The science behind it: The Establishment-based Risk Assessment (ERA) model for food establishments

The risks to food have changed considerably in recent years and continue to change rapidly. At the same time, the Canadian industry has to be more efficient and innovative to compete in a global economy. It is in this context that the Canadian Food Inspection Agency (CFIA) began to evolve the way it manages risk, supports industry's ability to compete globally, and embraces technology to provide more efficient and responsive service.

The CFIA committed to better use data, reports and surveillance to identify trends, allowing the Agency to focus on risk and support program design, planning, compliance and enforcement efforts. As part of the Strategic Integrated Risk Management priority, the CFIA developed an Establishment-based Risk Assessment (ERA) model for food establishments in order to allocate inspection resources based on food safety risks. This risk assessment takes into consideration typical food safety hazards, and is being used to determine the level of oversight required to appropriately manage the risks. The ERA model has been developed by CFIA staff in collaboration with experts from academia, industry and other government departments. The development of the model also drew upon the experience of other countries that have used a similar approach to risk assessment, and considered scientific literature and leading edge modelling technology.

The ERA model has three different groups of risk factors: inherent risk factors, mitigation factors and compliance factors. Data for the first two components are collected through My CFIA, by completing the "Additional Establishment Information". Regulated parties are prompted to provide the additional establishment information after the SFC license is granted and when the license is amended or renewed, or at any other time. Data on compliance factors are extracted from CFIA databases.

After a cycle of data collection and analysis by the ERA model, the risk results will provide input into the Agency's risk-based approach to manage food safety risks, including the prioritization of inspection, oversight strategies and priorities, laboratory capacity mobilization, and work planning. The ultimate objective of this initiative is to produce a near real time risk assessment for individual food establishments that will assist the Agency within its overall integrated risk management strategy.

The scientific approach and practical applications to develop the ERA model since 2013 are presented below. Annex 1 presents the Scientific Advisory Committee members and the ERA technical working group.

Scientific approach and practical applications

Identification of factors associated with food safety risk

The objective was to assess the importance and significance of 155 risk factors identified in the literature that could potentially be used in a risk assessment model for food establishments. Expert selection was based on nomination by the CFIA scientific advisory committee (SAC). Overall, of the 126 Canadian experts that were invited, 75 participated (60%) by completing an electronic questionnaire in June and July 2013. A scale from 1 to 10 was used to score the 155 risk factors, 1 having the least impact on food safety and 10 having the highest impact. Experts attributed a high score to most risk factors. One risk factor ("management commitment") received a median score of 10, while median scores of 9, 8 to 8.5, and below 8 were attributed to 42, 77 and 35 of the risk factors listed, respectively. Overall, 51 risk factors were excluded based on this study. The findings of this expert elicitation are available in Microbial Risk Analysis Journal.

Selection of risk factors for the ERA model

For a quantitative risk assessment model, a limited number of risk factors are needed. Thus, other criteria were considered to select risk factors such as the clarity of their definition, the merging of risk factors sharing similar concepts, the inclusion of only measurable risk factors (for example the probability that this factor can be objectively assessed during an audit process), and the availability of data sources. The final list of risk factors is presented in Figure 1 and the process followed for the selection is available in Food Microbiology Journal. Briefly, risk factors are grouped in inherent risks factors, mitigation factors and compliance factors.

Inherent risk factors represent those associated with a specific food commodity, operation or manufacturing process. These factors take into account the type of product, volume, and its direct distribution to a vulnerable population, such as residents of nursing homes, hospitals or daycares.

Mitigation factors are the measures or strategies that a food establishment is using to reduce the inherent risk and therefore reduce the risk of a food safety issue. Examples of these strategies include the implementation of an internationally recognised private certification scheme (meaning recognised preventive control plan), having a full time employee responsible for quality assurance and food safety on site, and the application of specific risk-prevention processes (for example high pressure processing).

Compliance factors refer to a food establishment's track record with respect to how well it has complied with its own preventive control measures and with regulatory requirements. This is assessed using the food establishment's historical and current data such as information pertaining to recalls, inspection reports and enforcement actions.

Figure 1: List of risk factors included in the ERA model

Figure 1: List of risk factors included in the ERA model. Description follows.
Description for image – List of risk factors included in the ERA model

This figure depicts the final list of risk factors included in the ERA model. The first box represents the inherent risk factors which are those associated with a specific food commodity, operation or manufacturing process. Three factors, namely the commodity, the type of products, the volume and the type of activities are related to the health impact (unit in DALYs – Disability Adjusted life Years) attributed to these risk factors. The second box represents the mitigation factors which are the measures or strategies that a food establishment has implemented to control the inherent risks and reduce the overall risk of a food safety issue. The third box represents the compliance factors which refer to a food establishment's track record on how well it has complied with its own preventive control measures and with regulatory requirements. The list under the inspector assessment is the list of preventive control plan (PCP) sub-elements that the ERA model considers under the CFIA's integrated Agency Inspection Model (iAIM).

Risk factors' criteria weighting for the ERA model

The objective was to quantify the relative importance of selected criteria used to measure the risk factors included in the ERA model. The selection of experts was based on nomination by the SAC. Of the 50 experts that were invited, 29 participated (58%) in an expert elicitation. Experts were from academia (31%), industry (31%), and government (38%). Overall, 173 criteria were presented to experts during a two-round face-to-face expert elicitation to estimate their relative risk to human health. There was a good consensus on the relative risk given to most criteria. Respondent profile did not have a strong influence on the results. No expert expressed formal opposition to the inclusion of any criterion. Median values for each criterion are used in the ERA model. The peer-reviewed scientific paper is available in Food Control Journal.

Risk Attribution at the sub-product level

The objective was to estimate the contribution of different food sub-products to the level of human illness in the Canadian population. A web-based questionnaire was used to determine the attribution of sources for the main food safety pathogens in selected commodities. The selection of experts was based on nomination by the SAC and the technical committee. Then, a snowball approach was used to nominate other experts. Overall, 119 experts were invited to complete the expert elicitation questionnaire and 64 did so. The source attribution at the sub-product level for 31 pathogen-commodity combinations was investigated. For each pathogen-commodity combination, experts were also asked to provide their level of certainty on a scale from 1 to 10 (1 being less confident and 10 being the most confident). Experts were offered two versions of the questionnaire, depending on their choice. The first version grouped questions based on the type of pathogen, while the second version grouped questions based on the type of commodity. A Food Safety Hazards Background document was also provided to experts before completing the survey. For most of the pathogen-commodity combinations, respondent profiles did not have a significant influence on the source attribution at the sub-product level. Since experts provided different levels of certainty for each pathogen-commodity combination, a weighted average was used to calculate the source attribution. The peer-reviewed scientific paper is available in International Journal of Food Microbiology.

Design of the ERA model algorithm

The ERA model concept is based on the allocation of risks to food establishments based on their impact on consumer health in Canada. The underlying principle is that the total impact (expressed as DALYs) remains constant, but the proportion allocated to individual establishments is fluid. This value takes into consideration the number of cases associated with each food safety hazard yearly, their attribution to specific food commodities and sub-products, and the health impact per case of illness for each hazard. Thus, the health impact is first allocated to individual establishments based on the volume of each product type they manufacture. The establishment-level health impact is then adjusted considering the presence or absence of specific food safety risk factors and their relative risks (Figure 2). A scientific paper on the ERA algorithm is currently being prepared for submission to a peer-reviewed journal.

Figure 2: ERA model arrow illustration

Figure 2: ERA model arrow illustration. Description follows.
Description for image – ERA model arrow illustration

This figure illustrates the model design as an arrow. First, the initial DALYs are calculated by attributing the health impact to four factors: type of activity, commodity, type of products and volume. Then, the health impact is adjusted by the inherent risk factors, the mitigation factors, and the compliance factors represented by the first, second and third boxes, respectively. This then generates the health impact at the establishment level represented by the last box.

Testing of the model (Pilot projects)

The objectives of the commodity-specific pilot projects were to obtain risk results and to validate the data collection tool. Food establishments were randomly selected.

Commodity Number of participating establishments out of the total number of establishments randomly selected Completion date
Dairy 29/29 June 2014
Meat/poultry 49/52 June 2014
Fish/seafood 49/52 February 2017
Maple 31/32 September 2017
Honey 30/32 October 2017
Eggs and egg products 28/32 April 2018
Fruits and vegetables Upcoming 2019

As a result of the pilot project data analysis, as well as feedback from establishments and inspectors, a simplified, improved and automated version of the data collection tool was developed, and is now available through My CFIA, by completing the "Additional Establishment Information".

Performance assessment of the ERA model outputs

The objectives of this step were to estimate the agreement between the risk assessments provided by the ERA model and CFIA senior inspectors, and to refine the model based on the identification of major discrepancies.

For each establishment that participated in the commodity-specific pilot project, information related to the risk factors used as inputs in the ERA model was summarized in one page. Each expert categorized 10 establishments for their risk to the health of consumers, including 8 randomly selected establishments from the commodity-specific pilot project and 2 controls: one with the lowest risk and one with the highest risk. The controls were created by the ERA technical committee.

Commodity Number of participating CFIA senior inspectors Outcome
Dairy 22 A good correlation was achieved between the ERA model and inspectors' assessment. Minor refinements were done in the algorithm.
Meat/poultry 39
Fish/seafood 31 Discrepancies were identified and triggered a reassessment of the categorization of fish sub-products.
Maple 23 Inspectors did not consider the production volume as significantly impacting the risk result of an establishment. When fixing this variable, the correlations were excellent. As the volume is used as a measure of exposure assessment by the model, no adjustment will be done to ERA for these commodities.
Honey 21
Eggs and egg products 24 A very good correlation was achieved between the ERA model and inspector assessment.
Fruits and vegetables Upcoming

National Data Collection

The ERA model is being implemented following a commodity by commodity approach through a national data collection phase. In order to collect information for the inherent, mitigation and compliance factors and assess the risk of all federally regulated food establishments, regulated parties are invited to fill out an online questionnaire (Additional Establishment Information) through My CFIA. After a cycle of data collection and analysis by the ERA model, the risk results are being used in inspection planning and are providing input into the Agency's risk-based approach to managing food safety risks.

The ERA technical team is currently adapting the ERA model for food importers (Importer Risk Assessment model). Furthermore, the same scientific approach was used to develop an Establishment-based Risk Assessment model for Hatcheries and is actually being used to develop an Establishment-based Risk Assessment model for Feed establishments. For more information, email cfia.eramodel-modeleere.acia@canada.ca.

Annex 1 – The Scientific Advisory Committee members and the ERA technical working group, as of June 2019

ERA Scientific Advisory Committee members
Name Affiliation
Sylvain Quessy Université de Montréal
Julie Arsenault Université de Montréal
Mansel Griffiths University of Guelph
Art Hill University of Guelph
Jeffrey Farber University of Guelph
Sylvain Charlebois Dalhousie University
Tom Gill Dalhousie University
Rick Holley University of Manitoba
Aamir Fazil Public Health Agency of Canada
Greg Paoli Risk Sciences International
Anna Mackay Canadian Food Inspection Agency
ERA technical working group
Name Affiliation
Manon Racicot Canadian Food Inspection Agency
Romina Zanabria Canadian Food Inspection Agency
Alexandre Leroux Canadian Food Inspection Agency
Geneviève Comeau Canadian Food Inspection Agency
Raphaël Plante Canadian Food Inspection Agency
Suzanne Savoie Canadian Food Inspection Agency
Mohamed Rhouma Canadian Food Inspection Agency
Haoran Shi Canadian Food Inspection Agency
France Provost Canadian Food Inspection Agency
Virginie Lachapelle Canadian Food Inspection Agency
Elisabeth Mantil Canadian Food Inspection Agency
Brent Waite Canadian Food Inspection Agency

Additional resources

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