Citation

Bunn TL, Costich JF, Mirzaian M, Daniels LK, Wang D, Quesinberry D. Inj. Prev. 2023; ePub(ePub): ePub.

Copyright

(Copyright © 2023, BMJ Publishing Group)

DOI

10.1136/ip-2023-044894

PMID

37648420

Abstract

BACKGROUND: Variation among industries in the association between COVID-19-related closing or reopening orders and drug overdose deaths is unknown. The objectives of this study were to compare drug overdose decedent demographics, annual drug overdose fatality rates and monthly drug overdose fatality rates by specific industry within the service-related industry sector, and to perform an interrupted time series analysis comparing weekly drug overdose mortality counts in service-related and non-service-related industries, examining the COVID-19 pre-pandemic and pandemic phases by Kentucky closing and reopening orders.

METHODS: Kentucky drug overdose death certificate and toxicology testing data for years 2018-2021 were analysed using Χ(2) and interrupted time series methods.

RESULTS: Before the pandemic, annual drug overdose fatality rates in service-related industries were higher than in non-service-related industries. However, these trends reversed during the pandemic. Both service-related and non-service-related industry groups experienced increased fatal drug overdoses at change points associated with the gubernatorial business closure orders, although the magnitude of the increase differed between the two groups. Young, female and black workers in service-related industries had higher frequencies of drug overdose deaths compared with decedents in the non-service-related industries.

CONCLUSION: Spikes in drug overdose mortality in both service-related and non-service-related industries during the pandemic highlight the need to consider and include industries and occupations, as well as worker populations vulnerable to infectious diseases, as integral stakeholder groups when developing and implementing drug overdose prevention interventions, and implementing infectious disease surveillance systems.

Language: en

Keywords

COVID-19; poisoning; drugs; time series