Research Synthesis Methods in an Age of Globalized Risks: Lessons from the Global Burden of Foodborne Disease Expert Elicitation

Risk Anal. 2016 Feb;36(2):191-202. doi: 10.1111/risa.12385. Epub 2016 Feb 9.


We live in an age that increasingly calls for national or regional management of global risks. This article discusses the contributions that expert elicitation can bring to efforts to manage global risks and identifies challenges faced in conducting expert elicitation at this scale. In doing so it draws on lessons learned from conducting an expert elicitation as part of the World Health Organizations (WHO) initiative to estimate the global burden of foodborne disease; a study commissioned by the Foodborne Disease Epidemiology Reference Group (FERG). Expert elicitation is designed to fill gaps in data and research using structured, transparent methods. Such gaps are a significant challenge for global risk modeling. Experience with the WHO FERG expert elicitation shows that it is feasible to conduct an expert elicitation at a global scale, but that challenges do arise, including: defining an informative, yet feasible geographical structure for the elicitation; defining what constitutes expertise in a global setting; structuring international, multidisciplinary expert panels; and managing demands on experts' time in the elicitation. This article was written as part of a workshop, "Methods for Research Synthesis: A Cross-Disciplinary Approach" held at the Harvard Center for Risk Analysis on October 13, 2013.

Keywords: Disease burden; expert elicitation; expert judgment; exposure estimates; foodborne illness; research synthesis; source attribution; systematic review; uncertainty quantification.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Calibration
  • Data Collection
  • Food Microbiology*
  • Food Safety*
  • Foodborne Diseases / epidemiology*
  • Geography
  • Humans
  • Internationality
  • Program Development
  • Public Health / methods
  • Risk Assessment
  • World Health Organization