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Issue #81: The second Nobel year in the time of COVID-19: Modelling complexity

01 Nov 2021

Issue #81: The second Nobel year in the time of COVID-19: Modelling complexity

By Nobel Laureate Professor Peter Doherty

Continuing on from last week (#80), how does the 2021 Nobel Physics award for climate systems science have any special relevance to COVID-19? The answer is that it’s basically a prize for mathematical insights and strategies that facilitate the analysis of complex systems and enable the prediction of likely trends and consequences. Climate is massively complex, but so is normal human biology and, interfacing that with the need to deal with a foreign invader, a pathogen like SARS-CoV-2, takes us to an even higher level of complexity.

This may be the first Nobel for modelling, but the Royal Swedish Academy of Science (#80) where the physics prize was announced is also responsible for awarding another major science prize, the Crafoord (#75). Earlier in 1996, the year Rolf Zinkernagel and I received the Nobel Prize for Medicine, Australian Physicist Sir Robert May was awarded the Crafoord for his contributions to theoretical ecology. Trained at Sydney University in the Harry Messel era – older Australians may recall Messel asking, ‘Why is it so?’ on ABC radio – May switched from physics to ecology while at Princeton University and was long established as the Professor of Zoology at Oxford University (surely the first physicist in that role) at the time of his award.

A major intellect and enormously effective at getting things done, Bob May was later President of the British and Commonwealth Academy of Science (London’s Royal Society), then Chief Scientist for the British Government. His great skill as a researcher was to break complex issues down to simple questions that could be ‘interrogated’ with the tools of mathematics. When HIV/AIDS hit in the 1980’s, May and his colleagues, particularly Roy Anderson, used simple mathematical models, then computer simulation to analyse and predict virus spread, the type of strategy we’re familiar with from epidemiologists operating in this time of COVID.

Then the Oxford team also looked ‘inward’ to the infected patient and used ‘predator/prey’ type modelling strategies to simulate HIV progression and the evolution of mutational change, drug resistance, virulence and so forth. Prominent in this work was Austrian mathematician Martin Nowak. Martin, who is also fascinated by linguistics, is currently Professor of Mathematics and Biology at Harvard.

Located at St Jude Children’s Research Hospital in Memphis, we collaborated with Martin –  who was then at Princeton – on studies of influenza. But (unlike HIV) influenza virus does not normally persist and mutate sequentially in infected people, so the system was much less interesting. Continuing in that ‘analysing the disease within mode’, medical doctor, immunologist and Oxford-trained modeller Miles Davenport – he heads the Infection Analytics Program at the UNSW Kirby Institute – asked how falling serum antibody levels (as happens in any immune response) to the SARS-CoV-2 spike protein might increase the likelihood of ‘breakthrough’ infections with different virus variants. The validity of the Davenport group’s modelling, which began with observations from seven different vaccines and from convalescent patients, was soon confirmed in the ‘real world’ as the delta variant of SARS-CoV-2 spread rapidly within the heavily vaccinated Israeli community. Collaborating from the University of Melbourne and with colleagues at Monash, we’ve worked with Miles for many years on aspects of T cell-mediated immunity in influenza.

Now very familiar to the broader community as engaging TV ‘personalities’, the epidemiologists seek to describe and predict what could happen with COVID-19. Their conclusions may vary, depending in part on the weighting they assign to underlying ‘assumptions’. The ‘softest’ of those must surely relate to the vagaries of human behaviour! When it comes to the ‘Doherty Modelling’ that has received so much public attention this has, of course, nothing to do with me and refers to the team (which also involves colleagues from five other universities) led by our Director of Epidemiology, Jodie McVernon.

Jodie, a Monash medical graduate, trained first in paediatrics, then in public health and vaccinology. In her words, ‘models are sophisticated thought experiments’. If you reflect on that a little, clarity of focus at the outset is clearly of major importance. Having that capacity, along with the skill sets she acquired at Oxford University, then the UK Health Protection Agency in London, Jodie is very much in the Bob May lineage. Lord May of Oxford died in April 2020. He was a very special person and is greatly missed.

Like all scientists, epidemiologists emerge from varied backgrounds. University of Melbourne Professor of Mathematical Biology James McCaw trained, like Bob May, as a physicist and works across the University, the School of Population and Global Health and with us. A member of our Institute, infectious diseases physician and epidemiologist Katherine Gibney is part of the medical team caring for COVID patients at The Royal Melbourne Hospital. A graduate of the two-year US CDC training course in epidemiology, Katherine has also been engaged on the COVID-19 public health front.

In contemporary biomedicine, the skill sets of the caring physician, the ‘dry lab’ computational biologist working ‘in silico’, or the ‘wet lab’ bench scientist processing biological samples from infected patients can come together as varying mixes, both within individuals and in research programs. At the cutting edge, biomedical research is a complex and demanding game played by people with unique combinations of talent and training. Best of all, neither the game – interrogating and being instructed by nature – nor the key players, are predictable or boring.

Setting it Straight by Laureate Professor Peter Doherty Archive