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WOLFRAM|DEMONSTRATIONS PROJECT

Assessing the Risk of Food Poisoning

​
data
generate
clear
use seed
runs
500
seed
0
minima
maxima
pathogen
α
0.3
α
0.4
n
50
10
n
50
50
history
n
0
20
n
0
50
k
0.002
k
0.04
t
15.
t
25.
f
i
-0.2
f
i
-0.1
n axis maximum
n
max
500.
p
BP
(n) = 1 - (1 + n (
1/α
2
- 1)/
n
50
-α
)
p
p
= 1 - (1 +
n
0
k t
e
(
1/α
2
- 1)/
n
50
-α
)
p = If[
f
i
<0,
p
p
(1 +
f
i
/2),
p
p
+ (1 -
p
p
)
f
i
/2]
p
max. freqency
= 0.53
mean = 0.541
std. dev. = 0.067
The probability of becoming sick or dying after ingesting a food-borne pathogen’s cells primarily depends on its virulence, the number of cells ingested, and the state of the person’s health. A dose-response-based model that incorporates the pathogen’s infective or lethal dose, its cells’ exponential growth rate, the growth duration, and an additive factor that represents an individual’s susceptibility or immunity is used to estimate this probability. Since the magnitudes of these factors are rarely if ever known exactly, they are entered as ranges. The acute poisoning probability is estimated by the expanded Fermi solution method, where random values formed within these ranges are used to calculate interim estimates in hundreds of Monte Carlo runs. The mode of the histogram of these interim estimates is considered the best estimate of the probability of poisoning.
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