Posted on Nov 18, 2020 in Astronomy, Biology, Pandemic, Science
Some of the greatest medical discoveries of the 20th century came from physicists who switched careers and became biologists. Francis Crick, who won the 1962 Nobel Prize in Physiology and helped identify the structure of DNA, started his career as a physicist, as did Leo Szilard who conceived the nuclear chain reaction in 1933, writing the letter for Albert Einstein’s signature that resulted in the Manhattan Project that built the atomic bomb, but spent the last decades of his life doing pioneering work in biology, including the first cloning of a human cell.
Today, a group of world-renowned researchers at the Perimeter Institute for Theoretical Physics with expertise from cosmology to quantum gravity are using physics to help fight the COVID-19 pandemic.
“People are Like Galaxies”
“People are kind of like galaxies. They are gravitated towards each other.”” said astrophysicist Niayesh Afshordi, who collaborated with fellow physicists and with researchers from the computational science giant Wolfram Research. Like astronomers researching dark matter by studying many different galaxies, reports Perimeter, the team analyzed the entire set of local COVID-19 epidemics in the United States. They included a broad selection of demographics, as well as population density, climate factors, and local mobility data in an attempt to discover what makes a difference to the disease spread, and what doesn’t. Afshordi has created a public dashboard aimed at making predictions on COVID-19 mortality rates changing based on external factors.
“I think there is a lot in common between epidemiology and cosmology,” Afshordi says. “In both, we have a large component of a mysterious and invisible ‘dark matter’ that surrounds us, and we can only infer its properties indirectly, via incomplete and biased tracers.”
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According to Perimeter, the team used statistical techniques from cosmology to build a model that can make predictions of how the COVID mortality rate might change in response to external factors. The model is now available as a public dashboard, and the team hopes communities can use it to develop good policies – and maybe even save lives.
“The math skills, the ways of thinking, the data analysis that people do in a different field, that has applications and that experience is useful,” said quantum physicist, Robert Myers, director of the institute.
Tracking Mutations
Data-oriented cosmologist Kendrick Smith, a world expert in developing mathematical techniques that extract fundamental physics from astronomical data, is bringing his skills to mutation tracking. Smith, who’s work is a mixture of theoretical physics, phenomenology, computational physics, statistics, and data analysis, holds the James Peebles Chair in Theoretical Physics. One of his most recent projects,” reports Perimeter, “was creating the software pipeline for the CHIME (Canadian Hydrogen Intensity Mapping Experiment) telescope to find fast radio bursts.” That skill set is a perfect match for sequencing the genome of the coronavirus, a computationally intensive process – not just because there’s a lot of data, but because the process involves “amplifying” the viral genome and reading it out in small pieces.
“Imagine there’s a whole book you want to read, and someone has made a million copies of a few hundred words, and from that you have to reassemble the story,” says Smith.
Smith is working with The McMaster-Sunnybrook Research Institute team who needed someone with someone with experience with big, messy scientific data sets. They turned to Perimeter, and Director Rob Myers pointed them to Smith, who volunteered his time and got the software pipeline running to study how the genomes of the viruses afflicting individual patients differ from each other – that is, studying the mutation of the novel coronavirus. Some mutations may spread more readily than others. Some may cause more serious disease. And knowing who has what strain can help track how the virus spreads.
“It’s a simplification to say there’s only one virus. There are hundreds of mutations,” Smith notes about the new software, SIGNAL, which is publicly available, and a landmark study comparing the viral genomes in 1,000 different patients is expected soon.
From the Big Bang to Batch Testing
Cosmologist Neil Turok is noted for innovating approaches to understanding the big bang and for his work in founding Perimeter’s sister institute, the African Institute for Mathematical Sciences (AIMS). Turok was a leader in replaced the concept of the “classical big bang” with a “quantum big bounce.” Working with Stephen Hawking, he discovered instanton solutions describing the birth of inflationary universes. His work on open inflation forms the basis of the multiverse paradigm. With Paul Steinhardt, he developed an alternative, cyclic model for cosmology, whose predictions are so far in agreement with all observational tests.
Along with colleagues from AIMS, Turok is working on group testing for coronavirus infections, using “batch testing” or “pool testing,” that by pools samples from lots of patients. In its most straightforward use, group testing can clear many people at once when the whole group sample tests negative.
Turok thought the idea could be pushed further, notes Perimeter. In the scheme he envisioned, works with geometry: when a group sample tests positive, samples from people in that group could be re-sorted and recombined in new ways, allowing testers to identify individual infected people. To develop this new yesting scheme, says Perimter, Turok is working with a multidisciplinary team that includes Wilfred Ndifon, a mathematical biologist who is the director of research at AIMS, and Leon Mutesa, a geneticist at the University of Rwanda and coordinator of that nation’s COVID response task force.
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Reaching for Higher Dimensions
“For physicists, it’s very natural to reach for higher dimensions,” says Turok. “In fact, I think we do it a little too much. But in this case, it gives us huge practical advantages.” This testing scheme, which can drastically reduce the number of tests needed to identify infected individuals, is being used in a trial at the University of Rwanda’s state-of-the-art Center for Human Genetics, where team member Mutesa is the director. The idea is even spreading outside of academia, Turok says. “The method is now being used to regularly test one of the top rugby teams in South Africa and is likely to catch on with others.”
Network Theory–How the Coronavirus Spreads
When the pandemic struck, postdoctoral researcher Mark Penney, working in mathematical physics put his work on topological quantum field theory aside, instead joining with mathematical biologists Chris Bauch, director of The Bauch Lab at Canada’s University of Waterloo and Madhur Anand of the University of Guelph to work on computational models of how the coronavirus spreads, based on insight from network theory. It’s a far-reaching and well-developed field, used to study everything from power grids to workflow patterns to predator-prey relationships. The network they’re looking at here is social. Penney explains: “We’re thinking of how the structure of the network of social contacts between people influences how disease is spread.”
It’s not an unusual way to model disease spread, but the team found a way to make the model more powerful by adding percolation theory –similar percolating coffee. “In a certain way,” says Penny, “an infectious disease spreading throughout a community also follows a percolation-like process. But rather than trying to get the water through the little gaps in the coffee grounds, it’s a virus passing through these social contacts. If you study percolation on a network instead of through a material, it’s the same as studying certain aspects of how infectious disease spreads.”
“If you can selectively target the more connected individuals, you can use fewer resources to achieve the same reduction in the spread of the disease,” notes Penney, about a model of how the coronavirus bubbles through our social networks that informs decisions on how best to distribute a limited number of tests or vaccines.
The COVID Alert App
There are obviously privacy concerns, Penny notes, but technologies like Canada’s COVID Alert app may offer a way to thread that needle, guiding medical policy decisions without compromising individual privacy pointing the way to a post-pandemic future. “Some ballparks, based on much more theoretical networks, suggest that with vaccination strategies enabled by COVID Alert you can achieve herd immunity with millions fewer vaccines.”
The Daily Galaxy, Max Goldberg, via Perimeter Institute
Image credit: Shutterstock License
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