# Presentation: 711896

## Risk Assessments for Salmonella Enteritidis in Shell Eggs and Salmonella spp. in Liquid Egg Products

- October 22, 2004

**Notes:**
We will actually be looking at two different risk assessments today.  One is for Salmonella Enteritidis in shell eggs and the other is for all Salmonella serovars in egg products.

## Outline

- Risk Assessment of* Salmonella* Enteritidis in Shell Eggs
- Review risk management questions
- Brief description of model
- Results
- Risk Assessment of* Salmonella *spp. in Liquid Egg Products
- Review risk management questions
- Brief description of model
- Results

- 04/30/2002

**Notes:**
We tend to see only Salmonella Enteritidis in shell eggs while we see many types of Salmonella in egg products.  So, it is easier to consider shell eggs and egg products separately.  For each risk assessment we will first review risk management questions.  Then we will give a very brief overview of the model.  Finally, we will give the results of the risk characterization.

## Risk Assessment of Salmonella Enteritidis in Shell Eggs

**Notes:**
So first we will review the Risk Assessment of Salmonella Enteritidis in Shell Eggs.  

## Risk Management QuestionsSalmonella Enteritidis in Shell Eggs

**Notes:**
The Salmonella Enteritidis in Shell Eggs risk assessment addresses three different risk management questions.

## Risk Management Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella* Enteritidis in pasteurized and non-pasteurized shell eggs?

- 04/30/2002

**Notes:**
The first one is, “What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?”

## Risk Management Question 2

- What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?

- 04/30/2002

**Notes:**
Question 2 is, “What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?”

## Risk Management Question 3

- What is the number of *Salmonella* Enteritidis in shell eggs before and after a specified pasteurization scenario?

- 04/30/2002

**Notes:**
And question 3 is, “What is the number of Salmonella Enteritidis in shell eggs before and after a specified pasteurization scenario?”

## Model DescriptionSalmonella Enteritidis in Shell Eggs

**Notes:**
The Salmonella Enteritidis in Shell Eggs risk assessment uses a farm to table model.

## Inputs by Model Stage (Eggs)

**Storage1**

**Preparation**

**Cooking**

**Health**
**Effect**

**Pasteurization**

**Storage2**

- SE in egg at lay

- growth in egg prior to processing

- dose response function

- cooking effect

- servings per contaminated egg

- growth in egg after pasteurization

- pasteurization factor

- 04/30/2002

**Notes:**
This slide shows a graphical overview of the model.  An egg starts with a certain number of bacteria.  Those bacteria can grow until and if the egg is pasteurized.  After pasteurization the bacteria may grow again.  The egg is then allocated into one or more servings and the servings are cooked.  Finally the number of bacteria left after cooking are used as an input into the dose response function to determine if illness occurs.

## Modeling Illnesses – Determine:

- If egg is contaminated with SE
- How much SE is in egg
- Growth due to storage
- Decline due to cooking
- Consumption by one or more persons
- Whether dose causes illness

- 04/30/2002

**Notes:**
The model considers several things to estimate illnesses:  We model contaminated eggs one at a time from farm to fork.  First we must determine is if the egg is contaminated with SE.  If it is, how much SE is in it.  Then we estimate the growth due to storage and the decline due to cooking.  Then we estimate how much of the egg was consumed by one or more persons.  Finally, we determine whether the consumed doses would cause illness.
Each of these determinations requires collection and analysis of the available information, construction of probability distributions to represent the variability in different practices, and incorporation of these distributions into a computer model.

## Modeling Illnesses – Determine: If egg is contaminated with SE

**Factors**
- Infected flock
- Infected chicken
- Infection passed to egg

**Data Sources**
- FSIS surveys
- SE Pilot Project
- ARS studies
- Published literature

- 04/30/2002

**Notes:**
The first step in modeling illnesses is to determine whether an egg is contaminated.  This depends first on whether the flock is infected with SE.  Producers routinely test incoming chicks and pullets for SE, but SE can enter the house in other ways and insect and rodent vectors can maintain SE in houses that have been cleaned and disinfected.  If the flock is infected we must determine whether the chicken that laid the egg is infected?  Individual hens vary in their exposure and susceptibility to SE.  Thus, only a fraction of the hens will actually be infected.  Finally, we must determine whether the infection is actually passed to the egg.  Not all infected hens pass SE into the egg and those that do usually only do so for a short period of time.  Data for this estimate came from FSIS surveys, ARS studies, and the published literature.

## Modeling Illnesses – Determine:How much SE is in egg

**Factors**
- Location
- Shell membrane
- Albumen
- Vitelline membrane
- Yolk
- Egg to egg variability

**Data Sources**
- Published literature
- Analysis of study data

- 04/30/2002

**Notes:**
If the egg is infected, we must determine how much SE is in the egg.  This depends on the location of the contamination within the egg.  Whether the contamination is on the shell membrane, in the albumen, in the vitelline membrane that separates the albumen from the yolk or in the yolk itself.  It also depends on individual egg or hen variability.  We used information from the published literature and from analysis of data provided by researchers.

## Modeling Illnesses – Determine: Growth of SE due to storage

**Factors**
- SE growth dynamics
- Time
- Temperature
- Location of egg
- Carton
- Case
- Pallet

**Data Sources**
- National Animal Health Monitoring System survey
- Audits International surveys
- Published literature

- 04/30/2002

**Notes:**
Once we know that the egg is contaminated we need to know how much the SE grow while the egg is in storage.  We model the time and temperature of the egg at each step of the farm to fork continuum.  Along with ambient temperature, the temperature of the egg depends on whether the egg is stored in the center or the edge of a carton, a case, or a pallet.  Eggs that are stored in the center of a pallet will take longer to cool than eggs stored at the edge.  If eggs are stored long enough and warm enough, SE will grow.  A diverse set of data sources was used to estimate both how SE grows and the types of conditions to which eggs will be exposed.

## Modeling Illnesses – Determine: Decline of SE due to cooking

**Factors**
- Type of serving
- Egg
- Mixture
- Beverage
- Type of cooking
- Hard boiled, soft boiled
- Scrambled, fried, omelet
- Raw

**Data Sources**
- Published literature
- Continuing Survey of Food Intake by Individuals

- 04/30/2002

**Notes:**
After SE grow in the egg, they can then be killed by cooking.  This depends on the type of serving and then the type of cooking.  Eggs may be served as eggs or they may be ingredients in some type of mixture such as a cake.  Eggs may also be incorporated into a beverage such as egg nog.  The number of bacteria that are killed also depends on how thoroughly the egg is heated.  For instance, soft boiled eggs are not cooked as much as hardboiled eggs and would be expected to have more surviving SE.  We used data from CSFII and the published literature to estimate the types of servings and expected log reductions for each type of serving and cooking method.

## Modeling Illnesses – Determine:Consumption by one or more persons

**Factors**
- One egg may serve more than one person
- Pooling
- Multiple eggs in recipe
- More servings per egg = more exposures to fewer SE

**Data Sources**
- Continuing Survey of Food Intake by Individuals

- 04/30/2002

**Notes:**
It is important to remember that one egg may serve more than one person.  This can occur when eggs are broken out into a bowl and held for later use, or when eggs are simply combined in a recipe.  CSFII tells how many gram of egg are in a serving; it does not tell how many eggs went into the serving.  As we noted earlier a recipe that serves 10 means that one contaminated egg in the recipe will expose 10 people.  Each of these 10 people would get one tenth of the dose, but that dose may still be enough to cause illness.  

## Modeling Illnesses – Determine:Whether dose causes illness

- Dose response model developed by Joint Expert Meetings on Microbiological Risk Assessment
- Joint FAO/WHO response to Codex request

- 04/30/2002

**Notes:**
Finally, we need to determine whether the amount of SE consumed will cause illness.  The dose response function used in the model is taken from the Joint FAO-WHO report developed by the Joint Expert Meetings on Microbiological Risk Assessment.  The extensive peer review of this report makes the choice of this dose response model easy to defend.

## ResultsSalmonella Enteritidis in Shell Eggs

**Notes:**
Let’s now do a quick review of the results.

## Baseline Model

- Best estimates
- Values
- Distributions
- Designed to model current practices

- 04/30/2002

**Notes:**
As we talk about the results of the two models we will refer to the baseline model and baseline results.  The baseline model uses our best estimates of input values and distributions and is designed to model current practices of production, processing, and preparation.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

- Risk Management Question 1

- 04/30/2002

**Notes:**
So the first risk management question was, “What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?”

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized |  |  |
| --- | --- | --- | --- |
|  |  |  |  |
| Illnesses/egg |  |  |  |
|  |  |  |  |
|  |  |  |  |

**0.000007**

- Risk Management Question 1

- 0.000007 equivalent to 7 per million or
- 7 x 10-6.

- 04/30/2002

**Notes:**
We will consider this question in parts.  When we think about servings we often think of how many eggs or how many grams of product a person eats.  So an individual might eat one, two, or three eggs for breakfast.  What we might not think about is that an egg may serve more than one person.  If we make scrambled eggs by cracking 12 eggs into a bowl, scrambling them, cooking them, and then feeding 6 people, then each of those 12 eggs has served 6 people.  So first we determine the number of illnesses that each egg can cause. [Click-Table]  The estimated illnesses per non-pasteurized shell egg is about 7 per million.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized |  |  |
| --- | --- | --- | --- |
|  |  |  |  |
| Illnesses/egg | 0.000007 |  |  |
| Annual illnesses |  |  |  |
|  |  |  |  |

**350,000**

- Risk Management Question 1

- Based on about 50 billion table eggs

- 04/30/2002

**Notes:**
There are about 50 billion shell eggs consumed as table eggs annually in the United States.  A table egg is one that is available to cook as an egg or to be incorporated as an ingredient in a recipe. [Click-Table] So given 50 billion table eggs and 7 illnesses per million, we would expect to have about 350,000 illnesses.

## Comparing Model Estimates to Epidemiologic Estimates

- Surveillance data from year 2000 implied 174,356 human illnesses
- Based on multiplying reported cases by 37
- Uncertainty within multiplier
- Visit doctor
- Culture taken
- Sent to lab
- Isolate organism
- Report by lab

- 04/30/2002

**Notes:**
Earlier Carl presented an estimate of about 174,000 human illnesses based on surveillance data from the year 2000.  350,000 is certainly more than that.  The estimate from the surveillance data is based on the assumption that there are 37 total cases for each reported case.  This multiplier, however, has uncertainty associated with it which is a product of the uncertainty underlying the various parts of the multiplier.  So it is to be expected that the estimate of 174,000 lies within a range of uncertainty.

## Comparing Model Estimates toUncertainty Based on CDC Estimates

- Model Baseline 350,000

- Uncertainty Based on CDC Estimates

- Upper Bound

- Lower Bound

- Model Baseline 350,000

- 04/30/2002

**Notes:**
So we looked to see how close our estimate of 350,000 illnesses was compared with epidemiologic estimates when we considered this uncertainty.  We used FoodNet data for Salmonella and SE to develop a distribution to describe the uncertainty associated with the estimate of SE cases due to shell eggs.  As you can see the baseline model result fell within the uncertainty associated with the epidemiologic estimate.  Recently, we have worked with colleagues to narrow the uncertainty. [Click-Yellow line] This yellow line represents our most recent distribution.  The new range of uncertainty is much more narrow and the baseline model estimate now appears near the upper end of the distribution.  It is still, however, within the bounds of uncertainty and thus, should be a useful model of the farm to table continuum.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized |  |  |
| --- | --- | --- | --- |
|  |  |  |  |
| Illnesses/egg | 0.000007 |  |  |
| Annual illnesses | 350,000 |  |  |
| Illnesses/serving |  |  |  |

**0.0000028**

- Risk Management Question 1

- 04/30/2002

**Notes:**
There are about 125 billion servings of table eggs annually. [Click-Table] Thus, there are about 2.8 illnesses per million servings of table eggs.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized | Pasteurized |  |
| --- | --- | --- | --- |
|  |  | 3 logs | 5 logs |
| Illnesses/egg | 0.000007 |  |  |
| Annual illnesses | 350,000 |  |  |
| Illnesses/serving | 0.0000028 |  |  |

**0.000002**

**0.000001**

- Risk Management Question 1

- 04/30/2002

**Notes:**
We modeled two pasteurization scenarios.  In one, we modeled a 3 log pasteurization. [Click-Table] This is equivalent to multiplying the number of bacteria in an egg by 0.001 or reducing the number by 99.9%.  This reduction in bacteria due to pasteurization results in an estimate of illnesses per egg of about 2 per million.  If we model a 5 log pasteurization we get a reduction to about 1 illness per million eggs.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized | Pasteurized |  |
| --- | --- | --- | --- |
|  |  | 3 logs | 5 logs |
| Illnesses/egg | 0.000007 | 0.000002 | 0.000001 |
| Annual illnesses | 350,000 |  |  |
| Illnesses/serving | 0.0000028 |  |  |

**110,000**

**52,000**

- Risk Management Question 1

- 04/30/2002

**Notes:**
The corresponding annual number of illnesses with these pasteurization scenarios is 110,000 for the three log pasteurization and 52,000 for the 5 log pasteurization.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized | Pasteurized |  |
| --- | --- | --- | --- |
|  |  | 3 logs | 5 logs |
| Illnesses/egg | 0.000007 | 0.000002 | 0.000001 |
| Annual illnesses | 350,000 | 110,000 | 52,000 |
| Illnesses/serving | 0.0000028 |  |  |

**0.0000009**

**0.0000004**

- Risk Management Question 1

- 04/30/2002

**Notes:**
And these annual number of illnesses correspond with about 9 illnesses per 10 million servings for the three log pasteurization scenario and about 4 illnesses per 10 million servings for the five log pasteurization scenario.

## What is the number of illnesses per serving and annual number of illnesses from Salmonella Enteritidis in pasteurized and non-pasteurized shell eggs?

|  | Non-pasteurized | Pasteurized |  |
| --- | --- | --- | --- |
|  |  | 3 logs | 5 logs |
| Illnesses/egg | 0.000007 | 0.000002 | 0.000001 |
| Annual illnesses | 350,000 | 110,000 | 52,000 |
| Illnesses/serving | 0.0000028 | 0.0000009 | 0.0000004 |

- Risk Management Question 1

- 04/30/2002

**Notes:**
This is a summary of the answer to question 1.

## What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?

- Risk Management Question 2

- 04/30/2002

**Notes:**
Question 2 was, “What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?”

## Scenarios Evaluated

- Refrigeration
- Time until refrigeration
- Pasteurization

- 0.5    1.0    1.5

- 0       3        5

- 45    53     60

- °F

- days

- logs

-  3 x 3 x 3 = 27 scenarios

- 04/30/2002

**Notes:**
To answer this we looked at different scenarios for refrigeration temperature, different scenarios for time until refrigeration, and the different scenarios for pasteurization for a total of 27 different combinations.  

## Results for Storage at 53 F and 60 F

- As many or more illnesses as baseline

- 04/30/2002

**Notes:**
Storage at 53 or 60 degrees Fahrenheit resulted in almost as many or more illnesses as the baseline scenarios.  This is because many producers and processors already refrigerate eggs shortly after lay.

## Storage at 45 F Within 0.5, 1, or 1.5 Days of Lay

- What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?

- 04/30/2002

**Notes:**
There was, however, a noticeable effect when eggs were stored at 45 degrees shortly after lay. [Click-Chart] This chart shows the annual number of illnesses for different pasteurization scenarios for eggs stored at 45 degrees within 12, 24, or 36 hours of lay. [Click-Orange] The orange bars represent the baseline scenarios that we examined earlier. [Click-Turquoise] The turquoise bars represent the result of storing eggs at 45 degrees within 36 hours of lay. [Click-Red] The red bars show the effect of refrigerating eggs within 24 hours of lay. [Click-Yellow] And the light yellow bars show the effect of refrigerating eggs within 12 hours of lay.  Because most producers collect eggs twice a day, refrigerating eggs within 12 hours of lay is essentially the same as refrigerating them as soon as they are collected.

## Storage at 45 F Within 0.5, 1, or 1.5 Days of Lay

- What is the effect of the temperature and length of time (in days) before eggs are collected after they are laid by the hen and then refrigerated and further processed on the estimated risk of illness?

|  | Pasteurization |  |  |
| --- | --- | --- | --- |
| Days | None | 3 logs | 5 logs |
| 0.5 | 77,000 | 14,000 | 7,200 |
| 1.0 | 130,000 | 33,000 | 17,000 |
| 1.5 | 240,000 | 66,000 | 32,000 |
| Base | 350,000 | 110,000 | 52,000 |

- 04/30/2002

**Notes:**
This is a table showing the same results we saw in the previous chart.  Note that a combination of rapid refrigeration plus pasteurization is much more effective than either mitigation alone.  Without refrigeration, SE bacteria in eggs can quickly reach high levels that pasteurization cannot eliminate.  Without pasteurization, many more eggs remain contaminated so that later exposures to high temperatures result in rapid growth later in the continuum.

## What is the number of Salmonella Enteritidis in shell eggs before and after a specified pasteurization scenario?
Pasteurization decreases the number, BUT
Regrowth can occur

- Pasteurization decreases the number, BUT
- Regrowth can occur

- Risk Management Question 3

- 04/30/2002

**Notes:**
Question 3 is, “What is the number of Salmonella Enteritidis in shell eggs before and after a specified pasteurization scenario?”  In short, we saw that pasteurization decreases the number of SE bacteria, but regrowth of these bacteria can still occur if there are surviving bacteria after pasteurization.

## Potential for Human Illness at Various Model Stages

- 04/30/2002

**Notes:**
The number of bacteria at each model stage is actually a distribution.  It may be easier to think of these distributions in terms of their ability to cause human illness.  Thus we can think of the potential for human illness at various model stages if humans were to consume raw eggs at those stages.  This is, of course, unrealistic, but it does show how the potential risk of eggs changes in the farm to table continuum. [click – blue line] This light blue line shows the number of illnesses expected after each stage without pasteurization.  If all eggs were consumed raw in the layer house, there would be about 600,000 illnesses.  The potential illnesses increase to about 1.5 million by the time we reach the end of home storage.  Finally, cooking reduces the potential illnesses to about 350,000, our baseline value.
[click – yellow line] If eggs are subjected to 3 logs of pasteurization, the potential for human illness drops substantially.  Furthermore, the potential for additional illness does not increase as rapidly.  This is because bacteria have now been eliminated from most contaminated eggs.  Cooking further reduces the risk.  [click – green line] Five logs of pasteurization further reduces the potential for eggs to cause human illness.

## Uncertainty and Sensitivity

- Baseline model evaluates effect of variability
- Iterates through specific values and distributions
- Nominal range sensitivity analysis
- Series of scenarios
- Set all inputs except one to the baseline values
- Set remaining inputs to upper or lower bound

- 04/30/2002

**Notes:**
The SE in shell eggs risk assessment baseline model accounts for variability in the system by iterating through specific values and distributions.  The effect of uncertainty was evaluated by running a series of scenarios.  Each scenario consisted of setting all inputs except one to the baseline values.  The remaining input was set to an upper or lower bound.  These bounds were either set arbitrarily or by evaluating the uncertainty of parameters.  This nominal range sensitivity analysis is useful for evaluating the effect that each input has on the model output whether the uncertainties were characterized probabilistically or not.  

## Uncertainty and Sensitivity

- Inputs with greatest effect
- Storage temperatures
- Growth parameters
- Prevalence of contaminated eggs
- Pasteurization

- 04/30/2002

**Notes:**
Inputs that had the greatest effect on model output for the SE in shell eggs risk assessment were related to storage temperatures, growth parameters, and the prevalence of contaminated eggs.  Additionally, as noted earlier, pasteurization greatly influences the estimates of human illnesses.

## Summary of Shell Egg Model

- Baseline model estimates about 350,000 illnesses per year
- Quick refrigeration at 45F and pasteurization at 5 logs both effective in reducing illnesses
- Combination of refrigeration and pasteurization more effective than either alone

- 04/30/2002

**Notes:**
In summary, the baseline model estimates about 350,000 illnesses per year.  Quick refrigeration at 45F and pasteurization at 5 logs are both effective in reducing illnesses.  And, the combination of refrigeration and pasteurization is more effective than either alone in reducing illnesses.

## Risk Assessment of Salmonella spp. in Egg Products

**Notes:**
Now we will review the risk assessment of Salmonella species in egg products.

## Outline

- Review questions
- Brief description of model
- Anchoring of model
- Results

- 04/30/2002

**Notes:**
As with the risk assessment for SE in shell eggs, we will review risk management questions and give a brief description of the model.  Then we will discuss how we have anchored pasteurization estimates to the FSIS end product sampling and look at the results of the risk characterization.

## Risk Management Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella* spp. in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?

- 04/30/2002

**Notes:**
The first risk management question is, “What is the number of illnesses per serving and the annual number of illnesses from Salmonella spp. in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?”

## Risk Management Question 2

- What is the number of *Salmonella *spp. in a liter of egg product (whole, yolk, albumen) before and after a specified pasteurization scenario?

- 04/30/2002

**Notes:**
The second question is, “What is the number of Salmonella spp. in a liter of egg product (whole, yolk, albumen) before and after a specified pasteurization scenario?”

## Differences in Egg Products Model from Shell Egg Model

- _Egg Products Model_
*Salmonella *spp.
- processor to table
- illnesses per serving

- _Shell Egg Model_
*Salmonella* Enteritidis
- farm to table
- illnesses per egg

- 04/30/2002

**Notes:**
I’d like to point out some differences between the two risk assessments.  The egg products model is for all serovars of Salmonella, while the shell egg model is only for Salmonella Enteritidis.  The egg products model is a processor to table model while the shell egg model is a farm to table model.  This is not as big a difference as might appear because the effect of on farm mitigations could be modeled as a decrease in the incoming level of Salmonella in liquid egg product.  Lastly, the focus in the egg products model is on illnesses per serving, while in the shell egg model it is on illnesses per egg.

## Modeling Illnesses – Determine:

- How many *Salmonella* in a serving
- Decline due to pasteurization
- Growth due to storage
- Decline due to cooking
- Whether dose causes illness

- 04/30/2002

**Notes:**
The egg products model is built in a similar way to the shell eggs model.  Like the shell eggs model, the egg products model is complex, containing many distributions intended to represent the great variability in use, storage, and cooking of egg product servings.  Because there are relatively few contaminated servings the model must run about 10 times as long to reach the same level of stability.  
The egg products model first determines how many Salmonella are in a serving of liquid egg product, it then models the decline due to pasteurization, growth due to storage, further decline due to cooking, and then whether the dose causes illness.

## Modeling Illnesses – Determine:  How many Salmonella in a serving

**Factors**
*Salmonella* per gram in liquid egg product
- White
- Whole
- Yolk
- Size of serving

**Data Sources**
- FSIS raw egg product baseline study

- 04/30/2002

**Notes:**
The number of Salmonella in a serving of liquid egg product depends on the initial level in white, whole, or yolk, and on how large a serving is consumed.  We used the FSIS raw egg product baseline study to determine Salmonella per gram.

## Modeling Illnesses – Determine: Decline of Salmonella due to pasteurization

**Factors**
- Type of egg product
- White, whole, yolk
- Additives
- Salt, sugar
- Temperature
- Time
- Seven combinations – products, additives

**Data Sources**
- UEP sponsored pasteurization study

- 04/30/2002

**Notes:**
Unlike shell eggs, it is assumed that all liquid egg product is pasteurized to some level.  The decline of Salmonella due to pasteurization is dependent on the type of product and whether the product had any ingredients such as salt or sugar added to it before pasteurization.  These affect the time and temperature to which the product can be subjected during pasteurization and ultimately, the level of Salmonella in the product.  Seven combinations of products and additives are specifically modeled. A recent study sponsored by the United Egg Producers supplied data for this input.

## Modeling Illnesses – Determine: Growth of Salmonella due to storage

**Factors**
- Growth dynamics
- Time
- Temperature

**Data Sources**
- SE growth dynamics
- RTI expert panel

- 04/30/2002

**Notes:**
As with the shell eggs model, growth of Salmonella during storage is dependent on time and temperature.  We modeled growth with the same model as for shell eggs.  We did not, however, have time and temperature data available, so we used information from a previously convened expert elicitation panel.

## Modeling Illnesses – Determine: Decline of Salmonella due to cooking

**Factors**
- Type of serving
- Egg
- Mixture
- Beverage
- Type of cooking
- Thoroughly cooked
- Undercooked

**Data Sources**
- Continuing Survey of Food Intake by Individuals
- Cooking of shell eggs

- 04/30/2002

**Notes:**
Also similar to the shell eggs model, the decline of Salmonella due to cooking is dependent on the type of serving, whether the product is served as an egg, as a mixture in a recipe, or as a beverage, and then how thoroughly cooked the product is.  As with shell eggs we used data from CSFII.  We used log reductions in shell eggs as a proxy for log reductions in cooked egg products.

## Modeling Illnesses – Determine:Whether dose causes illness

- Dose response model developed by Joint Expert Meetings on Microbiological Risk Assessment
- Joint FAO/WHO response to Codex request

- 04/30/2002

**Notes:**
The same FAO/WHO dose response function is used for the egg products model as for the shell eggs model.

## Inputs by Model Stage

**Cooking**

**Health**
**Effect**

**Pasteurization**

**Storage**

- dose response function

- cooking effect

- growth of *Salmonella* in
- serving after pasteurization

- pasteurization factor

*Salmonella* in serving
- before pasteurization

- Baseline data

- UEP sponsored study

- End product
- sampling

- 04/30/2002

**Notes:**
This slide shows the main model stages.  Since this is not a farm to table model, there is no provision for growth of bacteria before pasteurization. [Wait until dose response function flies in] Now the Salmonella in serving before pasteurization is based on the [Click-Baseline data]  FSIS egg products baseline study and the pasteurization factor is based on the UEP sponsored study.  This information was used in the development of the model.  There is an additional source of information, however, that was not used in the development of the model and this is [Click-End product sampling] FSIS end product sampling. [Click-Anchoring]  We anchored the model to this information for one egg product type – egg white.

## Anchoring Model

- Purpose
- Ensures that results are consistent with reality
- Egg products model
- Unanchored model gives high estimate of human illnesses compared to epidemiologic estimates

- 04/30/2002

**Notes:**
We anchor a model to observed data to ensure that results are consistent with the real world.  We anchored the egg products model to end product sampling because we believe that the unanchored model gives a high estimate of human illnesses compared to epidemiologic data. 

## Anchoring Model

- Method
- Pasteurization levels adjusted to give results consistent with end product sampling
- Consequence
- Pasteurization level for egg white adjusted from 3.25 logs to 5.0 logs
- Other egg products consistent with end product sampling and not adjusted

- 04/30/2002

**Notes:**
So what we did was to adjust the pasteurization levels until we got results consistent with end product sampling.  The only level that needed to be adjusted was the one for egg whites.  This level was adjusted from a 3.25 log reduction to a 5.0 log reduction due to pasteurization.  The other egg products types were consistent with end product sampling and were not adjusted.

## ResultsSalmonella in Egg Products

**Notes:**
Now we will review the results for the egg products model.

## Policy Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella *spp*.* in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?

- 04/30/2002

**Notes:**
The first policy question was, “What is the number of illnesses per serving and the annual number of illnesses from Salmonella spp. in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?”

## Policy Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella *spp*.* in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?

- 04/30/2002

**Notes:**
As for shell eggs, we have divided this question into parts. [Click-Chart] This chart shows the expected illnesses per serving for pasteurization scenarios ranging from 5 to 12 logs of reduction due to pasteurization.  At this level of pasteurization the effect is fairly linear.  So increasing pasteurization from 6 logs to 7 logs means reducing the illnesses per serving by nearly a factor of 10.  This chart assumes that all egg products are pasteurized to the given pasteurization levels.

## Policy Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella *spp. in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?

**Baseline model result: 37,000 illnesses**

- 04/30/2002

**Notes:**
We next look at the annual number of illnesses.  [Click-Chart] This chart shows the annual number of illnesses expected for each of the given pasteurization levels.  This chart shows the straight line relationship seen in the previous chart.  There would be about 240,000 illnesses given a 5 log reduction, about 28,000 given a 6 log reduction, and about 2900 given a 7 log reduction. [Click-Baseline Result] The baseline model result is about 37,000 illnesses.  This does not mean that all egg products currently undergo what looks like about a five and a half log reduction.  Rather, it means that if we aggregate the illnesses for all of seven product types with baseline pasteurization, storage, and cooking assumptions we get about 37,000 illnesses.  

## Policy Question 1

- What is the number of illnesses per serving and annual number of illnesses from *Salmonella *spp. in pasteurized egg products (e.g., liquid whole eggs, yolks, and egg whites)?

| LR | Human Illnesses |
| --- | --- |
| 5 | 240,000 |
| 6 | 28,000 |
| 7 | 2900 |
| 8 | 280 |
| 9 | 28 |
| 10 | 3 |
| 11 | 0 |
| 12 | 0 |

**Baseline model result: 37,000 illnesses**

- 04/30/2002

**Notes:**
This slide shows the same information in tabular form.

## Policy Question 2

- What is the number of *Salmonella *spp. in a liter of egg product (whole, yolk, albumen) before and after a specified pasteurization scenario?

- 04/30/2002

**Notes:**
The second question is, “What was the number of Salmonella spp. in a liter of egg product (whole, yolk, albumen) before and after a specified pasteurization scenario?”

## Number of Salmonella spp. in a Liter  Before and After Pasteurization

- Number of *Salmonella *spp. in a Liter  Before and After Pasteurization

**Before pasteurization**

**3 log reduction**

**6 log reduction**

**9 log reduction**

- 04/30/2002

**Notes:**
This chart shows the number of Salmonella per liter before and after specified pasteurization scenarios.  On the x-axis are levels of Salmonella per liter.  On the y-axis is the percent of liters of egg product that are at or below the corresponding levels of Salmonella.  The vertical white line represents one Salmonella per liter.  [Click-Before Pasteurization]  The levels of Salmonella before pasteurization in whole egg is shown in this line.  Because the line intersects the vertical white line at 10%, we would expect that 10% of liters would have less than one Salmonella and that 90% would have more than one Salmonella per liter.  Over 50% would have more than 1000 Salmonella per liter.  [Click-3 log]  The next line shows the results of a 3 log reduction due to pasteurization.  Now, only about half of the liters would be expected to have one or more Salmonella. [Click-6 log] With a 6 log reduction, less than 5 percent would be expected to have more than one Salmonella [Click-9 log] and with a 9 log reduction, it is unlikely to have surviving bacteria.

## Policy Question 2

- What is the number of *Salmonella spp.* in a liter of egg product (whole, yolk, albumen) before and after a specified pasteurization scenario?
- Before pasteurization
- ~90% > 1 / liter
- After pasteurization
- 3 logs: ~50% > 1 / liter
- 6 logs: ~5% > 1 / liter
- 9 logs: ~0% > 1 / liter

- 04/30/2002

**Notes:**
This summarizes what we saw on the chart.  Nearly all liters of raw whole egg product before pasteurization would be expected to have one or more Salmonella bacteria.  Pasteurization to 9 logs of reduction virtually eliminates Salmonella.

## Model Output Sensitive To:

- Incoming level of *Salmonella*
- Log reductions due to pasteurization
- Use of end-product
- Cooking

- 04/30/2002

**Notes:**
The model output is sensitive to the incoming level of Salmonella, log reductions due to pasteurization, and how the end-product is used, especially how it is cooked.

## Summary of Egg Products Model

- Anchored baseline model estimates about 37,000 human illnesses
- Each log increase in pasteurization results in a log decrease in illness

- 04/30/2002

**Notes:**
In summary, the anchored baseline model estimates about 37,000 human illnesses.  The baseline model assumes that all egg products are pasteurized to effect at least a five log reduction.  Additional increases in pasteurization result in corresponding decreases in human illness.

## Questions?

- 04/30/2002

**Notes:**
Thanks for your time.  What are your questions?