The data science of COVID-19 vaccination

To kickstart the first webinar of 2021 for the the Data Science in the News series, we explored the data science of COVID-19 vaccination. There is a Q&A session at the end for the audience to post questions to the panellists.


The recording of this panel session is now available

Panel Discussion – The Data Science of COVID-19 Vaccination, March 2021




  • Distinguished Professor Kerrie Mengersen – Director, QUT Centre for Data Science



  • Dr Kirsty Short – Research Fellow, Head of Viral Parthenogenesis Lab, The University of Queensland Data Science in the News: COVID19 and vaccines
  • Professor Raja Jurdak – Professor of Distributed Systems and Chair in Applied Data Science, Queensland University of Technology
  • Associate Professor Dan Nicolau – Australian Research Council Future Fellow, Queensland University of Technology
  • Dr Adrianne Jenner – Lecturer in Mathematical Oncology, Queensland University of Technology.


More about the Panel Session Topics:

Dr Kirsty Short: COVID-19: A year later


Professor Raja Jurdak: COVID-19 vaccination strategies and importation risks

This talk will discuss our recent work on COVID-19 place-based vaccination strategies and importation risk. Because vaccine supplies are limited, efficient use of available vaccines to minimise COVID-19 spread is critical. I will describe our placed-based vaccination strategy that prioritises individuals visiting the busiest locations for vaccination, which can maximise reductions in spread. I will also cover our recent work on understanding COVID-19 importation risk into Australia from overseas based on incoming travel patterns.


Dr Adrianne Jenner: What modelling the immune response to SARS-CoV-2 infections can tell us about COVID-19

After infection with SARS-CoV-2, the primary distinction between whether asymptomatic, mild or severe COVID-19 disease will develop depends on an individual’s immune response; however, understanding exactly what variation in the immune system drives the diversity of disease outcomes across the human population is challenging. Fortunately, as the disease has evolved in real-time, so has the human-based data available for scientists to leverage and build an understanding of this disease. For the past year, we have been undertaking a bilateral approach to investigate what happens inside the human body after SARS-CoV-2 infection by considering the immune response at the lung tissue level and the systemic level (whole body response) using mathematical and computational modelling. Leveraging the abundance of available of data, we have extrapolated a population of virtual patients for which we have identified biomarkers that drive the severity in COVID-19. Using these mathematical and computational models, we hope to now investigate how vaccine pressure may result in mutant strains and predict how an individual’s immune response to the vaccine may vary, given the already varied responses to SARS-CoV-2 infections, and what this could mean for vaccine success.


More about the Moderator and Panellists:

Dr Kirsty Short is an ARC DECRA Research Fellow and Head of the viral pathogenesis lab at the University of Queensland with extensive experience in emerging viral pathogens and pandemic preparedness. Dr Short is working on SARS-CoV-2 and in particular the role of children in disease spread, the impact of this disease on people with diabetes and the development of new antiviral therapies.


Professor Raja Jurdak is a Professor of Distributed Systems and Chair in Applied Data Sciences at Queensland University of Technology, where is Director of the Trusted Networks Lab. His work on the Disease Networks and Mobility (DiNeMo) Project explores how human infectious disease found overseas might spread in Australia and overseas due to the movement of people, and how this spread can be predicted. His main research interest is around dynamic network modelling. Networks and network science provide powerful representation of physical and logical relationships to gain insights into a broad range of systems, from communication and cyber-physical systems and Internet of Things to individual and entity relationship networks and interactions to guide value-creating decisions.


Associate Professor Dan Nicolau is a QUT mathematician, physician and an Australian Research Council Future Fellow. He and his team are collaborating with colleagues at the University of Oxford on a UK clinical trial to test common asthma inhalers as a treatment for COVID-19 infection.


Dr Adrianne Jenner research focuses on the applications of mathematical modelling in medicine. This includes the use of deterministic and stochastic modelling to answer important questions in medicine. For the most part, her research has been in developing mathematical models, closely calibrated to data, that help to understand cancer formation and treatment. This includes (but is not limited to) oncolytic virotherapy and immunotherapy. More recently, she has been involved in developing systemic and tissue level models of the immune response to SARS-CoV-2 with the goal of understanding the distinction between severe and mild disease responses


Professor Kerrie Mengersen is the Director of the QUT Centre for Data Science, Fellow of the Queensland Academy of Arts and Sciences, and Deputy Director of the ARC Centre of Excellence for Mathematical and Statistical Frontiers. She is acknowledged to be one of the leading researchers in her discipline. She uses and develops new statistical and computational methods that can help to solve complex problems in the real work. She works with a diverse range of people doing outstanding things in many different areas, and making the best use of data to make better decisions


This webinar series is brought to you by the QUT Centre for Data Science and the Queensland Academy of Arts and Science.


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