Speak to an Expert
If you are looking to ground an important decision in robust analysis and evidence, let’s start the conversation.
This online course introduces risk analysis and quantitative risk modeling for food safety and animal health, with applications to broader health issues like optimizing testing and vaccination strategies. Using R, an open-source statistical software, you will engage in practical exercises, live sessions with PhD-level instructors, and self-paced lectures.
EpiX Analytics is an international leader in risk analysis and its instructors provide real-life context to theory based on decades of research and consulting experience in the fields of animal health, food safety, and health risk analysis using a One Health approach. 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:
Choose “select a course” to enroll in either “full class with introduction to R” or “module II only”.
Registration discounts available for early bird (before April 5, 2025), students, government employees and groups from the same organization.
Early bird discount is automatically applied at the checkout before April 5th. All other discounts will require a coupon code, contact us for more information. Discounts cannot be combined.
Full class with introduction to R – USD $2000.00
Module II only – USD $1590.00
Module I: Introduction to R for risk modeling (this module is not included if you select Module II only when registering)
– 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
Anyone interested in quantitative risk analysis in health. The course is focused on animal health and food safety but is applicable to various risk analysis problems, including testing and surveillance programs.
No formal prerequisites, but some prior understanding is beneficial.
Duration:
– Module I: 1 week, with asynchronous lectures and optional office hours.
– Module II: 2 weeks, featuring six live lectures and over 40 asynchronous lectures (5-15 minutes each).
Time Commitment: 2-3 hours per day.
Certification Requirements:
Attendance at live lectures (or viewing recordings) and review of all core materials.
Software Required:
– RStudio (freeware at [RStudio Download](https://posit.co/download/rstudio-desktop/))
– A modern internet browser (Google Chrome or Microsoft Edge RS2 or newer recommended)
Access:
Course materials available during and for four weeks after the course. Module II includes six recorded live sessions available for asynchronous viewing. Live sessions are held 8-9am US Mountain Daylight Time (UTC/GMT -6 hours).
Office Hours:
Optional one-on-one sessions with instructors.
If you are looking to ground an important decision in robust analysis and evidence, let’s start the conversation.
