Upcoming Training

Modeling Food Safety and Animal Health Risks Using R - (Online) 

Duration: 2-3 weeks, online

Date: TBD, May, 2024

Time per day: 2-3 hours

Capacity: Minimum of 10 and maximum of 35 attendees

Cost: Full class: US$2,000, module II only: US$1,590 (see Course Content below)

This course is suitable to anyone interested in the foundational concepts of quantitative risk analysis in health. Although the course content and exercises focus on animal health and food safety, the course material is applicable to risk analysis problems of all types. For example, the course content covering the use of diagnostic tests to establish disease freedom and understand individual risks is directly applicable to modeling COVID-19 testing and surveillance strategies in occupational settings.

This online course provides an introduction to risk analysis and quantitative risk modeling for food safety and animal health, which are also applicable to a variety of health risk analysis problems such as the analysis and optimization of COVID testing and vaccination strategies. Exercises and problems will demonstrate core risk analysis functionality and applied food safety and animal health models in R, an open-source statistical programming platform. The class combines live sessions delivered by experienced, PhD-level instructors with self-paced lectures and practical problems to solve. Each topic will include a mixture of lectures, supporting reading material, demonstration of software implementation, and practice problems to solve. EpiX Analytics is an international leader in risk analysis and its instructors provide real-life context to theory based on decades of consulting and research experience in the fields of animal health, food safety, and health risk analysis. Case studies based on a variety of previous projects will be presented and discussed to illustrate the combination of various concepts introduced in the course.

The class is divided into two modules:

  • Module I is an optional introduction to R. It is designed for participants who have never used R, or for beginner R users.
  • Module II contains the core material for the class. Users with reasonable familiarity using R can decide to register to this module only.


  • Module I: Taught over one week period, with only asynchronous lectures to allow students to learn at their own pace using the course’s online resources and access to one-on-one office hours.
  • Module II: Taught over a two-week period, with seven live lectures lasting one hour, and over 40 asynchronous lectures 5-15 minutes in length.
  • Time per day: 2-3 hours
  • Requirements to receive a certificate of completion: Attendance at live lectures (or viewing of live lectures recordings) and review of all core course materials

Software required:
– R (freeware available at https://cran.r-project.org/https://cran.r-project.org/) and RStudio (freeware at https://rstudio.com/products/rstudio/download/https://rstudio.com/products/rstudio/download/)
– A modern internet browser compatible with Atlassian Confluence and Microsoft Teams (if not using Teams’ desktop application). We recommend Google Chrome or Microsoft Edge RS2 or newer. Safari is not fully compatible with Teams online.

Course participants will have access to all course materials during the class, and also four weeks after ending the class. For module II, 6 live sessions will also be recorded for asynchronous viewing, and will be held 8-9am US Mountain Daylight Time (UTC/GMT – 6 hours). Live session schedule (dates tbc):

  • Module I, no live session during the first week of class
  • Module II, introduction to the course and instructors, plus a motivating case study
  • Introduction to risk analysis, statistics, and simulation in R
  • The Binomial Process
  • The Poisson Processes / Aggregate models
  • Using data in models and fitting distributions
  • Course wrap-up and optional material
  • Office hours: participants are encouraged to schedule one to one office hours with our class instructors.

Module I: Introduction to R for risk modeling
– The R console, R studio, and other interfaces
– Basic R syntax, summary statistics
– Essential plots and data visualization
– Data objects and their manipulation
– Control flow, loops, logical statements
– Vectorized calculations
– Using packages

Module II: Modeling Food Safety and Animal Health Risks Using R
– Introduction to Risk Analysis
– Fundamentals of Statistics for Risk Analysis: probabilities, visualization, most useful probability distributions
– Communicating Results of a Risk Analysis: plots, statistics, sensitivity analysis
– Risk Analysis in R: probability calculations and efficient simulation, outputs
– Stochastic Processes: Binomial, Poisson, aggregate modeling
– Fitting Distributions: sourcing data, assessing fit
– Using Expert Opinion: modeling techniques (optional)
– Correlations: copulas and more (optional)
– Modeling parameter uncertainty: classical, bootstrap and Bayesian methods (optional)
– Dose Response Modeling: chemical and microbial (optional)
– Real-life case studies, including a step-by-step instructional on performing a quantitative risk assessment

If you register and pay 30 days before the course start date, an early registration discount of 5% is applied automatically at checkout.

Please contact us to obtain a code for the discounts below. Please note that discount rates cannot be combined.

* Government/Academic – 5% off registration (Proof of eligibility requested after registration)
* Student – 15% off registration (Proof of eligibility requested after registration)
* Groups of 3 or more people – please contact us for a special discount
Use our contact form if you have any questions, or if you are interested in a course not currently in our schedule.


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