Evidence map›Paper›PMID 31392812›Full record

ArticleJournal of viral hepatitis2019

Modelling the potential prevention benefits of a treat-all hepatitis C treatment strategy at global, regional and country levels: A modelling study.

Adam Trickey, Hannah Fraser, Aaron G Lim, Josephine G Walker, Amy Peacock, Samantha Colledge, Janni Leung, Jason Grebely, Sarah Larney, Natasha K Martin and 4 more

Abstract read
In one paragraph

Article in Journal of viral hepatitis, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Cost-Effectiveness of Hepatitis C Virus Case Finding and Treatment in Eastern Europe and Central Asia.Liver international : official journal of the International Association for the Study of the Liver · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. 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

14 authors.

Adam TrickeyPopulation Health Sciences, University of Bristol, Bristol, UK.ORCID 0000-0003-3462-2898
Hannah FraserPopulation Health Sciences, University of Bristol, Bristol, UK.
Aaron G LimPopulation Health Sciences, University of Bristol, Bristol, UK.
Josephine G WalkerPopulation Health Sciences, University of Bristol, Bristol, UK.
Amy PeacockNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia.
Samantha ColledgeNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia.
Janni LeungNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia.
Jason GrebelyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States.ORCID 0000-0002-1833-2017
Sarah LarneyNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia.
Natasha K MartinPopulation Health Sciences, University of Bristol, Bristol, UK.
Louisa DegenhardtNational Drug and Alcohol Research Centre, UNSW Sydney, Sydney, NSW, Australia.
Matthew HickmanPopulation Health Sciences, University of Bristol, Bristol, UK.
Margaret T MayPopulation Health Sciences, University of Bristol, Bristol, UK.
Peter VickermanPopulation Health Sciences, University of Bristol, Bristol, UK.

Funding

VirologyP30AI036214 · NIAID · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUSAN JANET LITTLE · 1994 to 2026
$78.4M
Modeling Structural HIV Determinants in Substance Users and related populationsR01DA037773 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MARTIN, NATASHA, STRATHDEE, STEFFANIE A. · 2015 to 2017
$1.4M
Department of Health RP-DG-0610-10055Department of Health RP-PG-0616-20008NIAID NIH HHS P30 AI036214NIDA NIH HHS R01 DA037773
6 · The paper itself

Abstract

The World Health Organization (WHO) recently produced guidelines advising a treat-all policy for HCV to encourage widespread treatment scale-up for achieving HCV elimination. We modelled the prevention impact achieved (HCV infections averted [IA]) from initiating this policy compared with treating different subgroups at country, regional and global levels. We assessed what country-level factors affect impact. A dynamic, deterministic HCV transmission model was calibrated to data from global systematic reviews and UN data sets to simulate country-level HCV epidemics with ongoing levels of treatment. For each country, the model projected the prevention impact (in HCV IA per treatment undertaken) of initiating four treatment strategies; either selected randomly (treat-all) or targeted among people who inject drugs (PWID), people aged ≥35, or those with cirrhosis. The IA was assessed over 20 years. Linear regression was used to identify associations between IA per treatment and demographic factors. Eighty-eight countries (85% of the global population) were modelled. Globally, the model estimated 0.35 (95% credibility interval [95%CrI]: 0.16-0.61) IA over 20 years for every randomly allocated treatment, 0.30 (95%CrI: 0.12-0.53) from treating those aged ≥35 and 0.28 (95%CrI: 0.12-0.49) for those with cirrhosis. Globally, treating PWID achieved 1.27 (95%CrI: 0.68-2.04) IA per treatment. The IA per randomly allocated treatment was positively associated with a country's population growth rate and negatively associated with higher HCV prevalence among PWID. In conclusion, appreciable prevention benefits could be achieved from WHO's treat-all strategy, although greater benefits per treatment can be achieved through targeting PWID. Higher impact will be achieved in countries with high population growth.

Indexed as

Models, TheoreticalAdolescentAdultAntiviral AgentsChildChild, PreschoolDisease ManagementFemaleGlobal HealthHepatitis CHumansInfantInfant, NewbornMaleMiddle AgedOutcome Assessment, Health CareAntiviral AgentsavertedDAAHCVinfectionstreat

Identifiers

PMID31392812
PMCPMC10401696

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.