The revised Codex Principles and Guidelines for the Establishment and Application of Microbiological Criteria Related to Foods

Transcription

1 The revised Codex Principles and Guidelines for the Establishment and Application of Microbiological Criteria Related to Foods Hajime Toyofuku, DVM., PhD Professor, Joint Faculty of Veterinary Medicine, Yamaguchi University, Japan Co-Chair of the CCFH MC revision WG

2

3 An approval of a new work on revision of the Codex MC Principles was requested by CCFH in 2009 Scope of the new work To update the establishment and application of MC by governments and industry in line with the latest knowledge and practices To introduce the new risk management metrics (FSO, PO and PC) and other quantitative microbiological limits (e.g. process control criteria, testing for HACCP verification) To provide guidance on the relationship between MC and MRM metrics

4 MAIN ASPECTS TO BE COVERED the principles of establishing microbiological criteria for within-lot evaluation of food product acceptability, the principles for establishing microbiological criteria for between-lot evaluation of food product acceptability in relation to verification of process control, effectiveness of HACCP programs, and other trend analysis application, the appropriate roles of microbiological testing for verification of process control within the context of HACCP and validation of control measures, the establishment and interpretation of microbiological criteria related to hygiene indicator microorganisms, the principles and practices for relating the stringency of a microbiological criterion to required or recommended risk management outcomes; i.e., means for relating the performance of sampling plans for both within-lot and between-lot applications to food safety risk management metrics (e.g., FSO, PO, PC), actions to be taken in case of non-compliance to microbiological criteria and other risk management metrics ( e.g., PO, PC), the role of microbiological testing to monitor environments in which foods are exposed and the establishment of performance criteria by competent authorities and industry to indicate an acceptable level of control.

5 What has been achieved? Work on revising the MC principles started in 2010, and still continues working groups, CCFH meetings A new 'main document', to replace the old MC principles CAC/GL was adopted at the Codex Alimentarius Commission meeting in July 2013 Seven practical examples on establishing and applying MC developed by a lead country and 3-5 mentee countries better use of the Codex Trust Fund, enhancing involvement of and capacity building in developing countries An annex on statistical considerations is under development A special MC issue of Food Control will be published in 2014

6 Practical examples Example 1: A GHP-based approach, prepared by EU(lead), Benin, Cameroon, Ghana and Panama; Example 2: Microbiological Criterion to Assess the Acceptability of a Food Lot, prepared by the USA (lead), Argentina, Thailand and Uruguay; Example 3a: Microbiological Criterion for verifying the performance of a HACCP system by the FBO, prepared by: IDF (lead), Bolivia, Gambia, and Nigeria; Example 3b: Microbiological Criterion for verifying the performance of a food safety control system, prepared by New Zealand (lead), Costa Rica, Kenya, Kiribati and Samoa; Example 4: Risk-based Microbiological Criterion for food/pathogen with a high prevalent pathogen, prepared by Denmark (lead), Colombia, Costa Rica, Senegal and ALA. Example 5a: Operationalising a Performance Objective with a Microbiological Criterion for a Risk- Based Approach, prepared by Canada (lead), Brazil, France, India and ICMSF; Example 5b: Operationalising a Performance Objective with a Microbiological Criterion for a Risk-Based Approach, prepared by the USA (lead), Brazil and Thailand.

7

8 Comparison of Table of Contents between 1997 and 2013 Table of Contents in 1997 Table of Contents in 2013 Introduction. 1. Introduction 1. Definition of Microbiological criterion. 2. Scope and Definitions 2. Components of Microbiological 2.1 Scope criteria for foods 2.2 Definitions 3. Purposes and application of 3. General Principles Microbiological criteria for foods 4. Establishment and Application of MC Application by regulatory 4.1 General considerations authorities. 4.2 Purpose Application by a food business 4.3 Relationship between MC and other operator. Microbiological Risk Management Metrics and 4. General considerations concerning ALOP Principles for establishing and applying 4.4 Components and other considerations microbiological criteria 4.5 Sampling Plan 5. Microbiological aspects of criteria 4.6 Microbiological and/or other limits 5.1 Microorganisms, parasites and their 4.7 Analytical Methods toxins/metabolites of importance in a 4.8 Statistical Performance particular food 4.9 Moving Window 5.2 Microbiological methods 4.10 Trend Analysis 5.3 Microbiological limits 4.11 Actions to be taken when the MC is not met 6. Sampling plans Methods and handling 4.12 Documentation and Record Keeping 7. Reporting 5. Review of Microbiological Criteria for Foods

9 Some improved features of the new Better title Codex MC document From Principles for the Establishment and Application of Microbiological Criteria for Foods to Principles and Guidelines for the Establishment and Application of Microbiological Criteria related to Foods An definition for MC with broad scopes, and better refelection of the current use of MC Solid considerations on setting new MRM metrics-based MC however, not much in the way of how to do this General principles for the establishment and application of MC Broader and better defined purposes for applying MC A good description of the Moving windows approach

10 Changed definition of MC The old A microbiological criterion for food defines the acceptability of a product or a food lot, based on the absence or presence, or number of microorganisms including parasites, and/or quantity of their toxins/metabolites, per unit(s) of mass, volume, area or lot The new A microbiological criterion is a risk management metric, which indicates the acceptability of a food, or the performance of either a process or a food safety control system following the outcome of sampling and testing for microorganisms at a specified point of the food chain

11 NEW in Codex MC doc: General Principles (1) 1) A MC should be appropriate to protect the health of the consumer and where appropriate, also ensure fair practices in food trade. 2) A MC should be practical and feasible and established only when necessary. 3) The purpose of establishing and applying a MC should be clearly articulated. 4) The establishment of MC should be based on scientific information and analysis and follow a structured and transparent approach.

12 NEW in Codex: General Principles (2) 5) MC should be established based on knowledge of the microorganisms and their occurrence and behavior along the food chain. 6) The intended as well as the actual use of the final product by consumers needs to be considered when setting a MC. 7) The required stringency of a MC used should be appropriate to its intended purpose. 8) Periodic reviews of MC should be conducted, as appropriate, in order to ensure that MC continue to be relevant to the stated purpose under current conditions and practices.

13 NEW in Codex: Five purposes of MC There may be multiple reasons for establishing and applying MC. The purposes of MC include, but are not limited to, the following: i) Evaluating a specific lot of food to determine its acceptance or rejection, in particular if its history is unknown. ii) Verifying the performance of a food safety control system or its elements along the food chain, e.g. prerequisite programs and/or HACCP systems. iii) Verifying the microbiological status of foods in relation to acceptance criteria specified between food business operators. iv) Verifying that the selected control measures are meeting POs and/or FSOs. v) Providing information to food business operators on microbiological levels, which should be achieved when applying best practices.

14 Towards a risk-based approach The risk-based angle is being used increasingly in the Codex Committee on Food Hygiene : there must be a link between the level of hazard in a food, and the risk for the consumer therefore, it should be possible to translate a level of protection (eg. an ALOP) to a MC Ongoing efforts to reduce the complexity of risk assessment may facilitate the development of true risk-based MC

15 MRM Metrics Framework FSO: The maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the appropriate level of protection (ALOP). PO: The maximum frequency and/or concentration of a hazard in a food at a specified step in the food chain before the time of consumption that provides or contributes to an FSO or ALOP, as applicable. Food Consumed

16 Relationship between MC, ALOP and other MRM Metrics (1) MC may be used by competent authorities and Food Business Operators, to operationalise the ALOP either directly or through other microbiological risk management metrics (e.g., PO, FSO). This requires the use of quantitative risk assessment. The risk estimation (itself based on source attribution studies) should include a combination of factors such as: the prevalence and concentration distribution of target microorganisms, as well as any changes in these after the step for which the MC has been set The risk assessment should include a characterization of the variability inherent to the food production system and express the uncertainty in the risk estimate

17 Relationship between MC, ALOP and other MRM Metrics (2) An MC can be linked directly to the ALOP, without explicit articulation of an FSO or a PO. This has been done in some countries with regard to Campylobacter in broilers. One approach involves testing the acceptability of individual lots and evaluating the acceptable relative risk to public health of the lot as compared to the ALOP the Danish example (and the new Dutch strategy?) Another approach is to link an MC directly to an ALOP using a risk assessment model to estimate the reduction in public health risk as a result of applying corrective actions to lots/processes that don't conform with the MC the New Zealand example

18 Example on Campylobacter in poultry Human ALOP Meal/RTE FSO RR = 0.271N *N >1000 Food Chain MC MC 20 meat /skin samples per food lot MC defined by critical value of RR (e.g. RR>10) Presented by WG leader, Dr. Jens Kirk Andersen at 44 th CCFH pwg

19 Deriving an MC from a PO that is set as an actual limit to the number of a microorganism PO established at a specific point in the value chain (i.e., pathogen level of 4 log cfu/g for 99.5% of the products in the batch) 1 2 Establish/decide on the concentration distribution in batch/lot and the standard deviation of the pathogen concentration (i.e., lognormal; s.d. 0.8 log cfu/g) Calculate a mean log concentration of the pathogen such that this batch/lot just complies with the PO (i.e., 1.94 log cfu/g) 3 Decide on the microbiological limit m for the sampling plan of the MC (i.e., m = 2 log cfu/g) 5 Decide on the probability with which a noncompliant batch/lot should be rejected (i.e., > 95% confidence) MC: suitable sampling plan parameters m and n (i.e., m = 2 log cfu/g and n = 5) 4 6 Calculate what the probability is for n samples to be negative for a just compliant batch/lot (i.e., n = 1, 53% up to n= 8, 0.6%) From this follows how many samples would be needed to achieve the selected probability of rejection (i.e., n = 5) Presented by WG leader, Dr. Jeff Farber at 44 th CCFH pwg

20 NEW in Codex: Approaches When considering the establishment of MC, a variety of approaches can be used depending on the risk management objectives and the available level of knowledge and data. These approaches can range from developing microbiological criteria based on empirical knowledge related to GHPs, to using scientific knowledge of food safety control systems such as through HACCP, or by conducting a risk assessment. The choice of the approach should be aligned with the risk management objectives and decisions relating to food safety and suitability.

21 Microbiological and/or other limits separate conforming from non-conforming analytical units two-class attributes sampling plan, one upper microbiological limit on the acceptable concentration in the analytical unit, denoted by m, the acceptance number c (often zero) is the maximum tolerable number of analytical units above the limit. three-class attributes sampling plan the microbiological limit m separates conforming from marginally acceptable, a limit M defines non-conforming analytical units. the acceptance number c refers to the maximum allowable number of marginally acceptable analytical units.

22 Example: 2 and 3 class sampling plan Where n = number of samples that must conform to the criteria: c = the maximum allowable number of defective sample units in a 2-class plan or marginally acceptable sample units in a 3-class plan: m = a microbiological limit which, in a 2-class plan, separates good quality from defective quality or, in a 3-class plan, separates good quality from marginally acceptable quality: M = a microbiological limit which, in a 3- class plan, separates marginally acceptable quality from defective quality CODE OF HYGIENIC PRACTICE FOR POWDERED FORMULAE FOR INFANTS AND YOUNG CHILDREN (CAC/RCP )

23 4.7 Analytical methods Depending on the microbiological limit (e.g. presence/absence of a specific foodborne pathogen), an appropriate analytical method should be selected. The methods used should be fit for purpose, meaning the method has been validated for relevant performance characteristics (e.g. limit of detection, repeatability, reproducibility, inclusivity, exclusivity). The validation study should be based on internationally accepted protocols and include an interlaboratory study. If not available, a validation should be done by the laboratory applying the method, according to a standardised protocol. The analytical methods specified should be reasonable with regard to complexity, availability of media, equipment, ease of interpretation, time required and costs. The results of testing may be impacted by compositing (i.e. pooling) of sample units prior to analysis. Compositing will affect the final concentration in the tested sample and is not appropriate for enumeration methods of analysis or within three-class sampling plans. Compositing may be considered in the case of presence/absence testing within a two-class sampling plan, as long as it is ensured that the result of testing will not be affected when compared to testing of individual analytical units

24 4.8 Statistical performance The statistical performance of a sampling plan is usually illustrated by its operating characteristic (OC) curve, which describes the probability of acceptance as a function of the actual proportion of non-conforming analytical units or concentration of the microorganisms in the food. An OC curve can be used to evaluate the influence of individual parameters of the sampling plan on the overall performance of the plan.

25 Probability of Acceptance Probability of Acceptance by Proportion D ef ectiv e 1.0 n=5, c= Probability of lot rejection P(rejection) =1-P(acceptance) = 1-(1-0.2)^5 = Probability of lot acceptance P(acceptance) = (1-0.2)^5 = Proportion Defective Dr. S. Dahms スライドより

26 Probability of Acceptance Probability of Acceptance by Proportion D ef ectiv e n=1, c=0 n=5, c=0 n=10, c=0 n=20, c= ロッ 0.2 トとしての合 0.0 格率 ロットの中で不良品の占める率 Proportion Defective Dr. S. Dahms スライドより改変

27 NEW in Codex: Moving Windows (1) In a moving window approach a sufficient number of sample units (n) is collected for a defined period of time (the window ). The results of the latest n sample units are compared with the microbiological limits (m, M) using the acceptance number c. As a new result from the sampling period is available, it is added to the window while the oldest result is removed, creating the moving window. This approach can also be applied to a set of results, e.g. results obtained during a week. The window, always consisting of n results, moves one result or set of results forward in time.

28 Moving window 2 The moving window approach is a practical and cost beneficial way of checking continuous microbiological performance of a process or a food safety control system. The moving window determines the acceptability of the performance so that appropriate interventions can be made in case of unacceptable shifts in control. The length of the moving window should be appropriate to enable corrective action to be taken in a timely manner. If more than c out of n results is above the limit m, or the limit M is exceeded, then corrective action is required. The moving window approach is a specific application of trend analysis used in process control that employs the addition of a decision rule to determine when the process can be considered to be out of control.

29 Moving Window The Simplest attribute sampling plans

30 Sampling plan Moving window: A specified number of units taken at a specified frequency over a specified time period Individual or pooled Systematic (routine) Defined by n + frequency Factors impacting frequency considerations: Number of processing lines Production frequency Distribution of the target organism in the food Probability of detection

31 Moving Window : An example of sampling plan 3 samples to be taken each processing day 5 processing days = 15 samples = 1 processing period 3 processing periods = window So: n = 45 samples in window m = limit of 3.78 log 10 colony forming units/carcass (90th percentile of target distribution curve) c = 6 (max. number of results that can be above m) Example presented by WG leader, Ms Judi Lee from NZ MPI

32 Interpretation of results Moving Window n= 45 samples in window m = 3.78 log10 cfu/carcass c = 6 (max. number that can be above m)

33 Example Moving Window 2 c = 6

34 Example Moving Window 3 c = 6 Action!

35 WINDOW Test results m M N=5, c=2 Example presented by IDF at pwg in Palma

36 WINDOW Test results m M

37 WINDOW Test results m M

38 WINDOW Test results m M

39 WINDOW Test results m M

40 WINDOW Test results m M

41 4.10 Trend Analysis Trend analysis is a procedure to detect a change in the patterns of observations over a period of time (usually over a relatively long period of time, often not predefined). It can be applied to many types of information including results of microbiological testing against a microbiological criterion. Trend analysis can detect a gradual loss of control that might not be detected by a moving window approach, as well as a more sudden loss of control. Trend analysis may show changes or patterns in the data that are a result of unwanted changes in the manufacturing process enabling the food business operator to take corrective actions before the food safety control system is out of control. The trends (or patterns) can be visualized, e.g. by displaying the test results graphically.

42 Trend analysis A procedure to look for systematic or emerging patterns or trends over a long period In control Out of control (operation) Max level Test results Out of control (trend) Out of control (system design) Max level Test results Max level Test results Max level Test results

43 Example of the trend analysis Meat hygiene assessment, 2 nd edition, Commonwealth of Australia, 2002

44 Different Roles Codex Alimentarius has a role in recommending MC at the international level. National governments may choose to adopt Codex MC into their national systems or use them as a starting point for addressing their intended public health goals. National governments also may establish and apply their own MC. Food business operators may establish and apply MC within the context of their food safety control systems.

45 Conclusions The effective implementation of control measures offers more advantages than sole reliance on microbiological testing through acceptance sampling of individual lots of the final product to be placed on the market. However, the establishment of MC may be appropriate for verifying that food safety control systems or parts of them are implemented correctly.

46 Further work: Annexes on statistical and mathematical matters 44 th CCFH recalled the recommendation of the working group, held in Grange, Ireland (July 2011), to develop an Annex on statistical and mathematical considerations for the elaboration of MC to request FAO and WHO to assist in the development of the Annex. The CCFH considered that the Annex was still necessary and agreed to request FAO and WHO assistance with the following terms of reference: Address the statistical and mathematical considerations related to establishing the performance characteristics of a sampling plan, including: How to develop and interpret operating characteristics curves; The impact of assumptions about the distribution and standard deviation of microorganisms in a food; How to establish the length of a moving window; and Any other relevant aspects