Evidence map›Paper›PMID 30962092›Full record

ArticleVaccine2019

Modeling indicates efficient vaccine-based interventions for the elimination of hepatitis C virus among persons who inject drugs in metropolitan Chicago.

Desarae Echevarria, Alexander Gutfraind, Basmattee Boodram, Jennifer Layden, Jonathan Ozik, Kimberly Page, Scott J Cotler, Marian Major, Harel Dahari

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 20% 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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Article
  6. Vaccines for immunoprevention of cancer.The Journal of clinical investigation · 2021
    Review
  7. Article
  8. 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

9 authors at 6 institutions in 1 country.

Desarae EchevarriaThe Program for Experimental & Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University, Medical Center, Maywood, IL, USA.
Alexander GutfraindThe Program for Experimental & Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University, Medical Center, Maywood, IL, USA; Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL, USA.
Basmattee BoodramCommunity Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, IL, USA.
Jennifer LaydenHealth Protection Office, Illinois Department of Public Health, Chicago, IL, USA.
Jonathan OzikConsortium for Advanced Science and Engineering, University of Chicago, Chicago, IL, USA; Decision and Infrastructure Sciences, Argonne National Laboratory, Argonne, IL, USA.
Kimberly PageDivision of Epidemiology, Biostatistics and Preventive Medicine, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
Scott J CotlerThe Program for Experimental & Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University, Medical Center, Maywood, IL, USA.
Marian MajorDivision of Viral Products, Center for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Harel DahariThe Program for Experimental & Theoretical Modeling, Division of Hepatology, Department of Medicine, Loyola University, Medical Center, Maywood, IL, USA. Electronic address: hdahari@luc.edu.
Loyola University Medical Center · USArgonne National Laboratory · USCenter for Biologics Evaluation and Research · USIllinois Department of Public Health · USUniversity of Illinois Chicago · USUniversity of New Mexico · US

Funding

Collaborative Integration of HCV Molecular Virology and Mathematical ModelingR01AI078881 · NIAID · UNIVERSITY OF ILLINOIS AT CHICAGO · PI PERELSON, ALAN S, UPRICHARD, SUSAN L. · 2011 to 2025
$7.5M
Disrupting Vector-borne Disease Transmission in Complex Urban EnvironmentsR01AI101229 · NIAID · UNIVERSITY OF PENNSYLVANIA · PI LEVY, MICHAEL Z · 2013 to 2017
$3.1M
Contextual risk factors for hepatitis C among young persons who inject drugsR01DA043484 · NIDA · UNIVERSITY OF ILLINOIS AT CHICAGO · PI BOODRAM, BASMATTEE · 2017 to 2021
$2.9M
Computational discovery of effective hepatitis C intervention strategiesR01GM121600 · NIGMS · LOYOLA UNIVERSITY CHICAGO · PI BOODRAM, BASMATTEE, DAHARI, HAREL · 2017 to 2021
$2.0M
NIAID NIH HHS R01 AI078881NIAID NIH HHS R01 AI101229NIDA NIH HHS R01 DA043484NIGMS NIH HHS R01 GM121600
6 · The paper itself

Abstract

BACKGROUND AND

aimsPersons who inject drugs (PWID) are at highest risk for acquiring and transmitting hepatitis C (HCV) infection. The recent availability of oral direct-acting antiviral (DAA) therapy with reported cure rates >90% can prevent HCV transmission, making HCV elimination an attainable goal among PWID. The World Health Organization (WHO) recently proposed a 90% reduction in HCV incidence as a key objective. However, given barriers to the use of DAAs in PWID, including cost, restricted access to DAAs, and risk of reinfection, combination strategies including the availability of effective vaccines are needed to eradicate HCV as a public health threat. This study aims to model the cost and efficacy of a dual modality approach using HCV vaccines combined with DAAs to reduce HCV incidence by 90% and prevalence by 50% in PWID populations.

methodsWe developed a mathematical model that represents the HCV epidemic among PWID and calibrated it to empirical data from metropolitan Chicago, Illinois. Four medical interventions were considered: vaccination of HCV naive PWID, DAA treatment, DAA treatment followed by vaccination, and, a combination of vaccination and DAA treatment.

resultsThe combination of vaccination and DAAs is the lowest cost-expensive intervention for achieving the WHO target of 90% incidence reduction. The use of DAAs without a vaccine is much less cost-effective with the additional risk of reinfection after treatment. Vaccination of naïve PWID alone, even when scaled-up to all reachable PWID, cannot achieve 90% reduction of incidence in high-prevalence populations due to infections occurring before vaccination. Similarly, the lowest cost-expensive way to halve prevalence in 15 years is through the combination of vaccination and DAAs.

conclusionsThe modeling results underscore the importance of developing an effective HCV vaccine and augmenting DAAs with vaccines in HCV intervention strategies in order to achieve efficient reductions in incidence and prevalence.

Indexed as

Drug UsersModels, TheoreticalAlgorithmsChicagoCost-Benefit AnalysisHealth Care CostsHepacivirusHepatitis CHumansIncidencePrevalenceVaccinationVaccine PotencyViral Hepatitis VaccinesViral Hepatitis VaccinesDirect-acting antiviralsHepatitis C virusMathematical modelingPersons who inject drugsVaccine

Identifiers

PMID30962092
PMCPMC6552658
OpenAlexW2933793176

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.