Evidence map›Paper›PMID 31195333›Full record

ArticleWater research2019

Long-term tracking of opioid consumption in two United States cities using wastewater-based epidemiology approach.

Adam J Gushgari, Arjun K Venkatesan, Jing Chen, Joshua C Steele, Rolf U Halden

Open access · greenAbstract read
In one paragraph

Article in Water research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

27 citing papers in PubMed, 80 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Fatal overdose: Predicting to prevent.The International journal on drug policy · 2022
    Article
  18. Article
  19. "Waste Not, Want Not" - Leveraging Sewer Systems and Wastewater-Based Epidemiology for Drug Use Trends and Pharmaceutical Monitoring.Journal of medical toxicology : official journal of the American College of Medical Toxicology · 2021
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Adam J GushgariBiodesign Center for Environmental Health Engineering, The Biodesign Institute, and School of Sustainable Engineering and the Built Environment, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ, 85287-8101, USA.
Arjun K VenkatesanCenter for Clean Water Technology, Department of Civil Engineering, Stony Brook University, Stony Brook, NY, 11794, USA.
Jing ChenBiodesign Center for Environmental Health Engineering, The Biodesign Institute, and School of Sustainable Engineering and the Built Environment, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ, 85287-8101, USA.
Joshua C SteeleBiodesign Center for Environmental Health Engineering, The Biodesign Institute, and School of Sustainable Engineering and the Built Environment, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ, 85287-8101, USA.
Rolf U HaldenBiodesign Center for Environmental Health Engineering, The Biodesign Institute, and School of Sustainable Engineering and the Built Environment, Arizona State University, 1001 S. McAllister Avenue, Tempe, AZ, 85287-8101, USA. Electronic address: rolf.halden@asu.edu.
Center for Environmental Health · USStony Brook University · US

Funding

In Situ Sampling Tool for Assessing Bioavailability and Toxicity of SedimentsR01ES020889 · NIEHS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI DENSLOW, NANCY D, HALDEN, ROLF U · 2011 to 2013
$874k
NIEHS NIH HHS R01 ES020889
6 · The paper itself

Abstract

Access to near-real time opioid use data is essential to the effective management of the U.S. opioid crisis. Current narcotic data collection methods are limited by time delay and would be complimented by a rapid data acquisition technique. Use of wastewater-based epidemiology (WBE) analysis may offer access to near real-time data on opioid consumption but application in the United States has been limited. From 2015 to 2017, monthly 24-h time-weighted composite samples of municipal raw wastewater from two Midwestern U.S. cities were routinely analyzed using liquid chromatography-tandem mass spectrometry for morphine, codeine, oxycodone, heroin, fentanyl, and select opioid metabolites. Concentrations of opioids (ng/L) in raw wastewater from City 1 and 2, respectively, were: morphine (713 ± 38; 306 ± 29; detection frequency (DF): 100%), oxycodone (17.8 ± 1.1; 78 ± 6; DF: 100%), codeine (332 ± 37; 100 ± 27; DF: 93%), heroin (41 ± 16; 9 ± 11; DF: 81%), and fentanyl (1.7 ± 0.2; 1.0 ± 0.5; DF: 62%). Average opioid consumption rates estimated using WBE ranged between 9 and 2590 mg/day/1000 persons. Anticipated overdoses and overdose-deaths calculated from analyte concentrations in wastewater forecasted 200 opioid-related overdoses/year and 39 opioid related overdose-deaths/year across the two cities during the year 2016, which aligned well with observed coroner-reported opioid deaths. This long-term U.S. screening study of opioids in wastewater was the first to utilize wastewater epidemiological data to estimate the number of expected overdose and overdose-deaths, and to identify detectable levels of the powerful synthetic opioid fentanyl in community wastewater consistently over the course of one whole year.

Indexed as

Analgesics, OpioidDrug OverdoseCitiesFentanylHumansUnited StatesWastewaterAnalgesics, OpioidFentanylWastewaterFentanylHeroinOpioid death estimationOpioid overdose estimationSewage epidemiology

Identifiers

PMID31195333
PMCPMC6613989
OpenAlexW2948364280

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.