Role of Microbiological Criteria and Value of Sampling · ICMSF Microorganismsin Foods. 7....

Public Health Agency of

Canada

Role of Microbiological Criteria and Role of Microbiological Criteria and

Value of SamplingValue of Sampling

Anna M Lammerding

Guelph, Ontario Canada

Microbiological Criteria and Microbiological Criteria and

SamplingSampling

� Traditional definition and use

� Broadening the scope

– Thinking outside of the ‘lot’

– “Fit for purpose”

� If you do it…

– Do it right

– Use it.

Microbiological Criterion: Microbiological Criterion:

Traditional DefinitionTraditional Definition

� The acceptability of a product or a food lot, based on the absence/presence or number of organisms including parasites, and/or quantity of their toxins/metabolites, per unit(s) of mass, volume, area or lot

– ICMSF, 1974, 1986; Codex AlimentariusCommission, 1997

� A statement of the microorganism of concern and/or their toxins/metabolites and the reason for that concern

� The food to which the criterion applies

� The specific point(s) in the food chain where the MC should be applied

� Microbiological limits defining acceptable or reject

Elements of a Microbiological

Criterion (MC)

� A sampling plan defining number and size of samples, method of sampling and handling

� The number and size of the analytical units to be tested

� The analytical methods to be used to detect or quantify

� The number of analytical units that should conform

� Any actions to be taken when criterion is not met


Criterion

Different types of criteria Different types of criteria

� Microbiological Standards

– Mandatory, written into law or regulations

– Acceptability of a food or compliance with

a regulation or policy

– Defined by governments


� Microbiological Guidelines

– Advisory; acceptable or expected microbial levels when the food production process is under control

– Defined by governments or industry


� Microbiological Specifications

– Established between buyers and

producers that define product quality and

safety attributes for ingredients or

finished product

Types of Microbiological AnalysesTypes of Microbiological Analyses

�Direct

–Analyses for specific pathogens

� Indirect

–Analyses for indicator

microorganisms

� Indicator organism

– A microorganism that is associated with a

condition or state that impacts food safety

– for example - E. coli as an indicator of

fecal contamination

Types of Microbiological AnalysesTypes of Microbiological Analyses

� Variables Sampling / Quantitative

– Determination of levels present

� Attribute Sampling

– Qualitative (Presence/absence)

– Quantitative results that have been grouped (e.g. < 10 cfu/g, 10 – 100 cfu/g, >100c cfu/g)

Variables Microbial TestingVariables Microbial Testing

� Use with quantitative data when

microbial history (distribution) is

known and new results can be

compared to see if statistically

different

�Make full use of quantitative data

TwoTwo--Class (Presence/Absence) Class (Presence/Absence)

Attribute Sampling PlansAttribute Sampling Plans

� Sampling plan definitions

– n: number of sample/analytical units examined per lot

– m: a microbiological limit (i.e. cfu/g); a sample is defined to be positive if its microbial content exceeds this limit

– c: maximum allowable number of sample units that can be positive and the lot is still acceptable; for pathogens, c is usually set to 0

ThreeThree--Class Attribute Sampling PlansClass Attribute Sampling Plans

� Use with “binned” quantitative data

wherein three levels defined

–Acceptable

–Marginally acceptable

–Unacceptable

ThreeThree--Class Attribute Sampling PlansClass Attribute Sampling Plans

– n: number of sample units analyzed

–m: level below which sample unit is

acceptable

– M: level wherein if any sample unit

exceeds this value will result in the lot

being rejected

– c: maximum number of marginally

acceptable sample units above which the

lot will be rejected

Log cfu/g

Probability Density

0 1 2 3 4 5 6

0.0

0.1

0.2

0.3

0.4

0.5

0.6

mean

s.d. s.d.

s.d.: standard deviation (=0.8)

Frequency Distribution Describing Lot Quality

Log cfu/g

Probability Density

0 1 2 3 4 5 6

0.0

0.1

0.2

0.3

0.4

0.5

0.6m

Proportion defective

Two-class sampling plan:

Log cfu/g

Probability Density

0 1 2 3 4 5 6

0.0

0.1

0.2

0.3

0.4

0.5

0.6m M


Three-class sampling plan:

Log cfu/g

Probability Density

0 1 2 3 4 5 6

0.0

0.1

0.2

0.3

0.4

0.5

0.6m M


Proportion marginally acceptable

Three-class sampling plan:

ICMSF CasesICMSF Cases

� Qualitative risk-based guidance for

selection of samplings plans

� Statistically-valid for defined distributions

15 cases which reflect severity of the hazard, effect of handling/preparation on the hazard, and intended population

ICMSF CasesICMSF Cases

Case 3Case 2Case 1Utility

Case 15Case 14 Case 13Severe

Case 12Case 11Case 10Serious

Case 9Case 8Case 7Moderate

Case 6Case 5Case 4Indicator

Conditions

may increase

hazard

Conditions

cause no

change in

hazard

Conditions

reduce

hazard

Type of

hazard

ICMSF TwoICMSF Two--Class Plans: Mean CFU/G Class Plans: Mean CFU/G

Rejected With 95% ProbabilityRejected With 95% Probability

Case 15:

n=60, c=0

1 cfu / 526g

Case 14:

n=30, c=0

1 cfu / 278g

Case 13:

n=15, c=0

1 cfu / 135g

Case 12:

n=20, c=0

1 cfu / 185g

Case 11:

n=10, c=0

1 cfu / 83g

Case 10:

n=5, c=0

1 cfu / 32g

m = 0 cfu / 25g,

and standard deviation s.d. = 0.8

To develop an effective MC To develop an effective MC –– need need

to know:to know:

�The mean and distribution of the

microorganism within the lot

�Definition of what is ‘acceptable’

and what is not

Probability Density

Log cfu/g

m

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa pd

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa pd

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa pd

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pdpa

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pa pd

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pd

Probability Density

Log cfu/g

0.0 1.0 2.0 3.0 4.0 5.0 6.0

m

pd

Probability Density

Log cfu/g

EndEnd--product testing product testing –– limited valuelimited value

� The number of samples required

becomes a limiting factor when the

defect rate is small (<5%)

� Process control testing is more

appropriate when verifying

effectiveness of food safety systems

Broadening the Definition of Broadening the Definition of

Microbiological CriteriaMicrobiological Criteria

� In the past, MC have often been

subjectively established without

clear links to public health risk

New challenges New challenges –– new concepts new concepts ––

new ways of thinkingnew ways of thinking



� New challenges:

– Very low levels and prevalence of pathogens –limitations of methods to detect by ingredients or end product testing

– Global trade of foods -> low levels, low prevalence can result in widespread outbreaks

– Changing diets, different types of foods, challenges to testing product: fresh fruits and vegetables, sprouts



� Introduction of risk analysis framework to microbial food safety, and new concepts in risk management, microbiological criteria have evolved to be components of an overall risk-based control system, to be implemented when useful and needed to achieve FSO, PO and Public Health Objectives


Raw

Ingredients

Pasteurization Storage Consumption Illness

Process Criteria

(e.g. deg C/min)

Food Safety

Objective

(cfu/g, %)

ALOP (e.g.

cases/yr)

Consider use to assess process/control

measure(s), sampling & testing methods, take into

account growth after the MC point



�MC need to be applied when and

where they are most useful, and to

generate results that inform risk

managers in decision-making.

Examples of Microbiological Testing in Food Examples of Microbiological Testing in Food

Safety ManagementSafety Management

Acceptance Testing

� Lot inspection by government; test end-products, attributes sampling plan for pathogens, indicators

� Verification of lots (batches) of known history, by government (end-products) or by industry (raw materials); attributes sampling plan for pathogens, indicators



� Monitoring, checking– CCP’s, process lines by industry; test line samples with attributes or variables sampling plans for indicators

� Environmental sampling– Line (contact surfaces), non-contact environment samples; used by industry, test residues, dust, water. Sampling plan targeted to find sources of contamination, efficacy of cleaning and disinfection



� Verification

– Part of HACCP programs by industry, end

product testing using attributes sampling

plans, test for pathogens/indicators

� Surveillance

– Compliance surveys by governments/industry

on products in commerce; attributes sampling

plans (usually n = 1) test for pathogens


Safety Management Safety Management

� Investigation

– Testing anywhere along the food chain by governments or industry; all types of samples; investigational – rarely statistically-based, may be biased sampling (targeted) based on prior knowledge

– Baseline studies – must be statistically-based


Criterion

� All valid considerations when “thinking outside the lot”

� Statistically-valid

Considerations for microbiological Considerations for microbiological

testingtesting

� Evidence of actual or potential hazards to

health

� The microbiological status of raw

materials

� The effect of processing

� Likelihood and consequences of microbial

contamination and/or growth during

subsequent handling, storage and use

ConsiderationsConsiderations

� The intended use of

the food

� The category of

consumers concerned

� The cost-benefit ratio

associated with the

application of the

particular criterion

Food Protection

Report,

July/August 2001

Microbial TestingMicrobial Testing

� Effective use

requires a clear

understanding of

the goals,

assumptions, and

characteristics of

both the testing

methods and the

sampling plans

MethodMethod’’s Operating s Operating

CharacteristicsCharacteristics

� Lower Limit of

Detection

� Repeatability

� Reproducibility

� Ruggedness

� Variance - Confidence

Intervals

Codex Current WorkCodex Current Work

� Proposed Draft Guidelines for Control of Campylobacter and Salmonella spp. in Chicken Meat

� New approach for international trade guidelines

� Critical assessment of published data useful for these guidelines – scientifically sound – methods, sampling

� Poorly conducted studies – not considered

ControlsControls

� GHP-based:

– Measures that are generally qualitative

in nature and are based on empirical

scientific knowledge and experience.

Usually prescriptive and may vary

between countries

ControlsControls

Hazard-based:

– Measures that are developed from

scientific knowledge of the likely level

of control of a hazard …have a

quantitative base and can be

validated…obvious expectation of

consumer protection but actual degree

of protection unknown.

ControlsControls

� Risk-based:

– Measures developed from risk assessments or other information on risk (e.g. surveillance data), on the basis of specific knowledge of the likely level of consumer protection that will result…quantitative base and can be validated against a level of consumer protection

Microbiological Testing & Microbiological Testing &

SamplingSampling

� Essential for inspection

� Essential to verify hazards are controlled

� Valuable for environmental monitoring

� Risk assessment

� Useful to detect defective batches

� CANNOT guarantee 100% safety

� Quality control cannot be based on end-product testing only

� The classical ‘ICMSF cases’ and sampling

schemes still offer a risk-based approach

for examining lots for regulatory or trade

purposes

� The statistical basis for ICMSF cases can be

applied for other types of sampling

programs

Microbiological Testing & Microbiological Testing &

SamplingSampling

????

Make Use of the Data!Make Use of the Data!

� Microbiological data collection is resource intensive…

� Define purpose – will the data (and efforts) help make better risk management decisions?

� Make sure the data collection process is statistically sound, appropriate methods to sample and test

� Microbiological data that is not analysed, not used to inform decision-making - serves no purpose!

� If you collect it, use it!

ReferencesReferences

� ICMSF Microorganisms in Foods. 7. Microbiological Testing in Food Safety Management (2002)

� Microorganismos de los alimentos. 7. Análisis microbiológico en la gestion de la seguridad alimentaria (2004)

� www.icmsf.itt.edu

Coming Soon!!

In memory of, and tributes to, Susanne Dahms (1963 – 2007)

Profesora (Berlin, Germany);

Statistician; ICMSF Member

(1998-2007); speaker at 1st

ABRAPA meeting in SP (2002); an

adventurer, scientist, artist,

traveller, teacher … too short her

life with us.

Someday,

they will

get it

right!

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Role of Microbiological Criteria and Value of Sampling · ICMSF Microorganismsin Foods. 7....

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