Limitations of Quantitative Risk Assessment Using Aggregate Exposure and Risk Models

Louis Anthony Cox ()
Additional contact information
Louis Anthony Cox: Cox Associates

Chapter Chapter 5 in Risk Analysis of Complex and Uncertain Systems, 2009, pp 125-161 from Springer

Abstract: Chapter 4 showed that risk matrices can assign small risks to high-risk categories and larger risks to lower-risk categories, defeating the intent of the classification system. Do other methods necessarily do better? This chapter shows that careless use of quantitative risk assessment concepts can also lead to worse-than-useless risk comparisons and recommendations. This happens if causal drivers of risk (such as age-specific failure rates, detailed exposures, or individual dose-response relations) are ignored in favor of potentially meaningless aggregate quantities (such as “average annual frequency,” “aggregate exposure,” or “population exposure-response ratio,” respectively). A lesson from Chapter 4 was that risk matrices cannot correctly compare some risks. The main lesson from this chapter is milder. Care must be taken in using quantitative risk concepts to make sure that they correctly represent causal relations among actions, exposures, and probable consequences. Otherwise, they may give rise to meaningless or misleading numbers and predictions.

Keywords: Microbial Load; Lifetime Distribution; Certainty Equivalent; Quantitative Risk Assessment; Priority Score (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-0-387-89014-2_5

Ordering information: This item can be ordered from
http://www.springer.com/9780387890142

DOI: 10.1007/978-0-387-89014-2_5

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().