Mathematical Modelling of Infectious Diseases

Lecturers

Associate Professor Roslyn Hickson, CSIRO and James Cook University

Synopsis

Infectious disease transmission is a nonlinear process with many subtleties and complications more sociological in nature (e.g. how people behave). Mathematical modelling of infectious disease transmission has substantial potential real world application, as highlighted by the recent COVID-19 pandemic.

This course explores key topics in infectious disease modelling, including the development of appropriate models, parameterisation from data using Bayesian Inference, and using models as a “what-if” scenario tool or as a tool to increase understanding of fundamental epidemiological processes. We will start with quite simple mathematical models that yield important insights to disease dynamics and control, and build to more complex models that better reflect complicated infectious disease dynamics. The focus will be on simulation of these models, as opposed to analytical analysis.

Course Overview

  • What is modelling? Introduction to epidemiology
  • Compartmental modelling
  • Parameterisation of models: What to do with data?
  • Controlling infectious diseases, including a case study
  • Spatial models
  • Introduction to agent-based approaches

Prerequisites

  • Systems of differential equations
    • Need to be able to solve dP/dt = b P(t)
    • Understanding how to get from a problem description to a differential equation
      will be helpful.
    • Understanding stability of equilibria will be helpful.
  • Basic probability
    • Understanding Bayes’ theorem/rule is an advantage.
  • Programming (at least basic)
    • Python will be used extensively throughout the course, so familiarity with the basics of Python will be advantageous.
  • No prior biological or epidemiological knowledge is expected.

Assessment

  • 2 assignments (20% each)
  • Final exam (40%)
  • Computer lab worksheets (20% in total)

(Assessment subject to change)

Resources/pre-reading (if available)

Lecture notes will be provided during the course that complement the following book by Keeling and Rohani

  • We will work a lot from Modelling Infectious Diseases: In animals and humans, by Keeling and Rohani. They also have a website with example code.
  • Optionally: The Handbook of Infectious Disease Data Analysis, by By Leonhard Held, Niel Hens, Philip D O’Neill, Jacco Wallinga.

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Associate Professor Roslyn Hickson
CSIRO and James Cook University

A/Prof Roslyn Hickson joined CSIRO and James Cook University as Science Leader for Emerging Infectious Diseases in June 2020. Her research is on mathematical modelling of infectious diseases to informing policy and practice.

Roslyn completed her PhD through UNSW Canberra in 2010, where her research on heat and mass transfer was awarded the Ria de Groot prize. Roslyn became a Research Fellow at the National Centre for Epidemiology and Population Health, ANU. In December 2011 she was awarded a four year University of Newcastle Research Fellowship. Roslyn joined IBM Research Australia in May 2014, during which she was named a finalist for the EmTech Asia Innovators Under 35 list by MIT Technology Review in 2016 and 2017. Roslyn joined The University of Melbourne as an Australian Centre of Research Excellence in Malaria Elimination Research Fellow in July 2018. She was awarded one of the Victorian Young Tall Poppies in 2018.