The risks of transfusion-transmissible infections (TTI)

Risks of transfusion-transmissible infection calculated on Lifeblood data

Agent and testing standard Window period Estimate of residual risk ‘per unit' (a)
HIV (antibody/p24Ag + NAT) 6 days Less than 1 in 1 million
HCV (antibody + NAT) 3 days Less than 1 in 1 million
HBV (HBsAg + NAT) 16 days Less than 1 in 1 million
HTLV 1 & 2 (antibody) 51 days Less than 1 in 1 million (b)
vCJD [No testing]   Possible, not yet reported in Australia
Malaria (antibody) 7–14 days Less than 1 in 1 million
T. pallidum (antibody) 30 days Less than 1 in 1 million

Notes: 
vCJD = variant Creutzfeldt-Jakob Disease
(a) HIV, HCV and HBV WP risk estimates are based on Lifeblood data from 1 January 2018 to 31 December 2019. HBV OBI risk based on Lifeblood data from 1 January to 31 December 2019.
(b) No HTLV incident donors recorded for the period – residual risk estimate derived from single model using first-time and repeat donor calculation and based on Lifeblood data from 1 January 2018 to 31 December 2019.

There have been no reported cases of transmission by transfusion of classical Creutzfeldt-Jakob Disease (cCJD), and retrospective studies suggest that the possibility of such transmission of cCJD is remote.

To date, there have been no reported cases of vCJD in Australia. In the UK, there have been a small number of reported cases of putative transfusion transmission since 2004.

In Australia, as a precaution, people who have spent a cumulative period of 6 months in the UK between 1 January 1980 and 31 December 1996 and/or had a transfusion in the UK between 1 January 1980 and the present time are not accepted as blood donors.

What TTI residual risk estimates do we publish and where are they published?

We publish the TTI residual risk estimates in the Blood Component Information (BCI) booklet, and on this website. The viral risk estimates are reviewed and updated periodically. Our estimates are based on published methods.

In very simple terms, what is the basis of the model calculations?

The 'window period' (WP) is defined as the interval between infection and first positive test marker in the bloodstream.
  
WP-based models assess the rate of incident infection (i.e. positive donors who have previously tested negative at Lifeblood for the same viral marker) in the repeat donor (RD) population as a measure of viral incidence (i.e. the rate of newly acquired infection).
  
The average inter-donation interval for all incident donors between the positive result and previous negative result is also incorporated. The longer this interval for an individual donor, the lower the probability that the donor was in the WP at the time of donation. In other words, the inter-donation interval is inversely proportional to the risk.
 
For infections subject to NAT testing (HIV, HBV and HCV), the Weusten model uses incidence to estimate the risk of infection in a recipient of a tested blood component based on the lower limit of detection of the applied NAT test and the probability of transmission based on a number of factors, including the volume of transfused plasma and the presumed ‘infectious dose’ of the infectious agent.
 
The WP model used for HTLV estimates only the probability of failing to detect a WP donation in a given time period based on either the rate of incident infection and inter-donation interval, or the prevalence in first-time donors.
  
The final model, applied only to HBV, estimates the risk specifically for occult HBV infection (OBI). The method is based on assessing the probability of 'non-detection' by HBV NAT and the average probability of HBV transmission from NAT non-reactive donations. NAT non detection is derived by examining HBV NAT data and assessing the frequency of prior NAT non-detectable donations from donors identified as OBI by NAT. The transmission function is based on investigation of the outcome of transfusions from blood components (termed lookback) sourced from donors with OBI.

What is the rationale for using the above calculations?

The WP-based models assume that the risk of collecting blood from an infectious donor predominantly relates to them being in the WP (i.e. incident infection) and the best estimate of incidence in the donor population is the rate of incident donors in the repeat donor population.
 
The Weusten model assumes a concentration-dependent probability that the virus is not detected in the log-linear ramp-up phase of plasma viraemia in acute infection, and a dose-dependent probability that an infection develops in the recipient of the contaminated blood product. Both these probabilities contribute to the overall residual risk.
  
While the assumption that WP donors account for the majority of risk seems to hold true for HIV, HCV and HTLV, HBV is problematic because of 'chronic' infection (i.e. HBsAg negative/anti-HBc positive with low levels of HBV DNA). WP-based models do not satisfactorily address the risk of long-term OBI. Therefore, Lifeblood developed a specific model to estimate the OBI risk which is summed with the WP risk to derive the overall HBV residual risk estimate. Importantly, HBV NAT will incrementally identify OBI donors since the vast majority can be detected using the highly sensitive ID NAT employed by Lifeblood.

How do these residual risk estimates compare to the risks associated with everyday living?

When considering the significance of specific risks, it is useful to compare them to the risks associated with everyday living. Levels of risk are compared in this Calman Chart.
 
The Calman Chart for Explaining Risk (UK risk per 1 year)

Classification Risk range Example
Negligible <1:1 000 000 Death from a lightning strike
Minimal 1:100 000–1:1 000 000 Death from a train accident
Very low 1:10 000–1:100 000 Death from an accident at work
Low 1:1000–1:10 000 Death from a road accident
Moderate 1:100–1:1000 Death from smoking 10 cigarettes per day
High >1:100 Transmission of chickenpox to susceptible household contacts

Source: Calman K. Cancer: science and society and the communication of risk. BMJ 1996;313:801.
 
The chance of dying in a road accident, for example, is about 1 in 10 000 per year which is considered a ‘low’ risk. Comparatively, all our viral risk estimates are well below this level, and would be classified as a ‘negligible risk’.

The relative risks of transfusion-transmitted infections are also very small compared to the health risks of everyday living (refer Relative risk of transfusion chart).