Food Safety

Microbiological risk assessment: the Risk Ranger tool

June 28, 2025

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Microbiological risk assessment is essential for safeguarding food safety and public health, with over 600 million people affected by foodborne illnesses each year. This article explores the Risk Ranger tool, a semi-quantitative risk assessment model, highlighting its advantages as demonstrated in a pivotal study by Bevilacqua et al. (2023).

Unlike traditional theoretical models, Risk Ranger offers practical, data-driven insights grounded in the Microbiological Risk Assessment (MRA) framework established by FAO/WHO guidelines and endorsed by the FAO.

This semi-quantitative tool combines scientific rigour with real-world applicability by quantifying the effects of food processing and population vulnerability within the broader matrix of risk analysis. As such, it stands out as a valuable asset for strengthening food safety management strategies across diverse production contexts.

From hazard identification to risk analysis

The global burden of foodborne diseases continues to pose significant challenges to public health systems worldwide, with the World Health Organization (WHO) reporting staggering statistics that underscore the urgency of effective risk management strategies (Bevilacqua et al., 2023). The complexity of modern food supply chains necessitates sophisticated approaches to hazard identification and risk quantification, moving beyond traditional qualitative assessments towards more robust, evidence-based methodologies.

The distinction between ‘hazard’ and ‘risk’ forms the cornerstone of contemporary food safety science — including in cases of cross-contamination involving food allergens (Dongo, 2022) — whereas:

hazard represents ‘a biological, chemical, or physical agent in, or condition of, food, with the potential to cause an adverse health effect‘, while
risk constitutes ‘a probabilistic function of an adverse health effect and the severity of that effect‘ (Official Controls Regulation EU 2017/625).

The evolution from HACCP (Hazard Analysis Critical Control Point) systems to comprehensive risk analysis methodologies reflects the food industry’s progression towards more holistic food safety management approaches. While HACCP remains fundamental for identifying critical control points, its qualitative nature limits its capacity to address global-level hazard control and risk reduction strategies. This limitation has driven the development of sophisticated risk assessment tools that integrate mathematical modelling, epidemiological data, and probabilistic analysis to provide quantitative risk estimates.

EFSA’s approach to risk ranking

The European Food Safety Authority’s Panel on Biological Hazards (BIOHAZ) has developed a comprehensive framework for evaluating risk ranking tools in food safety assessment. In their 2015 Scientific Opinion, eight tools relevant to risk ranking of biological hazards in food were identified and assessed using two case studies (EFSA BIOHAZ Panel, 2015). The EFSA evaluation revealed significant differences in tool performance related to:

risk metrics. The specific measures used to quantify risk;
data requirements. Ranging from minimal qualitative inputs to extensive quantitative datasets;
ranking approach. Ordinal scoring – assignment of values to qualitative or semi-quantitative variables (e.g. low, medium, high), ordered according to a criterion of severity or probability – versus probabilistic modelling;
model type. Deterministic versus stochastic approaches;
model variables. The factors considered in risk calculation;
data integration. Methods for combining different types of information.

Stochastic approaches in food safety risk assessment use probability distributions to model uncertainty and variability in factors such as contamination levels, exposure, and consumer behaviour. This allows for more realistic and informative risk estimates compared to deterministic method.

The EFSA panel concluded that stochastic quantitative models represent the most reliable approach for risk classification, provided that input parameters are adequately characterised. The BIOHAZ panel indeed observed that ordinal scoring approaches, typical of semi-quantitative models, tend to produce classifications more prone to error compared to deterministic models, which, however, by neglecting variability, can also lead to errors in risk estimation.

Importantly, FDA-iRISK was identified as the most appropriate tool for risk ranking of microbiological hazards, with the Burden of Communicable Diseases in Europe (BCoDE) toolkit recommended for use in combination with FDA-iRISK outputs or as a top-down tool to rank pathogens (EFSA BIOHAZ Panel, 2015).

FDA’s quantitative approach: FDA-iRISK

FDA-iRISK was developed by the US Food and Drug Administration (FDA) as a comprehensive web-based quantitative risk assessment system to address the need for evidence-based, transparent, and rigorous approaches to estimate and compare the risk of foodborne illness from microbial and chemical hazards and the public health impact of interventions (Chen et al., 2013). This sophisticated tool represents the pinnacle of quantitative risk assessment capabilities, incorporating what follows.

Key features

Monte Carlo simulation techniques. Based on random sampling, they allow for the simulation of variability and uncertainty in complex systems. In the context of food safety, they enable risk estimation by modelling realistic scenarios using probability distributions rather than fixed values;
a comprehensive framework that enables users to assess, compare, and classify the risks associated with specific food-hazard combinations across all stages of the food supply chain — from primary production, through processing and manufacturing, to retail distribution and final consumption;
intervention analysis enables the estimation and comparison of the impact of control measures on public health risk;
burden of disease metrics incorporate Disability-Adjusted Life Years (DALYs) to quantify the overall health impact.

Data requirements

The tool requires extensive inputs across seven components, as detailed by Chen et al. (2013):

food characteristics;
hazard properties;
population demographics;
process models (farm-to-fork pathways);
consumption patterns;
dose-response relationships;
health burden measures.

FDA-iRISK is designed to be a highly accessible tool that allows risk assessors to construct, evaluate, and compare hazard/food scenarios that may involve multiple hazards (both microbiological and chemical), foods, process pathways, and populations (FDA, 2023). The tool’s strength lies in its ability to provide probabilistic outputs that account for variability and uncertainty, though this sophistication comes at the cost of extensive data requirements and technical expertise.

Methodology

Study design and approach

Bevilacqua and colleagues (2023) employed a multi-faceted methodological approach combining literature review, comparative analysis, and practical case studies to evaluate risk assessment tools. The research methodology encompassed three primary components:

comprehensive background analysis of risk assessment principles;
comparative evaluation of eight risk ranking tools identified by the EFSA BIOHAZ Panel; and
empirical application of Risk Ranger through three distinct food-pathogen combinations.

Risk assessment framework

The study adopted the four-phase Microbiological Risk Assessment (MRA) framework established by FAO/WHO guidelines (MRA 36), comprising:

Hazard identification. Systematic identification of pathogens capable of surviving in target foods and causing adverse health effects. This phase incorporated analysis of food matrix properties (composition, intrinsic and extrinsic factors), technological history, and pathogen physiology;
Hazard characterisation. Qualitative and quantitative evaluation of pathogen severity, considering disease nature (fever, diarrhoea, neural complications), infectious dose, disease pathways, host susceptibility, and epidemiological data;
Exposure assessment. Determination of pathogen or toxin levels in food at consumption, accounting for contamination pathways, processing impacts, and consumption patterns;
Risk characterisation. Integration of previous phases to produce qualitative and/or quantitative risk evaluations through algorithms and modelling tools.

Risk Ranger methodology

The Risk Ranger tool, developed by the University of Tasmania, employs a semi-quantitative approach requiring assessors to answer eleven questions grouped into three categories, as outlined below.

Susceptibility and severity

hazard severity (severe, moderate, mild, or minor);
population susceptibility (general to specific vulnerable groups).

Probability of exposure

frequency of consumption (daily to yearly variations);
proportion of consuming population (% ranges);
size of consuming population (numerical input).

Probability of infectious dose

raw product contamination probability (0.01% to 100%);
processing effects on hazard levels;
post-processing recontamination potential;
post-processing control effectiveness;
contamination level increases;
preparation effects before consumption.

The tool converts qualitative responses into numerical values using proprietary algorithms, generating four key outputs:

risk ranking (0-100 scale);
probability of illness per consumer per day;
total predicted illnesses per annum;
comparative risk in the population.

Case study implementation

Three pathogen-food combinations were analysed by Bevilacqua and colleagues (2023), using consistent parameters based on Italian population data (60 million) and international consumption patterns:

Listeria monocytogenes in ready-to-use lettuce;
Escherichia coli in chicken salad;
Staphylococcus aureus in fresh egg pasta.

Additional comparative analysis examined multiple pathogens (Campylobacter spp., E. coli O157:H7, Salmonella sp.) in chicken salad to demonstrate the tool’s capacity for comparative risk assessment.

Practical implementation of Risk Ranger

Step-by-step implementation guide

The practical implementation of Risk Ranger follows a systematic approach that food safety professionals can readily apply in industrial settings. Based on FAO guidance, Risk Ranger helps to focus the attention of users on the interplay of factors that contribute to foodborne disease and can be used to explore the effect of different risk-reduction strategies (FAO, 2023).

Initial preparation

Access the tool via via FAO website.
Assemble the risk assessment team, including quality assurance personnel, production managers, and food safety specialists.
Gather baseline data on pathogen prevalence, processing conditions, and consumption patterns.

Systematic data entry

Question 1-2. Evaluate hazard severity and population susceptibility:

consider medical intervention requirements;
identify vulnerable groups (YOPI – young, old, pregnant, immunocompromised).

Question 3-5. Assess exposure probability:

document consumption frequency patterns;
estimate population coverage percentages;
input accurate population size data.

Question 6-11. Determine infectious dose probability:

evaluate contamination rates in raw materials;
assess processing efficacy (log reductions achieved);
consider post-processing contamination risks;
evaluate control system effectiveness.

Interpretation of outputs

The ‘Risk Ranking’ value is a simplified measure of relative risk using a logarithmic scale between 0 and 100, where 100 represents the theoretical worst scenario where every member of the population eats a meal containing a lethal dose daily (Food Safety Portal, 2023):

risk ranking 0-30. Low risk → routine monitoring sufficient;
risk ranking 31-60. Moderate risk → enhanced controls recommended;
risk ranking 61-100. High risk → immediate intervention required.

Scenario analysis

The tool enables ‘what-if’ scenarios to evaluate intervention strategies:

modify processing parameters to assess impact on risk reduction;
evaluate different population groups to identify vulnerable segments;
compare multiple pathogen-food combinations for prioritisation.

Integration with existing food safety systems

Risk Ranger complements existing food safety frameworks, rather than replacing them:

HACCP integration. Risk Ranger outputs can be used to validate CCP selection and critical limits;
ISO 22000 alignment. Risk rankings can be included into operational Pre-Requisite Programmes (oPRPs);
regulatory compliance. Risk assessment documents can support audit trails and regulatory submissions;
food safety management (writer’s note). A comprehensive, evidence-based semi-quantitative risk analysis may provide a solid basis for food safety management decisions.

Common implementation challenges and solutions

Data uncertainty → solutions:

use conservative estimates and document assumptions;
conduct sensitivity analysis by varying uncertain parameters.

Subjectivity in qualitative inputs → solutions:

solution → establish standard operating procedures for answer selection (within food safety management procedures, writer’s note);
use expert panels (also with the support of external experts, writer’s note) to reach consensus on ambiguous questions.

Result interpretation → solutions:

develop internal guidelines linking risk rankings to specific actions (i.e. the basis of a robust food safety management procedures, writer’s note);
create visual dashboards for management communication (and also, to share risk analysis with the competent authorities, in case of food safety incidents, writer’s note).

Results and discussion

Risk ranking outcomes

The application of Risk Ranger in the Bevilacqua et al. (2023) study yielded distinct risk rankings that reflected the complex interplay between pathogen characteristics, food properties, and processing conditions. Listeria monocytogenes in lettuce achieved the highest risk ranking of 59, indicating a significant risk level requiring immediate controlling measures. This elevated ranking stemmed from multiple factors: the pathogen’s psychrotrophic nature rendering refrigeration ineffective, the absence of thermal processing for ready-to-eat lettuce, and the vulnerability of specific population groups (YOPI – young, old, pregnant women, immunocompromised) to listeriosis.

Conversely, both E. coli in chicken salad and S. aureus in fresh egg pasta generated risk rankings of 40, suggesting moderate risk levels necessitating preventive measures. The lower rankings for these combinations reflected the mitigating effects of thermal processing during preparation, despite acknowledging that S. aureus enterotoxins remain thermostable. The probability of illness per consumer per day ranged from 2.50 × 10⁻⁶ for L. monocytogenes/lettuce to 4.27 × 10⁻⁷ for both E. coli/chicken salad and S. aureus/pasta combinations.

Comparative pathogen analysis

The extended analysis of chicken salad contamination revealed significant variations in risk profiles across different pathogens. Campylobacter spp. and E. coli O157:H7 both generated risk rankings of 52, whilst Salmonella sp. yielded a ranking of 40. The comparative risk values ranged from 3.21 × 10⁻⁹ to 3.21 × 10⁻¹¹, identifying Campylobacter spp. and E. coli O157:H7 as the limiting factors for chicken salad safety. These findings align with epidemiological data indicating higher hospitalisation rates and disease severity for these pathogens compared to typical Salmonella infections.

Tool comparison and evaluation

The comprehensive evaluation of risk assessment tools revealed distinct advantages and limitations across different approaches:

decision trees stood out for their simplicity and adaptability, albeit at the cost of marked subjectivity — which, in the view of the present author, may lead to divergent interpretations by external stakeholders, such as regulatory authorities — and their lack of comparability with quantitative methods;
FDA-iRisk provided sophisticated quantitative analysis incorporating Monte Carlo simulations and DALY calculations but required extensive data inputs and technical expertise beyond most food companies’ capabilities;
Risk Ranger emerged as the optimal compromise, offering meaningful quantitative outputs whilst maintaining accessibility for non-expert users. The tool’s traffic-light communication system (green, yellow, red) facilitates stakeholder understanding, whilst its statistical outputs enable evidence-based decision-making. However, limitations include the inability to assess uncertainty, the presence of mathematically impossible scenarios (0% and 100% risk), and restricted choice granularity in certain parameters.

Practical implications

The study’s findings have profound implications for food safety management in industrial settings:

Risk Ranger’s accessibility enables small and medium-sized food industries to conduct sophisticated risk assessments without extensive resources or specialised training;
the tool’s capacity to simulate various scenarios allows risk managers to evaluate the efficacy of different intervention strategies before implementation, optimising resource allocation and maximising food safety outcomes.

The case studies demonstrate how seemingly minor variations in processing conditions or pathogen characteristics can significantly impact risk levels, as follows:

the psychrotrophic nature of L. monocytogenes (i.e. its ability to grow at low temperatures) fundamentally alters the risk profile for refrigerated products, whilst
the thermostability of staphylococcal enterotoxins necessitates prevention-focused strategies rather than reliance on thermal processing.

Major outcomes

The research by Bevilacqua generated several significant outcomes with direct applications for food industry stakeholders:

Validation of semi-quantitative approaches. The study demonstrated that semi-quantitative tools like Risk Ranger can provide scientifically robust risk assessments whilst remaining accessible to non-specialist users, bridging the gap between academic research and industrial application;
Pathogen-specific risk profiles. The comparative analysis revealed pathogen-specific risk hierarchies, with L. monocytogenes presenting the highest risk in ready-to-eat products, whilst Campylobacter spp. and E. coli O157:H7 emerged as primary concerns for poultry products;
Processing impact quantification. The research quantified how different processing steps influence final risk levels, demonstrating that thermal processing typically reduces risk rankings by 19-32%, whilst post-processing contamination can increase risk by similar magnitudes;
Population-specific considerations. The study highlighted how population susceptibility factors can elevate risk rankings by 15-25%, emphasising the importance of considering vulnerable groups in risk assessment protocols;
Communication framework. The development of a clear risk communication framework using visual indicators and statistical outputs facilitates stakeholder engagement and regulatory compliance.

Conclusions

This comprehensive analysis by Bevilacqua et al. (2023) underscores the critical importance of systematic microbiological risk assessment in contemporary food safety management. The research conclusively demonstrates that Risk Ranger represents an optimal tool for food industry applications, balancing scientific rigour with practical accessibility. The semi-quantitative approach enables evidence-based decision-making whilst acknowledging the data limitations inherent in real-world food production environments.

The study’s findings indicate that effective risk management requires consideration of multiple interacting factors, including pathogen characteristics, food matrix properties, processing conditions, and population demographics. The case studies highlight that the interaction of these factors generates distinct risk profiles for each food-pathogen combination, making tailored intervention strategies necessary in place of generic solutions.

Future developments should focus on enhancing Risk Ranger’s capabilities through integration with predictive microbiology databases, expansion of parameter choices, and incorporation of uncertainty analysis. The tool’s potential as an educational platform for training food safety professionals remains largely untapped, presenting opportunities for academic-industry collaboration.

The systematic use of appropriate risk assessment tools can significantly reduce foodborne illnesses. In an increasingly complex global food system, accessible yet advanced tools like Risk Ranger will be essential for supporting sustainable food production and protecting public health.

Dario Dongo

References

Bevilacqua, A., De Santis, A., Sollazzo, G., Speranza, B., Racioppo, A., Sinigaglia, M., & Corbo, M. R. (2025). Microbiological risk assessment in foods: Background and tools, with a focus on Risk Ranger. Foods, 12(7), 1483. https://doi.org/10.3390/foods12071483
Chen, Y., Dennis, S. B., Hartnett, E., Paoli, G., Pouillot, R., Ruthman, T., & Wilson, M. (2013). FDA-iRISK—A comparative risk assessment system for evaluating and ranking food-hazard pairs: Case studies on microbial hazards. Journal of Food Protection, 76(3), 376-385. https://doi.org/10.4315/0362-028X.JFP-12-372
EFSA Panel on Biological Hazards (BIOHAZ). (2012). Scientific Opinion on the development of a risk ranking framework on biological hazards. EFSA Journal, 10(6), 2724. https://doi.org/10.2903/j.efsa.2012.2724
EFSA Panel on Biological Hazards (BIOHAZ). (2015). Scientific Opinion on the development of a risk ranking toolbox for the EFSA BIOHAZ Panel. EFSA Journal, 13(1), 3939. https://doi.org/10.2903/j.efsa.2015.3939
Food and Agriculture Organization of the United Nations (FAO). (n.d.). Risk Ranger. Food Safety Portal. https://foodsafetyportal.eu/riskranger/rr_riskranger.html
Food and Agriculture Organization (FAO). (2023). Risk Ranger: A simple food safety risk calculation tool. Retrieved from https://www.fao.org/food-safety/resources/tools/details/en/c/1191489/
Food Safety Portal. (2023). Risk Ranger tool. Retrieved from https://foodsafetyportal.eu/riskranger/rr_introduction.html
Regulation (EU) 2017/625 of the European Parliament and of the Council of 15 March 2017 on official controls and other official activities performed to ensure the application of food and feed law, rules on animal health and welfare, plant health and plant protection products. See Article 3 (Definitions), paragraph 1, points 23,24. Current consolidated version: 05/01/2025 http://data.europa.eu/eli/reg/2017/625/2025-01-05
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U.S. Food and Drug Administration (FDA). (2023). Risk analysis of food at FDA. Retrieved from https://www.fda.gov/food/risk-and-safety-assessments-food/risk-analysis-food-fda