Evidence map›Paper›PMID 36669599›Full record

ArticleAnnals of epidemiology2023

Geographic and temporal trends in fentanyl-detected deaths in Connecticut, 2009-2019.

Haidong Lu, Forrest W Crawford, Gregg S Gonsalves, Lauretta E Grau

Abstract read
In one paragraph

Article in Annals of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
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

4 authors.

Haidong LuDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT; Public Health Modeling Unit, Yale School of Public Health, New Haven, CT.
Forrest W CrawfordPublic Health Modeling Unit, Yale School of Public Health, New Haven, CT; Department of Biostatistics, Yale School of Public Health, New Haven, CT; Department of Statistics & Data Science, Yale University, New Haven, CT; Department of Ecology & Evolutionary Biology, Yale University, New Haven, CT; Yale School of Management, New Haven, CT.
Gregg S GonsalvesDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT; Public Health Modeling Unit, Yale School of Public Health, New Haven, CT; Yale Law School, New Haven, CT. Electronic address: gregg.gonsalves@yale.edu.
Lauretta E GrauDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT.

Funding

Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR01DA015612 · NIDA · STANFORD UNIVERSITY · PI OWENS, DOUGLAS K · 2002 to 2017
$9.4M
Making Better Decisions: Policy Modeling for AIDS and Drug AbuseR37DA015612 · NIDA · STANFORD UNIVERSITY · PI DOUGLAS K OWENS · 2019 to 2026
$6.3M
Novel, Adaptive Approaches to Predicting and Responding to Outbreaks of Overdose, HIV and HCV Among People Who Use DrugsDP2DA049282 · NIDA · YALE UNIVERSITY · PI GONSALVES, GREGG STEVEN · 2019 to 2019
$2.5M
Network-based epidemiology for hidden and hard-to-reach populationsDP2HD091799 · NICHD · YALE UNIVERSITY · PI CRAWFORD, FORREST WRENN · 2016 to 2016
$2.5M
NICHD NIH HHS DP2 HD091799NIDA NIH HHS DP2 DA049282NIDA NIH HHS R01 DA015612NIDA NIH HHS R37 DA015612
6 · The paper itself

Abstract

purposeSince 2012 fentanyl-detected fatal overdoses have risen from 4% of all fatal overdoses in Connecticut to 82% in 2019. We aimed to investigate the geographic and temporal trends in fentanyl-detected deaths in Connecticut during 2009-2019.

methodsData on the dates and locations of accidental/undetermined opioid-detected fatalities were obtained from Connecticut Office of the Chief Medical Examiner. Using a Bayesian space-time binomial model, we estimated spatiotemporal trends in the proportion of fentanyl-detected deaths.

resultsDuring 2009-2019, a total of 6,632 opioid deaths were identified. Among these, 3234 (49%) were fentanyl-detected. The modeled spatial patterns suggested that opioid deaths in northeastern Connecticut had higher probability of being fentanyl-detected, while New Haven and its neighboring towns and the southwestern region of Connecticut, primarily Greenwich, had a lower risk. Model estimates also suggested fentanyl-detected deaths gradually overtook the preceding non-fentanyl opioid-detected deaths across Connecticut. The estimated temporal trend showed the probability of fentanyl involvement increased substantially since 2014.

conclusionsOur findings suggest that geographic variation exists in the probability of fentanyl-detected deaths, and areas at heightened risk are identified. Further studies are warranted to explore potential factors contributing to the geographic heterogeneity and continuing dispersion of fentanyl-detected deaths in Connecticut.

Indexed as

Drug OverdoseFentanylAnalgesics, OpioidBayes TheoremConnecticutHumansAnalgesics, OpioidFentanylBayesian disease mappingFentanylOpioid crisisOverdoseSpatiotemporal analysis

Identifiers

PMID36669599
PMCPMC10163838

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.