Evidence map›Paper›PMID 30930214›Full record

ArticleEpidemics2019

Hepatitis C transmission in young people who inject drugs: Insights using a dynamic model informed by state public health surveillance.

Rachel E Gicquelais, Betsy Foxman, Joseph Coyle, Marisa C Eisenberg

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 2 pooled it
2.5field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 26 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Rachel E GicquelaisUniversity of Michigan School of Public Health, Department of Epidemiology, 1415 Washington Heights, Ann Arbor, MI 48109, United States; Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology, 615 N. Wolfe St, Baltimore, MD 21205, United States. Electronic address: rgic@umich.edu.
Betsy FoxmanUniversity of Michigan School of Public Health, Department of Epidemiology, 1415 Washington Heights, Ann Arbor, MI 48109, United States. Electronic address: bfoxman@umich.edu.
Joseph CoyleMichigan Department of Health and Human Services, 320 S Walnut St, Lansing, MI 48933, United States. Electronic address: CoyleJ@michigan.gov.
Marisa C EisenbergUniversity of Michigan School of Public Health, Department of Epidemiology, 1415 Washington Heights, Ann Arbor, MI 48109, United States. Electronic address: marisae@umich.edu.
University of Michigan–Ann Arbor · USJohns Hopkins University · USMichigan Department of Health and Human Services · US

Funding

Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI KOOPMAN, JAMES STEPHEN · 2014 to 2018
$12.5M
Johns Hopkins HIV Epidemiology and Prevention Sciences Training ProgramT32AI102623 · NIAID · JOHNS HOPKINS UNIVERSITY · PI Shruti H Mehta · 2013 to 2026
$5.3M
Modeling the Effects of the Environment on Enteric Pathogen DynamicsU01GM110712 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI EISENBERG, JOSEPH N. S. · 2014 to 2018
$3.0M
NIAID NIH HHS T32 AI102623NIGMS NIH HHS U01 GM110712NIGMS NIH HHS U54 GM111274
6 · The paper itself

Abstract

Increasing injection of heroin and prescription opioids have led to increases in the incidence of hepatitis C virus (HCV) infections in US young adults since the early 2000s. How best to interrupt transmission and decrease HCV prevalence in young people who inject drugs (PWID) is uncertain. We developed an age-stratified ordinary differential equation HCV transmission model of PWID aged 15-64, which we fit to Michigan HCV surveillance data among young PWID aged 15-29. We used Latin hypercube sampling to fit to data under 10,000 plausible model parameterizations. We used the best-fitting 10% of simulations to predict the potential impact of primary (reducing injection initiation), secondary (increasing cessation, reducing injection partners, or reducing injection drug use relapse), and tertiary (HCV treatment) interventions (over the period 2017-2030) on acute and chronic HCV cases by the year 2030. Treating 3 per 100 current and former PWID per year could reduce chronic HCV by 27.3% (range: 18.7-30.3%) and acute HCV by 23.6% (range: 6.7-29.5%) by 2030 among PWID aged 15-29 if 90% are cured (i.e. achieved sustained virologic response [SVR] to treatment). Reducing the number of syringe sharing partners per year by 10% was predicted to reduce chronic HCV by 15.7% (range: 9.4-23.8%) and acute cases by 21.4% (range: 14.2-32.3%) among PWID aged 15-29 by 2030. In simulations of combinations of interventions, reducing injection initiation, syringe sharing, and relapse rates each by 10% while increasing cessation rates by 10% predicted a 27.7% (range: 18.0-39.7%) reduction in chronic HCV and a 38.4% (range: 28.3-53.3%) reduction in acute HCV. Our results highlight the need for HCV treatment among both current and former PWID and the scale up of both primary and secondary interventions to concurrently reduce HCV prevalence and incidence in Michigan.

Indexed as

AdolescentAdultAge DistributionComorbidityFemaleHepatitis CHumansIncidenceMaleMichiganMiddle AgedModels, TheoreticalPrevalencePublic Health SurveillanceSubstance Abuse, IntravenousYoung AdultHepatitis C virusInjection drug useSystems modeling

Identifiers

PMID30930214
PMCPMC6690387
OpenAlexW2918751332

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.