Expert Knowledge Elicitation: Development of a quick and robust method for assessing data gaps in risk assessment

Risk assessments provide crucial evidence to assist decision-makers in the prevention and control of animal diseases.  However, one of the main limitations is lack of empirical evidence and data, particularly when considering new and exotic diseases or the impact of illegal activities.  A common way to deal with data gaps is to use expert knowledge elicitation (EKE). 

The EFSA guidelines outline a formal ‘gold standard’ EKE approach (EFSA, 2014).  This method provides rigid and transparent parameter estimates, which can be used in quantitative and semi-quantitative risk assessments. However, the method is time-consuming and requires extensive training to conduct. As such, in many situations, for example during a disease outbreak or a research project with limited budget, there is not always sufficient time or resources for the assessors and/or the experts themselves, to implement this approach fully.

In such situations there is a need for a more practical ‘light’ EKE method, which can provide a transparent behavioural aggregation of expert knowledge in the event of sparse data, time constraints and with limited training of those conducting the EKE.  In recent times, a number of ad-hoc modified EKE approaches have been used, also by members of our consortium, but a more formally developed approach would be beneficial.

In this project we propose to review the current EKE methodologies and seek to develop a ‘light’ EKE approach that can be implemented in time or resource limited situations while still providing robust estimates.