Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action
Year: 2021
Type: review
Abstract: The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.
Source: Translational research
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,930
Awards: Real-time prediction of emerging drug use epidemics in the United States, G2581201397, G3455198839, G374196923, G4943218370, G55634203, G565857054, Heroin in Transition, G7033059115, Ethno-epidemiology of HCV, HIV and Overdose associated with Drug Markets and Drug Tourism, G7557759041, G8696185941, UC San Diego Clinical and Translational Research Institute, Training Program in Substance Use, HIV and Related Infections, San Diego Center for AIDS Research (SD CFAR)
OpenAlex ID: W3151317736