Or more simply stated, it describes what we know and how certain we are of what we know. The risk is expressed as a mathematical statement of the chance of illness or death after exposure to a specific pathogen and it represents the cumulative probabilities of certain events happening and the uncertainty associated with those events. Quantitative risk assessment modeling is a relatively new approach to the field of microbial risk. The data are represented as large sets of numbers called distributions rather than as point estimates, which offer several potential advantages over traditional approaches. One advantage is that distributions may represent the spread of real world data more accurately than point estimates like a mean.
Distributions can also reflect the presence of uncertainty in the data.
Another potential advantage is that modeling allows risk assessors to test which factors are most important in determining the magnitude of a risk or what effect control measures will have on a risk.