Is dual testing for hepatitis C necessary? Modelling the risk of removing hepatitis C antibody testing for Australian blood donations

Background and Objectives: Parallel testing of blood donations for hepatitis C virus (HCV) antibody and HCV RNA by nucleic acid testing (NAT) has been standard practice in Australia since 2000. Meanwhile, NAT technologies have improved, and HCV has become a curable disease. This has resulted in a significant reduction in the risk and clinical consequences of HCV transmission through transfusion. This study aimed to estimate the residual risk (RR) under various testing options to determine the optimal testing strategy. Materials and Methods: A developed deterministic model calculated the RR of HCV transmission for four testing strategies. A low, mid and high estimate of the RR was calculated for each. The testing strategies modelled were as follows: universal dual testing, targeted dual testing for higher risk groups (first-time donors or transfusible component donations) and universal NAT only. Results: The mid estimate of the RR was 1 in 151 million for universal dual testing, 1 in 111 million for targeted dual testing of first-time donors, 1 in 151 million for targeted dual testing for transfusible component donations and 1 in 66 million for universal NAT only. For all testing strategies, all estimates were considerably less than 1 in 1 million. Conclusion: Antibody testing in addition to NAT does not materially change the risk profile. Even conservative estimates for the cessation of anti-HCV predict an HCV transmission risk substantially below 1 in 1 million. Therefore, given that it is not contributing to blood safety in Australia but consuming resources, anti-HCV testing can safely be discontinued.

Automated summary

Parallel testing of blood donations for HCV antibody and RNA has been standard practice in Australia since 2000. Improved NAT technologies and the curability of HCV have reduced the risk and consequences of HCV transmission through transfusion. This study aimed to determine the optimal testing strategy by estimating the residual risk under various testing options.