Emerging Infectious Diseases and Blood Safety: Modeling the Transfusion-Transmission Risk

- During the last 20 years there has been a growing awareness of the threat to blood safety from emerging infectious diseases (EIDs), a number of which are known to be, or are potentially, transfusion-transmissible.
- The transfusion-transmission risk of EID agents can be estimated by risk modeling which can form an important part of risk assessments and inform decisions regarding risk mitigation strategies.
- We describe and compare the methodological principles of two published risk models for estimating the transfusion transmission risk of EIDs.
- We use Zika virus as a case study to demonstrate that reliable risk modeling for EID agents can be problematic due to the uncertainty of the input parameters.

While the transfusion-transmission (TT) risk associated with the major transfusion-relevant viruses such as HIV is now very low, during the last 20 years there has been a growing awareness of the threat to blood safety from emerging infectious diseases, a number of which are known to be, or are potentially, transfusion transmissible. Two published models for estimating the transfusion-transmission risk from EIDs, referred to as the Biggerstaff-Petersen model and the European Upfront Risk Assessment Tool (EUFRAT), respectively, have been applied to several EIDs in outbreak situations. We describe and compare the methodological principles of both models, highlighting their similarities and differences. We also discuss the appropriateness of comparing results from the two models. Quantitating the TT risk of EIDs can inform decisions about risk mitigation strategies and their cost-effectiveness. Finally, we present a qualitative risk assessment for Zika virus (ZIKV), an EID agent that has caused several outbreaks since 2007. In the latest and largest ever outbreak, several probable cases of transfusion-transmission ZIKV have been reported, indicating that it is transfusion-transmissible and therefore a risk to blood safety. We discuss why quantitative modeling the TT risk of ZIKV is currently problematic.