Four methods for estimating hepatitis C incidence using extant testing data

Accurate 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.

Using 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.

Distinct 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.

These 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.