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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.