Predictive modelling is a rapidly developing area in public health. Already widely applied in predictive studies of interventions such as vaccination, modelling is a key input to policy and planning decisions in public health. Understanding how trends in disease will unfold in future years helps policymakers evaluate and prepare for future priorities. The focus in this course is on building predictive models of disease trends in excel and on assessing the value of modelling results for policy.

This course is an elective course of the Master of Public Health, Master of Global Health, Master of Health Leadership and Management and Master of Infectious Diseases Intelligence programs, comprising 6 units of credit towards the total required for completion of the study program. It is also a designated methods course as part of the Master of Public Health Specialisation in Infectious Diseases Epidemiology and Control.

Mode of study

Face-to-face classes on-campus for Internal students & fully online for Distance External students

Key contact

A/Prof James Wood
Course Convenor
+61 (2) 9385 8769

Who should do this course?

This course has no required pre-requisites but does rely on reasonable quantitative skills and familiarity with Microsoft Excel. If you have any concerns in relation to your suitability for the course, please contact the course convenor (A/Prof Wood) by email or phone.

Course outcomes

This course aims to provide students with skills in applying predictive models to disease risks in public health and in developing their understanding of the benefits and limitations of predictive modelling in this context. Skills include the ability to:

  • discuss and explain the value of modelling approaches in policy formulation and planning for disease prevention and control
  • assess the suitability of a modelling approach to address policy questions in relation to disease prevention and control
  • design, implement and critique single-cohort models for demographic and disease risk projections in Excel
  • extend single-cohort models to whole of population models for projecting disease incidence through time.

Learning & teaching

This course focuses on developing your understanding, practical skills and critical thinking in relationship to predictive modelling in the context of public health. While lectures and course notes are an important component of the course, there is also an emphasis on skill development in terms of building and analysing models through structured tutorials and assessment. Finally, critical thinking in terms of the role of modelling in informing policy is an important component and one that the course aims to develop through discussions of published papers. From a professional perspective, the course will help students strengthen their quantitative skills and gain confidence in assessing the role of modelling in public health interventions. This is relevant both to policy roles in which models might inform decision-making, and in more analytical roles where skills form the course could be applied in developing models.

The expectation is that you will work through the online course materials each week, supported through Moodle in terms of questions about lectures, tutorials and discussion items. This will be supported by live tutorial sessions and webinars as detailed later in this outline. The key course materials will be short video lectures and guest lectures, Excel-based tutorials and associated worksheets, course notes and readings. These will all be provided through the Moodle site. In addition, solutions to tutorial questions and screencast tutorial demonstrations will be posted at appropriate times during the course.


Assessment Task 1 – Technical report: Demographic models
Weighting: 20%
Length: 1000 words

Assessment Task 2 – Technical report: Disease risk models
Weighting: 30%
Length: 1500 words

Assessment Task 3 – Written report: Modelling case study
Weighting: 50%
Length: 2500 words

Readings & resources 

Learning resources for this course consist of the following, all available in Moodle:

  • course notes and readings
  • lecture slides
  • lecture recordings
  • Excel-based tutorial
  • supplementary resources such as video demonstrations.