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Modeling the evolution of the US opioid crisis for national policy development
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 Academie...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191351/ https://www.ncbi.nlm.nih.gov/pubmed/35639699 http://dx.doi.org/10.1073/pnas.2115714119 |
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author | Lim, Tse Yang Stringfellow, Erin J. Stafford, Celia A. DiGennaro, Catherine Homer, Jack B. Wakeland, Wayne Eggers, Sara L. Kazemi, Reza Glos, Lukas Ewing, Emily G. Bannister, Calvin B. Humphreys, Keith Throckmorton, Douglas C. Jalali, Mohammad S. |
author_facet | Lim, Tse Yang Stringfellow, Erin J. Stafford, Celia A. DiGennaro, Catherine Homer, Jack B. Wakeland, Wayne Eggers, Sara L. Kazemi, Reza Glos, Lukas Ewing, Emily G. Bannister, Calvin B. Humphreys, Keith Throckmorton, Douglas C. Jalali, Mohammad S. |
author_sort | Lim, Tse Yang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9191351 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-91913512022-06-14 Modeling the evolution of the US opioid crisis for national policy development Lim, Tse Yang Stringfellow, Erin J. Stafford, Celia A. DiGennaro, Catherine Homer, Jack B. Wakeland, Wayne Eggers, Sara L. Kazemi, Reza Glos, Lukas Ewing, Emily G. Bannister, Calvin B. Humphreys, Keith Throckmorton, Douglas C. Jalali, Mohammad S. Proc Natl Acad Sci U S A Biological Sciences 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. National Academy of Sciences 2022-05-31 2022-06-07 /pmc/articles/PMC9191351/ /pubmed/35639699 http://dx.doi.org/10.1073/pnas.2115714119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Biological Sciences Lim, Tse Yang Stringfellow, Erin J. Stafford, Celia A. DiGennaro, Catherine Homer, Jack B. Wakeland, Wayne Eggers, Sara L. Kazemi, Reza Glos, Lukas Ewing, Emily G. Bannister, Calvin B. Humphreys, Keith Throckmorton, Douglas C. Jalali, Mohammad S. Modeling the evolution of the US opioid crisis for national policy development |
title | Modeling the evolution of the US opioid crisis for national policy development |
title_full | Modeling the evolution of the US opioid crisis for national policy development |
title_fullStr | Modeling the evolution of the US opioid crisis for national policy development |
title_full_unstemmed | Modeling the evolution of the US opioid crisis for national policy development |
title_short | Modeling the evolution of the US opioid crisis for national policy development |
title_sort | modeling the evolution of the us opioid crisis for national policy development |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191351/ https://www.ncbi.nlm.nih.gov/pubmed/35639699 http://dx.doi.org/10.1073/pnas.2115714119 |
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