Unit Overview

Description

This unit provides a practical, computational, and statistically grounded introduction to modern infectious disease modelling, with a strong emphasis on solving real?world problems in research and policy.

The unit centres on building, fitting, and evaluating models that can handle the complexities of real data and noisy observation processes. Through extensive hands?on sessions, students will design and implement a range of model classes. These may include deterministic and stochastic compartmental models, individual?based models, and geostatistical models.

Students will learn and apply state?of?the?art computational statistical techniques for inference and prediction with mechanistic models in this domain. This may include application of MCMC, particle filtering, approximate Bayesian computation (ABC), amortized inference and approximate Gaussian Process methods.

By the end of the course, participants will be equipped to develop and critically assess modelling approaches suitable for contemporary infectious disease research, public?health decision?making, and policy evaluation.

Credit
6 points
Offering
AvailabilityLocationModeFirst year of offer
Not available in 2026UWA (Perth)On-campus
Outcomes

Students are able to (1) demostrate an understanding of infectious disease modelling; (2) apply computational statistical techniques for inference and prediction with mechanistic models in infectious disease modelling; (3) develop statistical modelling, and adapt known solutions to different situations; and (4) present results in a logical and coherent fashion and communicate effectively with others.

Assessment

Indicative assessments in this unit are as follows: (1) assignments and (2) final exam. Further information is available in the unit outline.



Student may be offered supplementary assessment in this unit if they meet the eligibility criteria.

Unit Coordinator(s)
Professor Nick Golding
Unit rules
Prerequisites
Enrolment in
60610 Master of Statistics
or Successful completion of
STAT2062 Fundamentals of Probability with Applications
or STAT2063 Probabilistic Methods and their Applications
or STAT2403 Regression Models for Data Science
or ( STAT2401 Analysis of Experiments
and STAT2402 Analysis of Observations
)
Contact hours
3-hours per week
  • The availability of units in Semester 1, 2, etc. was correct at the time of publication but may be subject to change.
  • All students are responsible for identifying when they need assistance to improve their academic learning, research, English language and numeracy skills; seeking out the services and resources available to help them; and applying what they learn. Students are encouraged to register for free online support through GETSmart; to help themselves to the extensive range of resources on UWA's STUDYSmarter website; and to participate in WRITESmart and (ma+hs)Smart drop-ins and workshops.
  • Visit the Essential Textbooks website to see if any textbooks are required for this Unit. The website is updated regularly so content may change. Students are recommended to purchase Essential Textbooks, but a limited number of copies of all Essential Textbooks are held in the Library in print, and as an ebook where possible. Recommended readings for the unit can be accessed in Unit Readings directly through the Learning Management System (LMS).
  • Contact hours provide an indication of the type and extent of in-class activities this unit may contain. The total amount of student work (including contact hours, assessment time, and self-study) will approximate 150 hours per 6 credit points.