 06/24/2024]
Abstract
Opioid misuse continues to cause significant harm. To investigate current research, we conducted a scoping literature review of disease spread models of opioid misuse from January 2000 to December 2022. In total, 85 studies were identified and examined for the opioids modeled, model type, data sources used and model calibration and validation. Most of the studies (58%, 49) only modeled heroin; the next largest categories were prescription opioids and unspecified opioids which accounted for 9% (8) each. Most models were theoretical compartmental models (57) or applied compartmental models (21). Previously published research was the most used data source (38), and a majority of the model validation involved the researchers setting initial conditions to verify theoretical results (30). To represent typical opioid use more accurately, multiple opioids need to be incorporated into the disease spread models, and applying different modeling techniques may allow other insights into opioid misuse spread.
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Affiliation(s)
- Chelsea Spence
- Department of Industrial Engineering, Clemson University, Clemson, SC, USA
| | - Mary E Kurz
- Department of Industrial Engineering, Clemson University, Clemson, SC, USA
| | - Thomas C Sharkey
- Department of Industrial Engineering, Clemson University, Clemson, SC, USA
| | - Bryan Lee Miller
- Department of Sociology, Anthropology and Criminal Justice, Clemson University, Clemson, SC, USA
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Zahan R, Osgood ND, Plouffe R, Orpana H. A Dynamic Model of Opioid Overdose Deaths in Canada during the Co-Occurring Opioid Overdose Crisis and COVID-19 Pandemic. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:442. [PMID: 38673354 PMCID: PMC11050073 DOI: 10.3390/ijerph21040442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 03/23/2024] [Accepted: 03/29/2024] [Indexed: 04/28/2024]
Abstract
With over 40,000 opioid-related overdose deaths between January 2016 and June 2023, the opioid-overdose crisis is a significant public health concern for Canada. The opioid crisis arose from a complex system involving prescription opioid use, the use of prescription opioids not as prescribed, and non-medical opioid use. The increasing presence of fentanyl and its analogues in the illegal drugs supply has been an important driver of the crisis. In response to the overdose crisis, governments at the municipal, provincial/territorial, and federal levels have increased actions to address opioid-related harms. At the onset of the COVID-19 pandemic, concerns emerged over how the pandemic context may impact the opioid overdose crisis. Using evidence from a number of sources, we developed a dynamic mathematical model of opioid overdose death to simulate possible trajectories of overdose deaths during the COVID-19 pandemic. This model incorporates information on prescription opioid use, opioid use not as prescribed, non-medical opioid use, the level of fentanyl in the drug supply, and a measure of the proportion deaths preventable by new interventions. The simulated scenarios provided decision makers with insight into possible trajectories of the opioid crisis in Canada during the COVID-19 pandemic, highlighting the potential of the crisis to take a turn for the worse under certain assumptions, and thus, informing planning during a period when surveillance data were not yet available. This model provides a starting point for future models, and through its development, we have identified important data and evidence gaps that need to be filled in order to inform future action.
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Affiliation(s)
- Rifat Zahan
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5A2, Canada; (R.Z.); (N.D.O.)
| | - Nathaniel D. Osgood
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5A2, Canada; (R.Z.); (N.D.O.)
| | - Rebecca Plouffe
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON K1A 0K9, Canada;
| | - Heather Orpana
- Centre for Surveillance and Applied Research, Public Health Agency of Canada, Ottawa, ON K1A 0K9, Canada;
- School of Psychology, University of Ottawa, Ottawa, ON K1N 6N5, Canada
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Shojaati N, Osgood ND. Opioid-related harms and care impacts of conventional and AI-based prescription management strategies: insights from leveraging agent-based modeling and machine learning. Front Digit Health 2023; 5:1174845. [PMID: 37408540 PMCID: PMC10318360 DOI: 10.3389/fdgth.2023.1174845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 06/05/2023] [Indexed: 07/07/2023] Open
Abstract
Introduction Like its counterpart to the south, Canada ranks among the top five countries with the highest rates of opioid prescriptions. With many suffering from opioid use disorder first having encountered opioids via prescription routes, practitioners and health systems have an enduring need to identify and effectively respond to the problematic use of opioid prescription. There are strong challenges to successfully addressing this need: importantly, the patterns of prescription fulfillment that signal opioid abuse can be subtle and difficult to recognize, and overzealous enforcement can deprive those with legitimate pain management needs the appropriate care. Moreover, injudicious responses risk shifting those suffering from early-stage abuse of prescribed opioids to illicitly sourced street alternatives, whose varying dosage, availability, and the risk of adulteration can pose grave health risks. Methods This study employs a dynamic modeling and simulation to evaluate the effectiveness of prescription regimes employing machine learning monitoring programs to identify the patients who are at risk of opioid abuse while being treated with prescribed opioids. To this end, an agent-based model was developed and implemented to examine the effect of reduced prescribing and prescription drug monitoring programs on overdose and escalation to street opioids among patients, and on the legitimacy of fulfillments of opioid prescriptions over a 5-year time horizon. A study released by the Canadian Institute for Health Information was used to estimate the parameter values and assist in the validation of the existing agent-based model. Results and discussion The model estimates that lowering the prescription doses exerted the most favorable impact on the outcomes of interest over 5 years with a minimum burden on patients with a legitimate need for pharmaceutical opioids. The accurate conclusion about the impact of public health interventions requires a comprehensive set of outcomes to test their multi-dimensional effects, as utilized in this research. Finally, combining machine learning and agent-based modeling can provide significant advantages, particularly when using the latter to gain insights into the long-term effects and dynamic circumstances of the former.
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Butler C, Stechlinski P. Modeling Opioid Abuse: A Case Study of the Opioid Crisis in New England. Bull Math Biol 2023; 85:45. [PMID: 37088864 PMCID: PMC10122875 DOI: 10.1007/s11538-023-01148-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 03/22/2023] [Indexed: 04/25/2023]
Abstract
For the past two decades, the USA has been embroiled in a growing prescription drug epidemic. The ripples of this epidemic have been especially apparent in the state of Maine, which has fought hard to mitigate the damage caused by addiction to pharmaceutical and illicit opioids. In this study, we construct a mathematical model of the opioid epidemic incorporating novel features important to better understanding opioid abuse dynamics. These features include demographic differences in population susceptibility, general transmission expressions, and combined consideration of pharmaceutical opioid and heroin abuse. We demonstrate the usefulness of this model by calibrating it with data for the state of Maine. Model calibration is accompanied by sensitivity and uncertainty analysis to quantify potential error in parameter estimates and forecasts. The model is analyzed to determine the mechanisms most influential to the number of opioid abusers and to find effective ways of controlling opioid abuse prevalence. We found that the mechanisms most influential to the overall number of abusers in Maine are those involved in illicit pharmaceutical opioid abuse transmission. Consequently, preventative strategies that controlled for illicit transmission were more effective over alternative approaches, such as treatment. These results are presented with the hope of helping to inform public policy as to the most effective means of intervention.
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Affiliation(s)
- Cole Butler
- Department of Mathematics and Statistics, University of Maine, 5752 Neville Hall, Orono, ME, 04469, USA
| | - Peter Stechlinski
- Department of Mathematics and Statistics, University of Maine, 5752 Neville Hall, Orono, ME, 04469, USA.
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Wang W, Lu S, Tang H, Wang B, Sun C, Zheng P, Bai Y, Lu Z, Kang Y. A Scoping Review of Drug Epidemic Models. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19042017. [PMID: 35206206 PMCID: PMC8872096 DOI: 10.3390/ijerph19042017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/21/2022] [Accepted: 01/26/2022] [Indexed: 02/05/2023]
Abstract
The phenomenon of drug epidemics has been a global issue in the past decades, causing enormous damages to the physical and mental health of drug users and social well-being. Despite great efforts to curb drug epidemics at the governmental or social level, the total number of drug users has still been on the rise in recent years, along with illicit production and trafficking around the world. Inspired by dynamical epidemic models of infectious disease, a flourishment of promising results has been observed in the exploration of drug epidemic models. In this review, we aim to provide a scoping review of all existing drug epidemic modeling studies, and it has been shown that most studies focused on analyses of theoretical behaviors of the model systems, lacking emphasis on practical applications in real settings. We found that the drug epidemic models were characterized by a longer time scale, no incubation period, no significant prevention vaccines interfered, and population specificity. This review could assist policymakers and public health workers in gaining deeper insights into modeling tools, and help modelers improve their works, thus narrowing gaps between mathematical epidemiology and public health studies.
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Affiliation(s)
- Wei Wang
- Institute of Environmental Information, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (W.W.); (B.W.); (C.S.)
| | - Sifen Lu
- Precision Medicine Key Laboratory of Sichuan Province and Precision Medicine Center, West China Hospital, Sichuan University, Chengdu 610041, China;
| | - Haoxiang Tang
- Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China;
| | - Biao Wang
- Institute of Environmental Information, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (W.W.); (B.W.); (C.S.)
| | - Caiping Sun
- Institute of Environmental Information, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (W.W.); (B.W.); (C.S.)
| | - Pai Zheng
- Department of Occupational and Environmental Health Science, School of Public Health, Peking University, Beijing 100871, China;
| | - Yi Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100871, China;
| | - Zuhong Lu
- State Key Lab of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China;
| | - Yulin Kang
- Institute of Environmental Information, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (W.W.); (B.W.); (C.S.)
- Correspondence:
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Dickson-Gomez J, Christenson E, Weeks M, Galletly C, Wogen J, Spector A, McDonald M, Ohlrich J. Effects of Implementation and Enforcement Differences in Prescription Drug Monitoring Programs in 3 States: Connecticut, Kentucky, and Wisconsin. SUBSTANCE ABUSE-RESEARCH AND TREATMENT 2021; 15:1178221821992349. [PMID: 33854323 PMCID: PMC8013627 DOI: 10.1177/1178221821992349] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 01/12/2021] [Indexed: 11/23/2022]
Abstract
Background and aims: Prescription Drug Monitoring Programs (PDMPs) were designed to curb opioid misuse and diversion by tracking scheduled medications prescribed by medical providers and dispensed by pharmacies. The effects of PDMPs on opioid prescription, misuse and overdose rates have been mixed due in part to variability in states’ PDMPs and difficulties measuring this complexity, and a lack of attention to implementation and enforcement of PDMP components. The current study uses qualitative interviews with key informants from 3 states with different PDMPs, Connecticut, Kentucky and Wisconsin to explore differences in the characteristics of the PDMPs in each state; how they are implemented, monitored and enforced; and unintended negative consequences of these programs. Methods: We conducted in-depth interviews with key informants from each state representing the following sectors: PDMP and pain clinic regulation agencies, Medicaid programs, state licensing boards, pharmacies, emergency medicine departments, pain management clinics, first responders, drug courts, drug treatment programs, medication assisted treatment (MAT) providers, and harm reduction organizations. Interview guides explored participants’ experiences with and opinions of PDMPs according to their roles. Data analysis was conducted using a collaborative, constant comparison method. Results: While all 3 states had mandated registration and reporting requirements, the states differed in the implementation and enforcement of these and the extent to which provider prescribing was monitored. These, in turn, influenced how medical providers perceived the PDMP and changed how providers prescribed opioids. Unintended consequences of state PDMPs included under-prescribing for pain and “dumping” patients who were long term users of opioids or who had developed opioid use disorders and may explain the increase in illicit heroin or opioid use. Conclusion: State PDMPs with similar mandates may differ greatly in implementation and enforcement. These differences are important to consider when determining the effects of PDMPs on opioid misuse and overdose.
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Affiliation(s)
- Julia Dickson-Gomez
- Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Erika Christenson
- Center for AIDS Intervention Research, Medical College of Wisconsin, Milwaukee, WI, USA
| | | | - Carol Galletly
- Center for AIDS Intervention Research, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Jennifer Wogen
- Department of Public Health Sciences, University of Connecticut, Farmington, CT, USA
| | - Antoinette Spector
- Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Madelyn McDonald
- Center for Drug and Alcohol Research, University of Kentucky, Lexington, KY, USA
| | - Jessica Ohlrich
- Institute for Health and Equity, Medical College of Wisconsin, Milwaukee, WI, USA
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Data Needs in Opioid Systems Modeling: Challenges and Future Directions. Am J Prev Med 2021; 60:e95-e105. [PMID: 33272714 PMCID: PMC8061725 DOI: 10.1016/j.amepre.2020.08.017] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 08/05/2020] [Accepted: 08/17/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION 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 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 policymakers' research questions and policy goals. CONCLUSIONS This article provides an important step in identifying and discussing data challenges in opioid research generally and opioid systems modeling specifically. It also identifies opportunities for systems modelers and government agencies to improve opioid systems models.
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Beaulieu E, DiGennaro C, Stringfellow E, Connolly A, Hamilton A, Hyder A, Cerdá M, Keyes KM, Jalali MS. Economic Evaluation in Opioid Modeling: Systematic Review. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2021; 24:158-173. [PMID: 33518022 PMCID: PMC7864393 DOI: 10.1016/j.jval.2020.07.013] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 06/29/2020] [Accepted: 07/25/2020] [Indexed: 05/08/2023]
Abstract
OBJECTIVES The 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. METHODS A 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. RESULTS The 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 studies' accounting for patient and physician preference, changing costs, or result stratification were largely ignored in these SBEEs. CONCLUSION The review shows consistently favorable cost analysis findings for naloxone distribution strategies and opioid agonist treatments and identifies major gaps for future research.
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Affiliation(s)
- Elizabeth Beaulieu
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA
| | - Catherine DiGennaro
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA
| | - Erin Stringfellow
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA
| | - Ava Connolly
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA
| | - Ava Hamilton
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Ayaz Hyder
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, OH, USA
| | - Magdalena Cerdá
- Center for Opioid Epidemiology and Policy, Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - Katherine M Keyes
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Mohammad S Jalali
- MGH Institute for Technology Assessment, Harvard Medical School, Boston, MA, USA; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.
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Jalali MS, Botticelli M, Hwang RC, Koh HK, McHugh RK. The opioid crisis: need for systems science research. Health Res Policy Syst 2020; 18:88. [PMID: 32771004 PMCID: PMC7414582 DOI: 10.1186/s12961-020-00598-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 06/29/2020] [Indexed: 01/07/2023] Open
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.
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Affiliation(s)
- Mohammad S. Jalali
- grid.38142.3c000000041936754XMGH Institute for Technology Assessment, Harvard Medical School, 101 Merrimac St, Suite 1010, Boston, MA 02114 United States of America ,grid.116068.80000 0001 2341 2786MIT Sloan School of Management, 100 Main St, Cambridge, MA 02142 United States of America
| | - Michael Botticelli
- grid.239424.a0000 0001 2183 6745Grayken Center for Addiction, Boston Medical Center, Boston, MA United States of America
| | - Rachael C. Hwang
- grid.116068.80000 0001 2341 2786MIT Sloan School of Management, 100 Main St, Cambridge, MA 02142 United States of America
| | - Howard K. Koh
- grid.38142.3c000000041936754XT.H. Chan School of Public Health, Harvard
University, Boston, MA United States of America ,grid.38142.3c000000041936754XHarvard Kennedy School, Harvard University, Cambridge, MA United States of America
| | - R. Kathryn McHugh
- grid.38142.3c000000041936754XMGH Institute for Technology Assessment, Harvard Medical School, 101 Merrimac St, Suite 1010, Boston, MA 02114 United States of America ,grid.240206.20000 0000 8795 072XDivision of Alcohol and Drug Abuse, McLean Hospital, Belmont, MA United States of America
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Homer J, Wakeland W. A dynamic model of the opioid drug epidemic with implications for policy. THE AMERICAN JOURNAL OF DRUG AND ALCOHOL ABUSE 2020; 47:5-15. [PMID: 32515234 DOI: 10.1080/00952990.2020.1755677] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Background: The U.S. opioid epidemic has caused substantial harm for over 20 years. Policy interventions have had limited impact and sometimes backfired. Experts recommend a systems modeling approach to address the complexities of opioid policymaking.Objectives: Develop a system dynamics simulation model that reflects the complexities and can anticipate intended and unintended intervention effects.Methods: The model was developed from literature review and data gathering. Its outputs, starting in 1990, were compared against 12 historical time series. Four illustrative interventions were simulated for 2020-2030: reducing prescription dosage by 20%, cutting diversion by 30%, increasing addiction treatment from 45% to 65%, and increasing lay naloxone use from 4% to 20%. Sensitivity testing was performed to determine effects of uncertainties. No human subjects were studied.Results: The model fits historical data well with error percentage averaging 9% across 201 data points. Interventions to reduce dosage and diversion reduce the number of persons with opioid use disorder (PWOUD) by 11% and 16%, respectively, but each of these interventions reduces overdoses by only 1%. Boosting treatment reduces overdoses by 3% but increases PWOUD by 1%. Expanding naloxone reduces overdose deaths by 12% but increases PWOUD by 2% and overdoses by 3%. Combining all four interventions reduces PWOUD by 24%, overdoses by 4%, and deaths by 18%. Uncertainties may affect these numerical results, but policy findings are unchanged.Conclusion: No single intervention significantly reduces both PWOUD and overdose deaths, but a combination strategy can do so. Entering the 2020s, only protective measures like naloxone expansion could significantly reduce overdose deaths.
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Affiliation(s)
- Jack Homer
- Homer Consulting, Barrytown, New York, USA
| | - Wayne Wakeland
- Systems Science Graduate Program, Portland State University, Portland, Oregon, USA
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