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Mathematical Modelling

Mathematical modelling plays an increasingly important role in cancer control by helping to identify the most impactful and cost-effective ways to reduce the burden of cancer at a population level. Integrated with epidemiological research, analysis of large-scale health datasets, and evidence reviews, modelling is a powerful tool to inform health policy, programs and practice.

Key areas of focus include in this stream include:

Developing and enhancing Policy1 platforms

Policy1 is a powerful, flexible modelling platform that can be used to evaluate the effectiveness, cost-effectiveness, costs and harms of alternative cancer control strategies. The platform uses a world-leading disease modelling approach, and incorporates information about multiple aspects of cancer and risk behaviour, including:

  • the ‘natural history’ of different cancers i.e., the course a disease takes in individual people from its onset until its detection, and eventual resolution to recovery or death
  • prevention strategies, including vaccination and lifestyle interventions
  • individual risk factors and screening behaviours
  • cancer treatment type and uptake
  • variation in different subgroups of the population.

In addition to existing, mature models, Policy1-Cervix and Policy1-Bowel, the team is building six modelling platforms: Policy1-Prostate, Policy1-Melanoma, Policy1-Ovary, Policy-Lung, Policy1-Breast and Policy1-Lynch

Modelling the impact of COVID-19 on cancer

As key contributors to the COVID-19 and Cancer Global Modelling Consortium the team is developing new models to support decision-making in cancer control both during the pandemic and in recovery. The work includes three key themes of work: impact of COVID-19 infections and cancer treatment delays on cancer outcomes and healthcare systems; the impact on cancer screening and recovery strategies; and the impact on long-term cancer risk and recovery prevention strategies.

Research Team

Dr Michael Caruana

Associate Professor Michael Caruana

Stream lead, Mathematical Modelling

Dr Renan Almeida

Research Fellow

Associate Professor Michael Caruana

Stream lead, Mathematical Modelling

Dr Yue He

Postdoctoral Modelling Analyst

Harriet Hui

Project Coordinator

Dr Kirstie McLoughlin

Research Fellow

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