Antibody Avidity-Based Approach to Estimate Population-Level Hepatitis C Incidence

Computer illustration of antibodies (pink) attacking a virus particle (blue).
A novel, resource-efficient method to accurately estimate primary hepatitis C virus (HCV) incidence in a population using data from a single point has been developed.

A novel, resource-efficient method to accurately estimate primary hepatitis C virus (HCV) incidence in a population using data from a single point has been developed, according to a study published in the Journal of Hepatology.1This method may be able to help monitor progress toward HCV elimination and appropriately guide control efforts.

In 2015, approximately 71 million people had chronic infection with HCV worldwide.2 One of the goals for eliminating HCV by the World Health Organization is an 90% reduction in incidence by 2030.3 However, accurate population-level HCV incidence estimates are needed to monitor this goal.

Researchers developed and evaluated a modified-Genedia HCV ELISA Avidity Assay (Green Cross Medical Science Corp., Chungbik, Korea), which costs approximately 4 USD per sample. This assay was investigated in combination with virologic confirmation to estimate cross-sectional HCV incidence. Researchers used data from 875 patients with a history of injection drug use who were enrolled in 5 cohort studies in the United States and India; 1840 HCV antibody and RNA positive samples were obtained.1

Researchers found that this approach can identify recently infected individuals in a high-risk population, with a low frequency of false recency and without being affected by genotype. HCV avidity increased with time post-HCV seroconversion among samples from patients with a known duration of infection; by 2 years post-HCV seroconversion, the majority of samples had an avidity index >90%.

In simulated populations of high HCV incidence (10%-40%), this approach required a sample size of < 1000 individuals to accurately estimate incidence. Age, gender, and HCV genotype were not associated with a lower avidity response (AI<40%) among samples collected ≥2 years post-HCV seroconversion. However, in this cohort, a lower avidity response (AI<40%) was more commonly observed in individuals with HIV who had a CD4+ T-cell count <200 cells/μL.

Although specific criteria for HCV have yet to be established, using the modified-Genedia approach, resulted showed that an antibody avidity index cutoff of <40% to achieve the most optimal mean duration of recent infection and false recent ratio combination using the HIV criteria as a reference. At this cutoff, misclassification is strongly associated with poor immune status among those with HIV.

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The study authors concluded that, “This tool can be used to characterize the epidemiology of recent infections and the design of targeted interventions to reduce further transmission and therefore has the potential to serve as a valuable resource to monitor the impact of programs and policies aimed toward reducing HCV incidence.”


  1. Boon D, Bruce V, Patel EU, et al. Antibody avidity-based approach to estimate population-level incidence of hepatitis C [published online March 30, 2020]. J Hepatol. doi:10.1016/j.jhep.2020.03.028
  2. Polaris Observatory HCVC. Global prevalence and genotype distribution of hepatitis C virus infection in 2015: a modelling study. Lancet Gastroenterol Hepatol. 2017;2:161-176.
  3. World Health Organization. Combating Hepatitis B and C to Reach Elimination by 2030. Geneva: World Health Organization. Posted May 2016. Accessed April 13, 2020.;jsessionid=C76AD3A76E5C52B1B720150E8A77597C?sequence=1