Evidence map›Paper›PMID 42268826›Full record

ArticlePloS one2026

Four methods for estimating hepatitis C incidence using extant testing data.

William J McFarlane, Jennifer A Flemming, Susan B Brogly, Yingwei Peng

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In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

William J McFarlaneDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.ORCID https://orcid.org/0000-0001-7486-2314
Jennifer A FlemmingDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.ORCID https://orcid.org/0000-0002-9911-0925
Susan B BroglyICES Queen's, Kingston, Ontario, Canada.
Yingwei PengDepartment of Public Health Sciences, Queen's University, Kingston, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccurate estimation of hepatitis C (HCV) incidence is crucial for measuring progress towards HCV elimination targets set by the World Health Organization (WHO). Extant HCV antibody (Ab) and RNA test results are widely used to estimate HCV incidence, but the impact of cohort specification and case definition on validity and generalizability is poorly understood.

methodsUsing databases linked at ICES - a repository of administrative health data for Ontario residents - we constructed a cohort of 15.8 million Ontarians aged 18-80 between 1999 and 2018 to estimate annual HCV incidence using four methods. The population-based method calculated HCV incidence as the number of new HCV diagnoses each year divided by annual population size estimates, while Poisson regression was used in the other three incidence estimation methods: the test-negative method defined eligibility at first negative test; the RNA-based method prioritized specificity by requiring RNA+ tests; and the antibody-inclusive method prioritized sensitivity by including all Ab+ tests.

resultsDistinct patterns of HCV incidence were found across the estimation methods: the RNA-based estimates were lowest and fluctuated around 30 cases per 100,000 person-years, while population-based and antibody-inclusive estimates were 1.5-fold higher, and test-negative estimates were 7.9-fold higher. Population-based estimates were sensitive to changes in the HCV case definition used in Ontario from 1999-2018. The test-negative cohort had a high prevalence of human immunodeficiency virus (HIV) and substance use disorder, limiting generalizability of HCV incidence estimates. RNA-based estimates likely underestimated HCV incidence because 22% of Ab+ tests were unconfirmed by RNA testing, while antibody-inclusive estimates likely overestimated HCV incidence by assuming all unconfirmed Ab+ tests were true cases.

conclusionThese new findings illustrate the influence of cohort definition and HCV case definition when estimating HCV incidence using extant testing data, which will support accurate measurement of progress towards WHO HCV elimination goals.

Indexed as

Hepatitis CAdolescentAdultAgedAged, 80 and overFemaleHepacivirusHepatitis C AntibodiesHumansIncidenceMaleMiddle AgedOntarioRNA, ViralYoung AdultHepatitis C AntibodiesRNA, Viral

Identifiers

PMID42268826
PMCPMC13252766

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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.