# Presentation: 050690

## Pathogen Reduction DialoguePanel 3 PERFORMANCE STANDARDS AND STATISTICAL SAMPLING

- Loren Lange
- Assistant Deputy Administrator
- Office of Public Health and Science
- May 7, 2002

## WHAT WILL BE DISCUSSED?

- History of Statistically Based Studies--Baselines
- How Data from Baselines Studies Was Used to Develop Existing Performance Standards

## History of Statistically Based 

- History of Statistically Based
- FSIS Microbiological Studies
- for Meat and Poultry Products

## BACKGROUND

- Microbiology Division Formed -- Mid ‘60’s
- 1st Large Statistically Based Survey--1982-1984 (Single Organism)
- Steer/Heifer Baseline Initiated--Oct. 1992
- Development of PR/HACCP Rule Begins--Fall 1994
- Standards Established--July 1996

**Notes:**
--national Salmonella incidence in broilers in 1982 to 1984; prior to this, there were limited surveys in the late ‘60’s and ‘70’s

--steer heifers 1st baseline conducted--first started used in the rule

--july ‘83 first rte--cooked roast and corned beef monitoring mm9; limited surveys prior to this

--baselines prior to beginning of rule

## ORIGINAL BASELINE OBJECTIVES

- To Collect Data Which Provide a General Microbiological Profile of Product for Selected Microorganisms of Various Degrees of Public Health Concern
- To Use the Information and Knowledge Gained From This Program As a Reference for Further Investigations and Evaluation of New Prevention Programs.

## NEWER BASELINE OBJECTIVES	

- Support Risk Assessments
- 	- Required by 1994 Reorganization Act
- 	- Effective April 15, 1995
- Support Development of Standards
- 	- Baseline Data Used to Develop Standards
- 	   Published in 1996

## KEY DESIGN FACTORS

- Nature and Number of Microorganisms
- Desired Accuracy of Estimates (Number of Samples Required)
- Cost and Laboratory Resources

## BASELINE ORGANISMS

- Pathogenic Organisms
*Clostridium perfringens*
*Staphylococcus aureus*
*Listeria monocytogenes*
*Campylobacter jejuni/coli*
*Escherichia coli *O157:H7
*Salmonella*

**Notes:**
--All organisms were quantitated except O157:H7

-- --the organisms selected were those most often associated with human illness as determined by foodborne illness reports or certain pathogens of concern because of the severity of the illness they produce in humans

## BASELINE ORGANISMS(cont’d)

- Indicator Organisms
- Aerobic Plate Count @ 350 C
- Total Coliforms
* *Generic* Escherichia coli*

**Notes:**
--data on certain bacteria, or groups of bacteria, thought to e of value as indicators of general hygiene or process control were also collected

##    NUMBER OF SAMPLES

-    Steer/Heifers		Approx. 2,100
- 	Cows/Bulls
- 	Market Hogs
-     Poultry Carcasses		  1,200 - 1,300

## ENSURED REASONABLE LEVELS

** ****OF PRECISION**

- _Product_

- Estimated Product
- Prevalence for
_*Salmonella*_

- 95%
- _Confidence Level_

-     Market Hog		 8.7	± 1.18%
-     Young Chicken	20.0	± 2.16%
-     Cow/Bull	  2.7	± 0.78%

- How Were The Performance
- Standards Derived From
- Baseline Results?

-   FSIS Used the Estimated National
-    _Product Prevalence for __*Salmonella*_
- 		    _Product__	__	__	__Percent_
- _	_      - Young Chicken		   20.0
- 	       - Cows/Bulls		               2.7
- 	       - Steers/Heifers		     1.0
- 	       - Market Hogs		               8.7
- 	       - Ground Beef		               7.5
- 	       - Ground Chicken		   44.6
- 	       - Ground Turkey		   49.9

##  The Baseline Prevalence is an Estimate of 

-    the Percentage of Product that Would Test
-    Positive for *Salmonella*
-  The Baseline Prevalence Can Also Be
-   Viewed As the Probability That Any One
-   Sample Will Be Positive
-   FSIS Decided That Performance Would Be
-    Measured by a Series of Samples Referred
-    to As a Set of Size **‘n’.**

- When Sampling with Two Possible Outcomes (**+/-**), the Number of Positives **x** in **n** Independent Samples is said to Possess a Binomial Distribution where:
- Probability (**x** positives) = **(n!/[x!(n-x)!])p****x****q****n-x**
- Where **p** is the Probability of a Positive (i.e.,Baseline Prevalence) and **q=1-p**

-    It follows that:
-    Probability (c or fewer positives) =

- 

**C positives**

**x = 1 Positive**

**(n!/[x!(n-x)!])p****x****q****n-x**

- FSIS Decided That an Establishment Operating at the Baseline Prevalence Should Have an **80%** Probability of Passing
- Selecting **80%** Came From Balancing the Need to Prevent an Establishment From Failing Based on Chance Results and the Need to Identify Establishments Likely to be Operating Above the Prevalence

-    The Following Equation was then Solved for Different Combinations of **c** and **n**.

- 

**C positives**

** ****x = 1 Positive**
**Where  p = baseline prevalence**

**= 0.80**

**(n!/[x!(n-x)!])p****x****q****n-x**

- Finally, FSIS Decided That **n** Needed to Be Greater Than 50 So That Sampling Would Measure Process Control Over Time
- So the **n** and **c** in the Meat and Poultry Regulations Are the First Combination Where **n**>=50 and Probability (**c** or Fewer Positives)=0.8 Where the Probability of Any Single Positive Is the Baseline Prevalence.

## OC CURVE

- OC Curve Illustrates the Performance of a Particular Sampling Plan and the Risk of Both Types of Errors
- OC Curve Shows the Likelihood of Passing at Different Levels of Prevalence

**Notes:**
--OPERATING CHARACTERISTIC CURVE

## Slide 21

**Notes:**
--% POSITIVE ON THE X AXIS

--PROBABILITY OF PASSING ON THE Y AXIS

--VERTICAL LINE SHOWS THE PERFORMANCE STANDARD

--CURVE LINE SHOWS THE PROBABILITY OF PASSING A SAMPLE SET FOR A PRODUCT AT EACH PROCESS PERSENT POSITIVE.  FOR EXAMPLE,

## Baseline

-  Prevalence
- (8.7 %)