The Univeristy of Melbourne The Royal Melbourne Hopspital

A joint venture between The University of Melbourne and The Royal Melbourne Hospital


20 Sep 2021

What is modelling?

Modelling is a process in which real-life or hypothetical situations or scenarios are translated into mathematical language.  This is done by first identifying a problem (for example, a disease outbreak) and asking a question (for example, how might certain restrictions change how the disease spreads?). The team then collects different types of data from different sources to inform their model, including statistical data, mobility data and demographic data. The modellers consult experts to gather more nuanced information about the problem. Modellers then identify the best type of model to use that will help them answer the questions they have asked. The modellers look at different scenarios based on the data they have collected, and the advice they have received on the problem.

These situations are analysed using well-defined rules and are guided by particular objectives. The model will produce outputs, which can then be analysed, adjusted and interpreted. Ultimately, models construct a theoretical representation of real-world situations. 

There are different types of models which range in complexity. The type of model used will vary depending on the objectives and purpose of the study, the amount and quality of data available, and what is understood about the epidemiology of the disease.

Although the Doherty-led consortium focuses on epidemiological modelling and modelling of infectious diseases, modelling in general has a wide variety of applications across many different sectors, including finance, policy making, engineering, economics and technology.  

How does modelling inform public health interventions?

Simulations and models are used to provide insights into infectious disease trends, quantify likely benefits of public health interventions and risks associated with certain actions or behaviours, and support risk assessment for emerging infectious diseases. It provides a deeper understanding of certain situations, and allows people to develop preparedness plans to mitigate negative impacts of disease outbreaks, and to respond quickly and effectively when outbreaks occur.

Ultimately, modelling helps to develop a scientific understanding of certain real-life or hypothetical situations, observe the effect of changes in these situations, and aid decision making. It can be utilised across a wide range of situations and can provide critical information about infectious disease trends.

How has modelling been used during the COVID-19 pandemic?

Modelling has been used extensively to support decision making in Australia (and worldwide!) relating to the COVID-19 pandemic. Although researchers also model other infectious disease outbreaks, COVID-19 has been a central focus over the past 2 years as many of the models produced by epidemiological modellers have helped to inform decision- and policy-making when the situation was changing rapidly.

You can read more about how mathematical modelling gave researchers an early warning about the spread of COVID-19, how it was used to assess inform testing and response strategies for COVID-19 outbreaks in remote communities and how social media data allowed researchers to measure the impact of physical distancing measures on population movement during COVID-19 restrictions using mathematical models.

Does modelling predict the future?

Although they may not definitively predict the future, models can make predictions about certain outcomes in situations and scenarios. These outcomes may be affected by certain factors, such as time, population size, demographics, movement, season and more. The more information modellers have about a certain situation, the more accurate their model outputs or predictions will be. Models can use both qualitative and quantitative elements to strengthen the model.

Modellers work hard to ensure the outputs they produce have validity and accuracy, however there is always variability and randomness in real-life situations, which is important to understand when interpreting or analysing a model – situations can change quickly, and unexpected events can occur, which means that although models are powerful tools, they should be seen as a support to decision making, rather than a decision maker in and of themselvesitself.   

Who are the researchers that use these models?

Different researchers use different types of models based on their expertise. Modellers work across different fields, with different professional experiences, specialisations and skills. Mathematical and epidemiological modellers work in public health, computer science, government departments, clinical medicine, epidemiology, project management and economics at universities and institutions in Australia and within our region. The diversity within the Doherty-led modelling consortium allows the researchers to have innovative discussions around modelling.