Sensitivity Analysis: Changing one Parameter at a Time
123
[ ]
[ ]
model baseline
the using
evaluated Mean
model e
alternativ an
using evaluated
Mean =
dMean
,
[ ]
[ ]
model baseline
the using
evaluated Median
model e
alternativ an
using evaluated
Median =
dMedian
In order to better understand the meaning of these measures of change in the context of such highly skewed risk output distributions, we note that a large value of dMeanParameter
indicates that the Parameter has a large impact, particularly, on the highest percentiles of the risk distribution, and so, on the mean of the risk output distribution. dMeanParameter values
greater than 1 point to a Parameter whose change effects an increase in the mean value, relative to the mean value calculated at a baseline value of the Parameter. dMeanParameter values less
than 1 point to a Parameter whose change effects a decrease in the mean value, relative to the mean value calculated at a baseline value of the Parameter. A large dMedianParameter value
indicates that the Parameter has a large impact on the whole risk distribution, particularly effecting a shift of location for the risk distribution.
In the following sections, we report results for these measures of change for the Risk per serving or the Risk per contaminated serving risk output, for the Canadian Elderly population relative to
the pasteurized-cheese baseline model. Other outputs’ or other subpopulations’ results are also reported if the characteristics of the measures of change are different.
9.2.1. Environmental Contamination Prevalence and Levels
The baseline models use the environmental contamination distribution that section 6.4 derived from Gombas et al. 2003 data as the only source of L. monocytogenes that persists to
consumption.
We evaluate the impact of varying the level of that contamination per cheese from 1 cfu per contaminated cheese to 100,000 cfu per contaminated cheese on the median and mean risk per
contaminated serving. In the baseline model, environmental contamination varies from 1 to 31 L. monocytogenes per contaminated cheese distribution, see Table 20, p. 69.
124 The median risk increases linearly with the level of environmental contamination: a 10-fold
increase in environmental contamination levels increases the median risk per contaminated serving 10-fold. One L. monocytogenes cfu is ½ the median of the baseline model Table 46.
The impact on the mean is smaller. For example, the mean risk per contaminated serving increases 1.4-fold when the environmental contamination increases 10-fold from 10,000
cfucheese to 100,000 cfucheese. Also, the dMean rate of change with increasing level of environmental contamination slows as the level of contamination increases 1-10, 10-100, … in
Table 46. This result suggests that other factors than high initial environmental contamination are needed to affect the mean risk per contaminated serving.
Table 46: Sensitivity of the risk per contaminated serving, Canadian Elderly population, to the level of environmental contamination, relative to the pasteurized-milk cheese PMC baseline.
Statistical summary
PMC Baseline
1 cfucheese
10 cfucheese
100 cfucheese
1,000 cfucheese
10,000 cfucheese
100,000 cfucheese
dMedian 1.00
0.47 1.0
7.3 74
740 7,141
dMean 1.00
0.51 0.9
2.6 4.4
6.5 8.8
9.2.2. Growth Characteristics
Section 6.1 captures L. monocytogenes growth in contaminated cheeses with the three-phase linear model. This section examines the sensitivity of risk outputs to changes to the exponential
growth rate and maximum population density that parameterize the primary growth model, to the storage temperature that parameterizes the secondary growth model and to the storage time and
temperature that parameterizes the amount of growth.
Exponential Growth Rate
We tested the influence of the Exponential Growth Rate EGR on the risk per serving by comparing pasteurized-milk cheese baseline model risk per contaminated serving to the risk per
contaminated serving under changes to the EGR as •
no growth, EGR
20
= 0 log
10
cfu per gram per day implies no growth at any temperature; •
lower than pasteurized-milk cheese baseline growth, dividing the baseline EGR
20
by a factor of 2, when growth occurs;
125 •
higher than pasteurized-milk cheese baseline growth, multiplying the baseline EGR
20
by a factor of 2, when growth occurs.
When growth occurs as in the pasteurized-milk cheese baseline model, the mean risk per serving is 53,000 times larger than the mean risk per contaminated serving when no growth occurs
Table 47, dMean row. This result suggests that the risk is principally linked to the bacterial growth that occurs in stages along the process pathway.
Halving the EGR
20
dramatically reduces the mean risk per contaminated serving, by a factor of approximately 8. On the other hand, doubling the EGR
20
multiplies the mean risk by a factor of approximately 4. This reflects the model’s representation of the non-linearity of this system, the
system’s asymptote at the maximum population density and interactions among EGR
20
and other factors.
Halving the EGR
20
has a small effect also on the median risk per contaminated serving. Doubling the EGR
20
scales the median risk per contaminated serving to 9.5 times the pasteurized-milk cheese baseline model’s median risk.
In the gamma concept predictive microbiology framework Zwietering et al. 1996, environmental factors act independently 0
≤ γ
i
x
i
≤ 1 or with a positive synergy 0 ≤ γ
int
x
1, …,
x
n
≤ 1 on the EGR according to . So, to halve the EGR,
modify any one or more factors such that
n i
i i
i
x x
x EGR
EGR ,...,
int 20
γ γ
=
∏
= ½; modifying one or more factors such that
∏
i i
i n
i
x x
x
γ γ
,...,
int
= 2, doubles the EGR. The mean risk per contaminated serving changes with changing EGR
20
, whatever method is used to effect the EGR changes.
∏
i i
i n
i
x x
x
γ γ
,...,
int
Maximum Population Density
A 1 log
10
higher and a 1 log
10
lower maximum population density for L. monocytogenes in soft- ripened cheese has a large impact on the mean risk per contaminated serving Table 47, dMean
and no impact on the median risk per contaminated serving Table 47, dMedian = 1. Changing
126 the maximum population density affects only those situations where growth to high levels can
occur. Those situations have a large impact on the mean risk but no impact on the median risk.
Table 47: Sensitivity of the risk per contaminated serving to growth characteristics relative to the pasteurized-milk cheese baseline.
Summary statistics
PMC Baseline
EGR
20
EGR
20
½ ×baseline
EGR
20
2 × baseline
Maximum population density
- 1 log
10
Maximum population
density +1 log
10
dMedian 1.00
0.35 0.47
9.5 1.0
1.0 dMean
1.00 1.9×10
-5
0.12 4.2
0.15 6.8
Temperature and Time of Storage
We tested the influence on the risk per contaminated serving of •
a general decrease of 1°C during transport and marketing, at retail and during storage in the home refrigerator, compared to the PMC baseline
• a general increase of 1°C during transport and marketing, at retail and during storage in
the home refrigerator, compared to the PMC baseline; •
a maximum duration of home storage of 28 days vs. 56 days in the pasteurized-milk cheese baseline.
The impact of changes to the home refrigerator temperature is the most important one: an increase of 1°C increases the mean risk per contaminated serving by a factor of 1.7 Table 48,
top. A 1 °C storage temperature increase or decrease during transport and marketing storage or
during retail storage increases or decreases the mean risk per contaminated serving by only a small amount.
Shortening the maximum duration of the home storage from 56 days to 28 days reduces the mean risk by a factor of approximately 2 for the Elderly population and the Pregnant women
population and by a factor of 1.4 for the Immunocompromised population and the General population Table 48, bottom. Storage times longer than 28 days happen more frequently among
servings eaten by individuals in the Elderly population and in the Pregnant women population 10 than among servings eaten by individuals in the Immunocompromised population and
the General population 5.
127
Table 48: Sensitivity of the risk per contaminated serving to the storage time and temperature relative to the pasteurized-milk cheese PMC baseline.
Temperature PMC
Baseline -1°C
compared to baseline
Transport Marketing
-1°C compared
to baseline Retail
-1°C compared
to baseline Home
+1°C compared
to baseline Transport
Marketing +1°C
compared to baseline
Retail +1°C
compared to baseline
Home
dMedian 1.0
0.88 0.88
0.82 1.2
1.2 1.3
dMean 0.94
0.90 0.88
0.53 1.0
1.0 1.7
Table : Sensitivity of the risk per contaminated serving to the storage duration relative to the pasteurized- milk cheese PMC baseline
Max. home storage
duration PMC
Baseline Max.
home storage: 28 days vs. baseline,
56 days Elderly
Max. home storage:
28 days vs. baseline, 56 days
Pregnant women Max.
home storage: 28 days vs. baseline,
56 days IC
Max. home storage:
28 days vs. baseline, 56 days
General
dMedian 1.00
0.88 0.81
0.94 0.94
dMean 1.00
0.52 0.45
0.70 0.70