Infectious Disease Modelling: Applied Methods in R



Overview

Infectious disease modelling is a growing field and can provide valuable insights into the spread and control of infectious diseases.

By fitting models of disease transmission and recovery to data, we can evaluate potential interventions and scenarios through fixed metrics, such as the basic reproduction number (or R number), or by comparing forward predictions using the outcomes of stochastic simulations.

This course provides an introduction to implementing and summarising models of infectious disease in the statistical programming language R, with a particular focus on modelling for policy and the importance of communicating uncertainty. 

No previous experience with modelling or using R is required. 

This course combines online study with a weekly 1-hour live webinar led by your tutor. Find out more about how our short online courses are taught.

Programme details

This course begins on the 15 Apr 2026 which is when course materials are made available to students. Students should study these materials in advance of the first live meeting which will be held on 22 Apr 2026, 3:00-4:00pm (UK time).

Week 1: Introduction

  • Installing R and RStudio
  • Using tidyverse
  • Vectors, matrices and data frames
  • Writing functions

Week 2: Analysing epidemic data

  • Summarising trends
  • Visualising data using ggplot2
  • Estimating the growth rate and reproduction number, R

Week 3: Epidemic models

  • Building a transmission model
  • The SI model
  • The SIR model

Week 4: Solving models in R

  • Using deSolve
  • The SI model
  • The SIR model

Week 5: Stochastic simulations

  • Stochastic vs. deterministic
  • Distribution functions in R
  • Simulating an epidemic

Week 6: Communicating uncertainty

  • Summarising simulation results
  • Plotting uncertainty

Week 7: Modelling interventions

  • Vaccination
  • Mass treatment
  • Social distancing
  • Comparing interventions

Week 8: Individual-based modelling

  • Individual-based SIR model
  • Modelling an epidemic on a square lattice

Week 9: Fitting to data

  • Fitting methods in R
  • Fitting vs. testing
  • Making predictions

Week 10: Interfacing science and policy

  • Transparency and reproducibility in science
  • Communicating assumptions and uncertainty
  • Examples from the COVID-19 pandemic

Certification

Credit Application Transfer Scheme (CATS) points 

Coursework is an integral part of all online courses and everyone enrolled will be expected to do coursework. All those enrolled on an online courses are registered for credit and will be awarded CATS points for completing work at the required standard.

See more information on CATS points

Digital credentials

All students who pass their final assignment will be eligible for a digital Certificate of Completion. Upon successful completion, you will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate or share it on social media if you choose to do so. 

Please note that assignments are not graded but are marked either pass or fail. 

Fees

Description Costs
Course Fee £360.00

Funding

If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. Please see the below link for full details:

Concessionary fees for short courses

Course aims

The course provides a foundation in R programming for infectious disease modelling.

Course Objectives:

  • Students will use the R language to construct and analyse models of infectious disease transmission.
  • Students will build and run model simulations and forecast population-level disease outcomes.

Teaching methods

Learning takes place on a weekly schedule. At the start of each weekly unit, students are provided with learning materials on our online platform, including one hour of pre-recorded video, often supplemented by guided readings and educational resources. These learning materials prepare students for a one-hour live webinar with an expert tutor at the end of each weekly unit which they attend in small groups. Webinars are held on Microsoft Teams, and provide the opportunity for students to respond to discussion prompts and ask questions. The blend of weekly learning materials that can be worked through flexibly, together with a live meeting with a tutor and their peers, maximise learning and engagement through interaction in a friendly, supportive environment.

Learning outcomes

By the end of the course students will be expected to:

  • be able to use R to solve, simulate, analyse and visualise basic models of infectious disease transmission;
  • understand the difference between mean-field and stochastic models;
  • have a basic understand of methods of fitting models to data;
  • be able to effectively communicate uncertainty in their results and understand how this uncertainty can impact policy decisions.

Assessment methods

You will be set independent formative and summative work for this course. Formative work will be submitted for informal assessment and feedback from your tutor, but has no impact on your final grade. The summative work will be formally assessed as pass or fail.

Application

Please use the 'Book' or 'Apply' button on this page. Alternatively, please complete an Enrolment form for short courses | Oxford University Department for Continuing Education

Level and demands

The Department's short online courses are taught at FHEQ Level 4, i.e. first year undergraduate level. FHEQ level 4 courses require approximately 10 hours study per week, therefore a total of about 100 study hours.

English Language Requirements

We do not insist that applicants hold an English language certification, but warn that they may be at a disadvantage if their language skills are not of a comparable level to those qualifications listed on our website. If you are confident in your proficiency, please feel free to enrol. For more information regarding English language requirements please follow this link: https://www.conted.ox.ac.uk/about/english-language-requirements

 

Terms & conditions for applicants and students

Information on financial support