Journal of Science Policy & Governance
Volume 23, Issue 01 | October 23, 2023

Policy Brief: Enhancing Epidemiologic Surveillance to Address the Opioid Epidemic: Overcoming
Challenges and Embracing Opportunities

Ebony D. Johnson (1),(2)
  1. University of Michigan, Department of Sociology, Ann Arbor, MI, USA
  2. Emory University, Department of Epidemiology, Atlanta, GA, USA
​​ ​
Corresponding author: [email protected]
Keywords: opioid epidemic; health policy; data science; health equity; syndromic surveillance
https://doi.org/10.38126/JSPG230105
​

Executive Summary

The United States is currently facing an alarming opioid epidemic, with overdose deaths rising by over 250% between 1999 and 2019. Synthetic opioids, polysubstance use, and stimulants have emerged as the primary contributors to this crisis. The COVID-19 pandemic has further exacerbated the situation, resulting in a 30% surge in overdose deaths in 2020, with indications of continued increases over time. Not only has this crisis taken a devastating toll on public health, but it has also imposed an immense financial burden, with costs reaching approximately $1.5 trillion in 2020 alone. To effectively address this multifaceted issue, it is imperative to adopt a comprehensive approach that encompasses epidemiology, clinical practices, and forensic investigations. Crucially, accurate and comprehensive data on opioid overdoses are vital for the development of evidence-based strategies. This policy brief highlights the urgent need to improve data infrastructure and collection methods, establish standardized definitions, and harness the potential of modern data science techniques. By prioritizing public health, fostering collaborations, and allocating necessary resources, we can effectively combat the opioid crisis and work towards a healthier future for all.

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Background header image courtesy of Common Wealth Fund
Ebony D. Johnson is a sociology doctoral candidate at the University of Michigan-Ann Arbor, specializing in the social determinants of neuropsychiatric health and research methods. She recently completed the Rollins Epidemiology Fellowship at Emory University, working as a substance use epidemiologist. Ebony is also a Science Policy Scholar-in-Residence with the National Science Policy Network. She holds an M.Sc. in epidemiologic science, an M.A. in sociology, and a Joint B.S. in public health/women's and gender Studies.

Acknowledgements
I would like to thank Beatrice King for her feedback on this paper.​

References

  1. Allen, Bennett, and Magdalena Cerdá. 2022. “Opportunities for Opioid Overdose Prediction: Building a Population Health Approach.” The Lancet Digital Health 4 (6): e403–4. https://doi.org/10.1016/S2589-7500(22)00097-8.
  2. Cerdá, Magdalena, and Katherine M Keyes. 2019. “Systems Modeling to Advance the Promise of Data Science in Epidemiology.” American Journal of Epidemiology 188 (5): 862–65. https://doi.org/10.1093/aje/kwy262.
  3. Chiang, Katelyn V., Ekwutosi M. Okoroh, Laurin J. Kasehagen, Luigi F. Garcia-Saavedra, and Jean Y. Ko. 2019. “Standardization of State Definitions for Neonatal Abstinence Syndrome Surveillance and the Opioid Crisis.” American Journal of Public Health 109 (9): 1193–97. https://doi.org/10.2105/AJPH.2019.305170.
  4. Committee on the Review of Specific Programs in the Comprehensive Addiction and Recovery Act, Board on Population Health and Public Health Practice, Health and Medicine Division, and National Academies of Sciences, Engineering, and Medicine. 2020. Measuring Success in Substance Use Grant Programs: Outcomes and Metrics for Improvement. Washington, D.C.: National Academies Press. https://doi.org/10.17226/25745.
  5. Council for State and Territorial Epidemiologists. 2019. “Neonatal Abstinence Syndrome Standardized Case Definition.”19-MCH-01. Maternal &Child Health Subcommittee, Council for State and Territorial Epidemiologists. https://cdn.ymaws.com/www.cste.org/resource/resmgr/2019ps/final/19-MCH-01_final_7.31.19.pdf.
  6. Decoteau, Claire Laurier, and Cal Lee Garrett. 2022. “Disease Surveillance Infrastructure and the Economisation of Public Health.” Sociology of Health & Illness 44 (8): 1251–69. https://doi.org/10.1111/1467-9566.13514.
  7. Hoots, Brooke E. 2021. “Opioid Overdose Surveillance: Improving Data to Inform Action.” Public Health Reports 136 (1_suppl): 5S-8S. https://doi.org/10.1177/00333549211020275.
  8. Horon, Isabelle L., Pooja Singal, David R. Fowler, and Joshua M. Sharfstein. 2018. “Standard Death Certificates Versus Enhanced Surveillance to Identify Heroin Overdose–Related Deaths.” American Journal of Public Health 108 (6): 777–81. https://doi.org/10.2105/AJPH.2018.304385.​
  9. Jalali, Mohammad S., Michael Botticelli, Rachael C. Hwang, Howard K. Koh, and R. Kathryn McHugh. 2020. “The Opioid Crisis: Need for Systems Science Research.” Health Research Policy and Systems 18 (1): 88. https://doi.org/10.1186/s12961-020-00598-6.
  10. Johnson, Marina, Abdullah Albizri, Antoine Harfouche, and Salih Tutun. 2021. “Digital Transformation to Mitigate Emergency Situations: Increasing Opioid Overdose Survival Rates through Explainable Artificial Intelligence.” Industrial Management & Data Systems 123 (1): 324–44. https://doi.org/10.1108/IMDS-04-2021-0248.
  11. Larochelle, Marc R., Svetla Slavova, Elisabeth D. Root, Daniel J. Feaster, Patrick J. Ward, Sabrina C. Selk, Charles Knott, Jennifer Villani, and Jeffrey H. Samet. 2021. “Disparities in Opioid Overdose Death Trends by Race/Ethnicity, 2018–2019, From the HEALing Communities Study.” American Journal of Public Health 111 (10): 1851–54. https://doi.org/10.2105/AJPH.2021.306431.
  12. Latimore, Amanda D., Justine Newman, and Leo Beletsky. 2022. “Build It Better for Public Health: Improved Data Infrastructure Is Vital to Bending the Curve of the Overdose Crisis.” American Journal of Public Health 112 (S1): S39–41. https://doi.org/10.2105/AJPH.2021.306697.
  13. Leist, Anja K., Matthias Klee, Jung Hyun Kim, David H. Rehkopf, Stéphane P. A. Bordas, Graciela Muniz-Terrera, and Sara Wade. 2022. “Mapping of Machine Learning Approaches for Description, Prediction, and Causal Inference in the Social and Health Sciences.” Science Advances 8 (42): eabk1942. https://doi.org/10.1126/sciadv.abk1942.
  14. Link, Bruce G. 2008. “Epidemiological Sociology and the Social Shaping of Population Health.” Journal of Health and Social Behavior 49 (4): 367–84. https://doi.org/10.1177/002214650804900401.
  15. Lucyk, Scott N., and Lewis S. Nelson. 2017. “Toxicosurveillance in the US Opioid Epidemic.” International Journal of Drug Policy 46 (August): 168–71. https://doi.org/10.1016/j.drugpo.2017.05.057.
  16. Mandl, Kenneth D., J. Marc Overhage, Michael M. Wagner, William B. Lober, Paola Sebastiani, Farzad Mostashari, Julie A. Pavlin, et al. 2004. “Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience.” Journal of the American Medical Informatics Association : JAMIA 11 (2): 141–50. https://doi.org/10.1197/jamia.M1356.
  17. Matero, Matthew, Salvatore Giorgi, Brenda Curtis, Lyle H. Ungar, and H. Andrew Schwartz. 2023. “Opioid Death Projections with AI-Based Forecasts Using Social Media Language.” Npj Digital Medicine 6 (1): 1–11. https://doi.org/10.1038/s41746-023-00776-0.
  18. Petteway, Ryan J. 2023. “On Epidemiology as Racial-Capitalist (Re)Colonization and Epistemic Violence.” Critical Public Health 33 (1): 5–12. https://doi.org/10.1080/09581596.2022.2107486.
  19. Slavova, Svetla, Chris Delcher, Jeannine M. Buchanich, Terry L. Bunn, Bruce A. Goldberger, and Julia F. Costich. 2019. “Methodological Complexities in Quantifying Rates of Fatal Opioid-Related Overdose.” Current Epidemiology Reports 6 (2): 263–74. https://doi.org/10.1007/s40471-019-00201-9.
  20. Tote, Katherine M., Heather Bradley, Erika G. Martin, Recai Yucel, and Eli S. Rosenberg. 2019. “Factors Associated with Incomplete Toxicology Reporting in Drug Overdose Deaths, 2010–2016.” Annals of Epidemiology 38 (October): 65–69. https://doi.org/10.1016/j.annepidem.2019.08.006.
  21. Vivolo-Kantor, Alana M., Herschel Smith, and Lawrence Scholl. 2021. “Differences and Similarities between Emergency Department Syndromic Surveillance and Hospital Discharge Data for Nonfatal Drug Overdose.” Annals of Epidemiology 62 (October): 43–50. https://doi.org/10.1016/j.annepidem.2021.05.008.
  22. Ward, Patrick J., Peter J. Rock, Svetla Slavova, April M. Young, Terry L. Bunn, and Ramakanth Kavuluru. 2019. “Enhancing Timeliness of Drug Overdose Mortality Surveillance: A Machine Learning Approach.” PLOS ONE 14 (10): e0223318. https://doi.org/10.1371/journal.pone.0223318.
  23. Wiemken, Timothy L., and Robert R. Kelley. 2020. “Machine Learning in Epidemiology and Health Outcomes Research.” Annual Review of Public Health 41 (1): 21–36. https://doi.org/10.1146/annurev-publhealth-040119-094437.
  24. Wiens, Terra, Elisabeth Bilden, Stefan Saravia, Jason Peterson, Matthew Wogen, Kaila Hanson, Roon Makhtal, Nate Wright, Jon Roesler, and Ruth Lynfield. 2021. “Biosurveillance of Drug Overdoses and Substance Misuse Treated in Selected Emergency Departments in Minnesota, 2017-2020.” Public Health Reports 136 (1_suppl): 87S-95S. https://doi.org/10.1177/00333549211042834.
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