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      Signal of Increased Opioid Overdose during COVID-19 from Emergency Medical Services Data

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Highlights

          • •

            COVID-19 pandemic disrupted treatment service delivery and harm reduction.

          • •

            Individuals with opioid use disorder may be at heightened risk of opioid overdose.

          • •

            Emergency medical services (EMS) data is a timely source for overdose surveillance.

          • •

            Kentucky EMS opioid overdose runs increased significantly during COVID-19 period.

          • •

            In contrast, average EMS daily runs for other conditions leveled or declined.

          Abstract

          Background

          Individuals with opioid use disorder may be at heightened risk of opioid overdose during the COVID-19 period of social isolation, economic distress, and disrupted treatment services delivery. This study evaluated changes in daily number of Kentucky emergency medical services (EMS) runs for opioid overdose between January 14, 2020 and April 26, 2020.

          Methods

          We evaluated the statistical significance of the changes in the average daily EMS opioid overdose runs in the 52 days before and after the COVID-19 state of emergency declaration, March 6, 2020.

          Results

          Kentucky EMS opioid overdose daily runs increased after the COVID-19 state emergency declaration. In contrast, EMS daily runs for other conditions leveled or declined. There was a 17% increase in the number of EMS opioid overdose runs with transportation to an emergency department (ED), a 71% increase in runs with refused transportation, and a 50% increase in runs for suspected opioid overdoses with deaths at the scene. The average daily EMS opioid overdose runs with refused transportation increased significantly, doubled to an average of 8 opioid overdose patients refusing transportation every day during the COVID-19-related study period.

          Conclusions

          This Kentucky-specific study provides empirical evidence for concerns that opioid overdoses are rising during the COVID-19 pandemic and calls for sharing of observations and analyses from different regions and surveillance systems with timely data collection (e.g., EMS data, syndromic surveillance data for ED visits) to improve our understanding of the situation, inform proactive response, and prevent another big wave of opioid overdoses in our communities.

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          Interrupted time series regression for the evaluation of public health interventions: a tutorial

          James Lopez Bernal, Steven Cummins, Antonio Gasparrini (2016)
          Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.
          Article 0 comments Cited 945 times – based on 0 reviews     Review now
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            An Epidemic in the Midst of a Pandemic: Opioid Use Disorder and COVID-19

            G Alexander, Kenneth Stoller, Rebecca Haffajee … (2020)
            The COVID-19 pandemic is a particularly grave risk to the millions of Americans with opioid use disorder, who—already vulnerable and marginalized—are heavily dependent on face-to-face health care delivery. These authors propose rapid and coordinated action on the part of clinicians and policymakers to mitigate risks of disrupted care for these patients.
            Article 0 comments Cited 160 times – based on 0 reviews     Review now
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              When Epidemics Collide: Coronavirus Disease 2019 (COVID-19) and the Opioid Crisis

              William C Becker, David A. Fiellin (2020)
              COVID-19 could cause infection in persons with opioid use disorder, increase opioid overdose rates, reverse system-level gains in expanding access to medication for opioid use disorder, halt critical research, and prevent exacting legal reparations against opioid manufacturers. The authors call for urgent action to counteract these risks.
              Article 0 comments Cited 104 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Svetla Slavova
                Journal
                Journal ID (nlm-ta): Drug Alcohol Depend
                Journal ID (iso-abbrev): Drug Alcohol Depend
                Title: Drug and Alcohol Dependence
                Publisher: Published by Elsevier B.V.
                ISSN (Print): 0376-8716
                ISSN (Electronic): 1879-0046
                Publication date PMC-release: 10 July 2020
                Publication date (Electronic): 10 July 2020
                Electronic Location Identifier: 108176
                Affiliations
                [a ]Department of Biostatistics, University of Kentucky, Lexington, KY, United States
                [b ]Kentucky Injury Prevention and Research Center, University of Kentucky, Lexington, KY, United States
                [c ]Department of Health Management and Policy, University of Kentucky, Lexington, KY, United States
                [d ]Department of Behavioral Science, University of Kentucky, Lexington, KY, United States
                [e ]Center on Drug and Alcohol Research, University of Kentucky, Lexington, KY, United States
                Author notes
                [* ]Corresponding author at: Department of Biostatistics, University of Kentucky, Healthy Kentucky Research Building RB2, Office 261, 760 Press Ave, Lexington, KY 40536, United States ssslav2@ 123456email.uky.edu
                Article
                Publisher ID: S0376-8716(20)30341-0 Publisher ID: 108176
                DOI: 10.1016/j.drugalcdep.2020.108176
                PMC ID: 7351024
                PubMed ID: 32717504
                SO-VID: 05ac7296-c23b-4654-aefd-e17880ca6a23
                Copyright © © 2020 Published by Elsevier B.V.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 16 May 2020
                Date revision received : 6 June 2020
                Date accepted : 1 July 2020
                Categories
                Subject: Article

                ScienceOpen disciplines: Health & Social care
                Keywords: opioid overdose,emergency medical services,interrupted time series,segmented regression,covid-19
                Data availability:
                ScienceOpen disciplines: Health & Social care
                Keywords: opioid overdose, emergency medical services, interrupted time series, segmented regression, covid-19

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