@article{ref1,
title="Use of laboratory data for illicit drug use surveillance and identification of socioeconomic risk factors",
journal="Drug and alcohol dependence",
year="2022",
author="Azimi, Vahid and Jackups, Ronald Jr and Farnsworth, Christopher W. and Budelier, Melissa M.",
volume="236",
number="",
pages="e109499-e109499",
abstract="BACKGROUND: Drug overdose is the leading cause of death among people 25-44 years of age in the United States. Existing drug surveillance methods are important for prevention and directing treatment, but are limited by delayed reporting and lack of geographic granularity. <br><br>METHODS: Laboratory urine drug screen and complete metabolic panel data from patients presenting to the emergency department was used to observe long-term and short-term temporal and geospatial changes at the zip code-level in St. Louis. Multivariate linear regression was performed to investigate associations between zip code-level socioeconomic factors and drug screening positivity rates. <br><br>RESULTS: An increase in the fentanyl positive drug screens was seen during the initial COVID-19 shutdown period in the spring of 2020. A decrease in cocaine positivity was seen in the fall and winter of 2020, with a return to baseline coinciding with the second major COVID-19 shutdown in the summer of 2021. These changes appeared to be independent of changes in emergency department utilization as measured by complete metabolic panels ordered. Significant short-term changes in fentanyl and cocaine positivity rates between specific time periods were able to be localized to individual zip codes. Zip code-level multivariate analysis demonstrated independent associations between socioeconomic/demographic factors and fentanyl/cocaine positivity rates as determined by laboratory drug screening data. <br><br>CONCLUSIONS: Analyzing clinical laboratory drug screening data can enable a more temporally and geographically granular view of population-level drug use surveillance. Additionally, laboratory data can be utilized to find population-level socioeconomic associations with illicit drug use, presenting a potential avenue for the use of this data to guide public health and healthcare policy decisions.<p /> <p>Language: en</p>",
language="en",
issn="0376-8716",
doi="10.1016/j.drugalcdep.2022.109499",
url="http://dx.doi.org/10.1016/j.drugalcdep.2022.109499"
}