Disruptions to naloxone training among lay and occupational responders in Maryland during the emergence of COVID-19: early impacts, recovery, and lessons learned.

COVID-19 harm reduction naloxone overdose prevention

Journal

Drug and alcohol dependence reports
ISSN: 2772-7246
Titre abrégé: Drug Alcohol Depend Rep
Pays: Netherlands
ID NLM: 9918350383506676

Informations de publication

Date de publication:
16 Jun 2023
Historique:
received: 22 03 2023
revised: 01 06 2023
accepted: 05 06 2023
medline: 26 6 2023
pubmed: 26 6 2023
entrez: 26 6 2023
Statut: aheadofprint

Résumé

: Opioid overdose death rates increased during the COVID-19 pandemic. Disruptions in community-based naloxone trainings could have reduced the likelihood of overdose reversal and increased the chances of a fatal overdose. We investigated changes in the number of people trained in naloxone administration and distribution in Maryland before, during, and after COVID-related stay-at-home orders. : Data on naloxone training are from the Maryland Department of Health. We used interrupted time series models to estimate changes in average monthly number of people trained: [1] pre-interruption (4/2019-3/2020), [2] 1-month post-interruption (4/2020-5/2020), and [3] 12-months post-interruption (4/2020-3/2021). Trainees were classified as lay (e.g., people who use drugs) or occupational (e.g., law enforcement officers and harm reduction workers) responders. : There were 101,332 trainees; 54.1% lay, 21.5% occupational, and 23.4% unknown responder status. We observed a decrease in the average monthly number of trainees in the pre-interruption period (-235, : Findings suggest a marked decrease in naloxone trainees immediately after stay-at-home order, followed by a moderate rebound in the 12-months after stay-at-home order. The decrease in occupational responders trained may have limited access to naloxone, but would likely have been offset by increases in number of lay responders trained. Strengthening lay and occupational responder connections could maintain naloxone distribution during public health crises.

Sections du résumé

Background UNASSIGNED
: Opioid overdose death rates increased during the COVID-19 pandemic. Disruptions in community-based naloxone trainings could have reduced the likelihood of overdose reversal and increased the chances of a fatal overdose. We investigated changes in the number of people trained in naloxone administration and distribution in Maryland before, during, and after COVID-related stay-at-home orders.
Methods UNASSIGNED
: Data on naloxone training are from the Maryland Department of Health. We used interrupted time series models to estimate changes in average monthly number of people trained: [1] pre-interruption (4/2019-3/2020), [2] 1-month post-interruption (4/2020-5/2020), and [3] 12-months post-interruption (4/2020-3/2021). Trainees were classified as lay (e.g., people who use drugs) or occupational (e.g., law enforcement officers and harm reduction workers) responders.
Results UNASSIGNED
: There were 101,332 trainees; 54.1% lay, 21.5% occupational, and 23.4% unknown responder status. We observed a decrease in the average monthly number of trainees in the pre-interruption period (-235,
Conclusions UNASSIGNED
: Findings suggest a marked decrease in naloxone trainees immediately after stay-at-home order, followed by a moderate rebound in the 12-months after stay-at-home order. The decrease in occupational responders trained may have limited access to naloxone, but would likely have been offset by increases in number of lay responders trained. Strengthening lay and occupational responder connections could maintain naloxone distribution during public health crises.

Identifiants

pubmed: 37362079
doi: 10.1016/j.dadr.2023.100173
pii: S2772-7246(23)00043-4
pmc: PMC10271935
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100173

Subventions

Organisme : NIDA NIH HHS
ID : T32 DA007292
Pays : United States

Informations de copyright

© 2023 The Author(s).

Déclaration de conflit d'intérêts

None

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Auteurs

Himani Byregowda (H)

Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.

Catherine Tomko (C)

Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health.

Kristin E Schneider (KE)

Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health.

Erin Russell (E)

Center for Harm Reduction Services, Maryland Department of Health.

Renee M Johnson (RM)

Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.

Ryoko Susukida (R)

Department of Mental Health, Johns Hopkins Bloomberg School of Public Health.

Saba Rouhani (S)

Department of Epidemiology, New York University School of Global Public Health.

Taylor Parnham (T)

Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health.

Ju Nyeong Park (JN)

Division of General Internal Medicine, Warren Alpert Medical School, Brown University.

Classifications MeSH