Risk modelling studies in blood safety play an important but occasionally misunderstood role. These studies are intended to quantify and contrast risks and benefits. This information is critical for policy development and intervention decision-making. The limitations of risk modelling should be considered alongside the results obtained.
The goal of this manuscript and presentation is to review current risk modelling techniques used in blood safety and to discuss the pros and cons of using this information in the decision-making process. The types of questions that can be answered include the extent of a risk or threat; implications of action or inaction; identification of effective strategies for risk management; or whether to adopt specific interventions. These analyses can be focused on a risk alone but are often combined with economic information to gain an understanding of feasible risk interventions given budgetary or other monetary considerations. Thus, analyses that include risk modelling provide insights along multiple lines. As important, the analyses also provide information on what is not known or uncertain about a potential hazard and how much that uncertainty may influence the decision-making process.
Specific examples of the range of risk analyses in which the author has participated will be reviewed and will include ongoing process improvement in testing laboratories such as error identification/eradication, estimation of the risk of malaria exposure based on the specific locations of travel, evaluation of blood supply and demand during an influenza pandemic, cost-utility analyses of screening interventions for infectious diseases in countries with different human development indices, and insurance against emerging pathogen risk. Each of these analyses has a different purpose and seeks to answer different questions, but all rely on similar methods.
The tool kit for risk analysis is broad and varied but does have limitations. The chief limitation of risk modelling is that risk analyses are not scientific experiments or otherwise controlled studies. Consequently, the analyses are more apt to be influenced by assumptions. These assumptions may be necessary to structure a problem in a way that will allow the question of interest to be answered or may result from incomplete or missing information. Another potential limitation is that commissioners of such studies, those who undertake them, and the intended audience, such as regulatory agencies, may have distinct and differing interpretations of the results.
Risk modelling is a set of techniques that can be used to inform and support decision-making at all levels in transfusion medicine. Advances in risk modelling techniques allow for continued expansion in the scope of possible questions that can be analysed. Expanded use also improves the acceptance of the utility of these studies in blood safety and transfusion medicine.