Queensland COVID-19 research

This page of Queensland’s research related to the COVID-19 pandemic is compiled from information provided by Queensland universities and research institutes.

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• Modelling COVID-19 in Queensland August 2021

  The strong second wave of COVID-19 in Melbourne and widespread outbreaks in Sydney show that Australia's COVID-19 response is in a critical phase. Clusters are likely to continue to appear until a vaccine is deployed, and even then there is uncertainty around vaccine efficacies, rollout times, and new variants. Various public health interventions are effective at reducing the spread of COVID-19, but for any given outbreak it is unknown what strategies optimally balance health and economic/societal impacts. This optimisation requires accurate predictions of the potential spread of COVID-19 in a location-specific manner, and predictions of the effects of various interventions (e.g. testing, contact tracing, mask use, physical distancing, vaccines). In partnership with COVID-19 modelling experts and using local demographic data from Queensland Health, we will use agent-based modelling to simulate COVID-19 outbreaks for the Queensland setting. We will test and optimise potential interventions, enabling rational informed decision making. This project is one of several projects enabled by a $5 million funding injection, in 2020, from the Queensland Government.

  #Modelling

  Centre

  QIMR Berghofer Medical Research Institute

  Contact details

  A/Prof James Roberts
  Team Head
  james.roberts@qimrberghofer.edu.au
  +61 7 3845 3850

  Collaborations

  • Collaborators:
  • Paula Sanz-Leon, QIMR Berghofer
  • Nathan Stevenson, QIMR Berghofer
  • Cliff Kerr, Institute for Disease Modeling, Seattle
  • Romesh Abeysuriya, Burnet Institute, Melbourne
  • Robyn Stuart, University of Copenhagen

• Recovery ratios reliably anticipate COVID-19 pandemic progression April 2020

  COVID-19 has infected millions and killed hundreds of thousands of people worldwide, but a new predictor model devised at QUT offers glimmers of hope, suggesting the worst has passed and indicating well under 1000 deaths for Australia. The team at QUT, led by physician, mathematician and Future Fellow Dan Nicolau, has developed what they believe to be a more accurate model to predict the trajectory of the virus and its mortality, based on reliable, country-independent data. The predictions, updated daily, are available at covidwave.org and look at the ratio of known infections to recoveries in each country. The team then compared this ratio with the number of reported daily deaths in each country. This country-by-country breakdown also gives a big picture view, which shows that the world is currently in the middle of a second global wave of COVID-19, likely to last for some weeks. Remarkably, the data pattern is the same for most countries, including Australia.

  #Modelling

  Centre

  Science and Engineering Faculty, School of Mathematical Sciences
  Queensland University of Technology

  Contact details

  A/Prof Dan Nicolau
  Future Fellow, Science and Engineering Faculty
  dan.nicolau@qut.edu.au
  +61 7 3138 5238

  Collaborations

  University of Oxford

• Atomistic simulation of the interaction between the spike protein of COVID-19 virus and the human angiotensin-converting enzyme 2 May 2020

  The strong binding of a protein (S-protein) on the surface of the COVID-19 virus to part of an enzyme (ACE2) in human cells present in the lungs (and arteries, heart, kidney, and intestines) leads to severe respiratory infection. Understanding of the interaction of this protein with this enzyme is essential for the drug/vaccine discovery for COVID-19. Based on recent cryo-electron microscopy (cryo-EM) experiments, this project proposes to simulate the interface between the virus and human cells at the atomic level. The expected outcomes include the optimised atomic structures of the interface, identification of the driving force for binding, and developed principles for blocking the binding of the virus to human cells. Such information will be used to screen the molecule candidates with fusion inhibiting the potential for the development of drugs and vaccines for COVID-19.

  #Modelling

  Centre

  Environmental Futures Research Institute
  Griffith University

  Contact details

  Doctor Yun Wang
  Senior Lecturer
  yun.wang@griffith.edu.au
  +61 7 5552 8358

  Collaborations

  • Prof Ronald Quinn
  • Dr. Alexandre S Cristino