Quantitative Microbial Risk Assessment
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While most microbes are harmless or beneficial, some are extremely dangerous – we call these biological agents of concern (BAC).
All BAC can cause serious and often fatal illness, but they
differ greatly in their physical characteristics, movement in the
environment, and process of infection. Quantitative microbial risk assessment (QMRA)
uses the best measurements about microbes’ behavior to identify where
they can become a danger and estimate the risk (including the
uncertainty in the risk) that they pose to human health.
has four stages, based on the National Accademy of Sciences framework
for Quantitative Risk Analysis, but modifed to account for the
properties of living organisms like BAC:
- Hazard Identification:
Describe a microorganism and the disease it causes, including symptoms,
severity, and death rates from the microbe. Identify sensative
populations that are particularly prone to infection.
The relationship between the dose (number of microbes) received and the
resulting health effects. Data sets from human and animal studies allow
the construction of mathematical models to predict dose-reponse.
- Exposure Assessment:
Describe the pathways that allow a microbe to reach people and cause
infection (through the air, through drinking water, by touch, etc.).
Determine the size and duration of exposure by each pathway. Estimate
the number of people exposed and the categories of people effected.
- Risk Characterization:
Integrate the information from steps 1, 2, and 3 into a single
mathematical model to calculate risk -- the probability of an outcome
like infection, illness or death. Since steps 1, 2 and 3 will not
provide a single value, but a range of values for expsure, dose, and
hazard, risk needs to be calculated for all values across those ranges.
This is called Monte Carlo Analysis, and the result
is a full range of possible risks, including average and worst-case
scenarios. These are the risks decision makers look at when choosing
policy and that scientists look at to see where we need to run more
experiments to find better information.
For a more thorough description of QMRA, see this Report to the European Commission by Gertjan Medema and Nicholas Ashbolt.