Meeting FSO and PO Through Control Measures
3.5 Deriving Performance Criteria
3.5.1 Examples of General Use of the ICMSF Conceptual Equation
In the following three examples, illustrated in (Figs. 3.4, 3.5, and 3.6), the same hypothetical dose-response curve for a certain infectious pathogen is considered (shown in the top of each figure), as a result of which the estimated number of cases per 100,000 population increases with pathogen con-centration. In all three examples, an FSO has been established at 1 cfu/100 g or −2 log10 cfu/g (note that a PO could be set to this level earlier in the value chain).
Example 3.1
In this example (Fig. 3.4), the maximum initial population (H0) in the raw material entering a step is estimated to be 103 cfu/g. Both growth from the initial population and contamination from other sources can be completely prevented, due no increase in the hazard level during the step (ΣI = 0). The PC required across the step to deliver the PO/FSO for the step can then be derived from Eqs. (3.1) and (3.2) as follows:
H FSO or PO and PC
in which thus
0 1
3 0 2 5
− + ≤
( )
= − +− + ≤ − ≤
Σ Σ Σ Σ
Σ Σ
R I R I
R , R,
PPC= − + ≥ −5 0 5
(3.2)
Fig. 3.4 Example 3.1 (see text) 3.5 Deriving Performance Criteria
84
Fig. 3.5 Example 3.2 (see text)
Fig. 3.6 Example 3.3 (see text)
3 Meeting FSO and PO Through Control Measures
85
This means that across this particular step, the food safety management system to be implemented should achieve an overall reduction in initial hazard level of 5 log10 or more in order to meet the FSO/
PO. This corresponds for instance to a performance standard that delivers a 5D reduction in the level of the pathogen in combination with control measures that completely avoid re- or cross-contamina-tion from happening after the 5D reduccross-contamina-tion treatment.
Importantly, the food safety management system of the operator of the previous step that supplies the incoming material to the current step needs to assure that the outcoming hazard level (i.e. the PO of the previous step) is no higher than 1000 cfu/g. Should the hazard level of the previous step, which represents the H0 of the current step, be higher than accounted for, the calculated PC will not achieve the FSO/PO.
A suitable microbiological criterion may be established to verify that an incoming hazard level (H0) and outcoming hazard level (PO/FSO) meets the level targeted at (Zwietering et al. 2015). Note that comparable supplier requirements and verification tools for H0 and PO/FSO apply to all examples following.
Example 3.2
In this example (Fig. 3.5), the maximum initial population (H0) in the raw material can be controlled to ≤100 cfu/g and any increase in hazard level during the step (ΣI) can be prevented completely. The required PC follows from:
H FSO or PO and PC
in which thus
0 1
2 0 2 4
− + ≤
( )
= − +− + ≤ − ≤
Σ Σ Σ Σ
Σ Σ
R I R I
R , R,
PPC= − + ≥ −4 0 4
(3.2)
In this case, the management system should achieve an overall reduction of at least 4 log10 units to meet the FSO/PO of −2 log10, corresponding to for instance a performance standard that delivers a 4D reduction in hazard level combined with control measures that avoid any subsequent contamination.
Example 3.3
In this example (Fig. 3.6), the initial population (H0) in the raw material at maximum is 103 cfu/g, but also growth of the hazard is possible within the step concerned. However, control measures are in place to limit the increase of the hazard due to growth to 100-fold (2 log10) and to avoid contamina-tion. The PC required across the step would be deduced as follows:
H FSO or PO and PC
in which thus
0 1
3 2 2 7
− + ≤
( )
= − +− + ≤ − ≤
Σ Σ Σ Σ
Σ Σ
R I R I
R , R,
PPC= − + ≥ −7 0 7
(3.2)
In this example, the management system should achieve at least an overall reduction of 7 log10
units (i.e. from 105 cfu/g to ≤1 cfu/100 g) to meet the FSO/PO. This could for instance be achieved by heat processing targeting a performance standard of 7D reduction in combination with a control measure that can limit growth to a maximum of 2 log10 units (e.g. cooling during storage within the step for a time limited period) plus a control measure for complete avoidance of post-process contami-nation (e.g. aseptic packaging).
Examples 3.4, 3.5, 3.6, and 3.7 (Figs. 3.7, 3.8, 3.9, and 3.10) provide additional cases of the use of the conceptual equation for situations where the increase in hazard level through recontamination and/
or cross-contamination does not play a significant role. Examples 3.8, 3.9, and 3.10 relate to situations where contamination from external sources or discrete events require tailored approaches to correctly quantify the changes in hazard levels, because these following with involve additions on the non- logarithmic scale in contrast to for instance growth and inactivation.
3.5 Deriving Performance Criteria
86
Fig. 3.7 Example 3.4 (see text)
Fig. 3.8 Example 3.5 (see text)
3 Meeting FSO and PO Through Control Measures
87
Example 3.4
In this example (Fig. 3.7), there is no reduction event possible within the step concerned, i.e. no con-trol measure available to reduce the incoming hazard level or to offset an increase within the step due to growth or contamination. Since there is no change in the hazard level possible within the step, the incoming hazard level should not exceed the FSO/PO set for product leaving the step:
H FSO or PO and PC
H in which PC
0 0
1
0 0 2 0 0 0
− + ≤
( )
= − +− + ≤ − = + =
ΣR ΣI ΣR ΣI
, ,tthus
H0 ≤ −2
(3.2)
In this scenario, the pathogen level coming into the step should be equal or lower to 1 cfu/100 g in order to meet the FSO/PO set as the outcome for this step. To achieve this, appropriate control mea-sures need to be applied in the previous step (i.e. the suppliers’ operations).
0.00 0.20 0.40 0.60 0.80 1.00
-8 -6 -4 -2 0 2 4 6 8
Log (cell concentration or concentration change)
Probability density FSO
Fig. 3.9 Probability distribution of initial cell level (H0 ——), reduction in concentration (ΣR– – –) and increase in con-centration (ΣI– – –) of Listeria monocytogenes on fresh cut lettuce, and resulting cell concentration distribution (←) in packages of lettuce at the point of consumption using input values in Table 2.2
Fig. 3.10 Impact of level of inactivation between 0 and 8D on final hazard level, for a 1000 kg batch of food with a pre-processing hazard level of 1 log/g and post-processing contamination with 1 g of material containing 3 log10/g of the hazard
-5.00 -4.00 -3.00 -2.00 -1.00 0.00 1.00 2.00 3.00 4.00 5.00
0 2 4 6 8 10
I (log increase)
R (log rereduction) estimate I
real I Final level 3.5 Deriving Performance Criteria
88
Additionally, any increase in hazard level within the step concerned needs to be avoided by apply-ing appropriate growth controllapply-ing measures, such as intrinsic or extrinsic factors, in combination with measures to prevent contamination from external source, such as applying laminar flow or pack-aging. Should it not be possible to completely control an increase in hazard level across the step concerned, the H0 should be managed proportionally lower by the supplier/operator responsible for the previous step and adequate verification in place.
Example 3.5
In this example (Fig. 3.8), the initial level of the pathogen can be controlled to ≤10 cfu/g and any form of contamination can be confidently prevented. However, growth may be possible in the course of the step and a PC needs to be determined that sufficiently limits such growth. Assuming that the PO or FSO has been set at 100 cfu/g (2 log10), the required PC can be deduced as follows:
H FSO or PO and PC
in which thus P
0 1
1 0 2 1
− + ≤
( )
= − +− + ≤ ≤
Σ Σ Σ Σ
Σ Σ
R I R I
I , I,
C
C= + ≥0 1 1
(3.2)
Thus, to ensure that the FSO/PO is met, the increase in pathogen concentration across the step due to growth must not be more than ten-fold. This may be achieved through the establishment of appro-priate product criteria based on aw and pH, either alone or in combination. Whether such control measures adequately cap growth, needs to be properly validated. Also, again, assurance is needed from the food business operator(s) or supplier providing the relevant incoming raw material or ingredient(s), that the incoming hazard level (H0) is no higher than 10 cfu/g, otherwise the PC deter-mined would not be effective to achieve the FSO/PO.
Example 3.6
It should be recognized that in all of the five examples described above, the values for the various parameters of the conceptual equation were chosen as point estimates. However, in practice, each parameter will likely have a distribution of values associated with them that reflects the variability of the particular parameter. If stochastic data (i.e., data on the variability associated with one or more different parameters) are available, then these probability distributions may be used rather than point estimates. Examples 3.6 and 3.7 illustrate the use of stochastic data to develop a risk management framework for the control of E. coli O157:H7 and Listeria monocytogenes on in pre-cut lettuce, respectively. Further examples can be found elsewhere (ICMSF 2011; Zwietering et al. 2010).
Example 3.6 is explored in more detail in Chap. 17, where the use of risk metrics is illustrated in establishing control measures for enterohaemorrhagic Escherichia coli in leafy vegetables. The exam-ple makes use of data collected for initial levels of product contamination, efficacy of processing interventions, and growth during distribution. A public health goal of a 50% reduction in risk, estab-lished by a competent authority based on epidemiological data, was translated into a Food Safety Objective (FSO). Taking the FSO as a starting point, the ICMSF equation and the ICMSF risk man-agement tool (ICMSF 2010, 2015a) is used to explore options for food safety risk manman-agement of leafy vegetables including specification of a Performance Objective (PO) related to processing. In this example, the ICMSF equation is used to demonstrate the interplay between on-farm practices to mini-mize raw product contamination, disinfection during processing, growth during distribution, and the role of microbiological testing in a holistic food safety management approach.
Example 3.7
Szabo et al. (2003) estimated the initial contamination level of L. monocytogenes on pre-cut lettuce, reductions using sanitized washing, and increases after packaging as well as during storage and dis-tribution. For a given initial level of L. monocytogenes on lettuce and the expected level of growth (ΣI) during storage and distribution, the necessary reduction level to achieve a given FSO was determined.
3 Meeting FSO and PO Through Control Measures
89
For instance, given an initial population of H0 = 0.1 log10 cfu/g and an estimated potential increase of ΣI = 2.7 log10 cfu/g during storage for 14 days at 8°C, a ΣR ≥ 0.8 log10 cfu/g was deemed necessary to achieve the FSO value assumed to be set at 2 log10 cfu/g:
H0−ΣR+ΣI= →2 0 1 0 8 2 7 2. − . + . =
Using this approach, the process can be considered to achieve the FSO exactly. However, in order to fully appreciate the impact of process variation it is necessary to move from point estimates to distributions that describe the variability of control measures in the risk management framework; for illustration purposes, the data from Szabo et al. (2003) are used in the example that follows.
Assume the standard deviation for ΣI is 0.59, and assume the log increase of L. monocytogenes is normally distributed. For ease of calculation and explanation, H0 and ΣR levels do not include varia-tion. Because of the distribution of ΣI, the producer must target a lower average level of L. monocyto-genes in the finished product to reliably meet the FSO. If the same average level was targeted (i.e., FSO = 2 log10 cfu/g), 50% of the products would be above the FSO to some extent. The processor can consider other sanitizing wash methods to provide a greater reduction step to help to achieve the FSO through process control. The level of reduction needed to achieve different levels of conformity is presented in Table 3.4. For example, if the ΣR is 2.62, the proportion product above 2 logs, for a log normal distribution with mean log 0.18 and standard deviation 0.59 is 0.1%.
The next step in this example is to include variability in the process for all process stages. This section assumes variation for H0, ΣI and ΣR (see values in Table 3.5). The resulting total describes the distribution of levels of L. monocytogenes in packages of fresh cut lettuce at the point of consumption, and is equal to the sum of the log means for H0, ΣI and ΣR. The mean is not a correct indicator of the risk without considering the variance. The variance of the total distribution equals the sum of the vari-ances, thus the standard deviation is the square root of the sum of the squares of the standard devia-tions. The distributions are illustrated in Fig. 3.9. Given this distribution of outcomes, the proportion of packages of lettuce not meeting an FSO = 2 log cfu/g in this example is 0.2%.
Reduction Conceptual equation Probability that FSO = 2 is exceeded [ΣR] [H0−ΣR + ΣI] [P (H0−ΣR + ΣI) >2 (sd = 0.59)]
0.8 0.1–0.8 + 2.7 = 2 0.5 (50%)
1.2 0.1–1.2 + 2.7 = 1.6 0.25 (25%) 1.77 0.1–1.77 + 2.7 = 1.03 0.05 (5%) 2.17 0.1–2.17 + 2.7 = 0.63 0.01 (1%) 2.62 0.1–2.62 + 2.7 = 0.18 0.001 (0.1%) Also see ICMSF (2011), and Zwietering et al. (2010)
Note: The proportion above the FSO is determined by the cumulative normal distribution F(2;μ,σ2), which is calculated in Excel by 1-NORMDIST(2,x,s,1).
For example, for the last line =1−NORMDIST(2,0.18,0.59,1) = 0.001019 Table 3.4 Results of
various levels of reduction (ΣR) on the proportion of defective units (P) with a standard deviation for the increase of 0.59, assuming the log increase is normally distributed
Table 3.5 Results on the proportion of products that do not meet the Food Safety Objective (packages of fresh cut lettuce calculated to have greater than 2 log cfu/g Listeria monocytogenes present at the point of consumption), with various mean log and standard deviation values for H0, ΣI and ΣR
H0 ΣR ΣI Totala
Mean log −2.5 1.4 2.7 −1.2 H0−ΣR+ΣI
sd 0.80 0.50 0.59 1.11 sd = sqrt(sd12 + sd22 + sd32)
P(>FSO) 0.2%
Also see ICMSF (2011), and Zwietering et al. (2010)
aThe level (log cfu/g) of L. monocytogenes present in a package of lettuce at the point of consumption 3.5 Deriving Performance Criteria
90
