Evidence map›Paper›PMID 35024654›Full record

ArticleThe Lancet regional health. Western Pacific2022

Assessment of the cost-effectiveness of Australia's risk-sharing agreement for direct-acting antiviral treatments for hepatitis C: a modelling study.

Dr Nick Scott, Ms Anna Palmer, Mr Tom Tidhar, Prof Mark Stoove, Dr Rachel S Sacks-Davis, A/Prof Joseph S Doyle, Dr Alisa J Pedrana, Prof Alexander Thompson, Prof David P Wilson, Prof Margaret Hellard

Abstract read
In one paragraph

Article in The Lancet regional health. Western Pacific, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. The Hepatitis C Cascade of Care for Opioid Agonist Therapy Recipients in Australia.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
  4. Clinical and demographic characteristics of participants in a hepatitis C treatment trial in rural Kentucky: How policies around treatment access may impact elimination efforts in the United States.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. 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

10 authors.

Dr Nick ScottDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Ms Anna PalmerDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Mr Tom TidharDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Prof Mark StooveDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Dr Rachel S Sacks-DavisDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
A/Prof Joseph S DoyleDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Dr Alisa J PedranaDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Prof Alexander ThompsonDepartment of Medicine, The University of Melbourne, Parkville, VIC 3050, Australia.
Prof David P WilsonDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.
Prof Margaret HellardDisease Elimination Program, Burnet Institute, Melbourne, VIC 3004, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatitis C elimination may be possible with broad uptake of direct-acting antiviral treatments (DAAs). In 2016 the Australian government committed A$1.2 billion for five years of unlimited DAAs (March 2016 to February 2021) in a risk-sharing agreement with pharmaceutical companies. We assess the impact, cost-effectiveness and net economic benefits likely to be realised from this investment.

methodsMathematical modelling to project outcomes for 2016-2030 included: (S1) a counter-factual scenario (testing/treatment maintained at pre-2016 levels); (S2) the current status-quo (testing/treatment as actually occurred 2016-2019, with trends maintained to 2030); and (S3) elimination scenario (S2 plus testing/treatment rates increased between 2021-2030 to achieve the WHO elimination targets).

findingsS1 resulted in 68,800 new hepatitis C infections and 18,540 hepatitis C-related deaths over 2016-2030. The total health system cost (HCV testing, treatment, disease management) was A$3.01 billion and the cost of lost productivity due to absenteeism, presenteeism and premature deaths was A$26.14 billion. S2 averted 15,700 (23%) new infections and 8,500 (46%) deaths by 2030, with a total health system cost of A$3.48 billion, A$472 million more than S1 (A$1.65 billion more in testing/treatment but A$1.20 billion less in disease costs; A$5,752 per QALY gained from a health systems perspective). Productivity loss over 2016-2030 was A$19.96 billion, A$6.17 less than S1, making S2 cost-saving from a societal perspective by 2022 with a net economic benefit of A$5.70 billion by 2030. S3 averted an additional 10,000 infections and 930 deaths compared with S2 and increased the longer-term economic benefit.

interpretationFive years of unrestricted access to DAAs in Australia has led to significant health benefits and is likely to become cost-saving from a societal perspective by 2022.

fundingBurnet Institute.

Indexed as

cost-effectivenessDAA, direct-acting antiviraleliminationGDP, gross domestic producthepatitis Cmathematical modelproductivityPWID, people who inject drugsQALY, quality-adjusted life yearWHO, World Health Organization

Identifiers

PMID35024654
PMCPMC8669355

What OpenQuestion holds

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LicenceCC BY
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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.