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New Simon Fraser University research could help prepare for COVID-19 variants

By using a combination of math and gene mapping, researchers say it could help the healthcare system learn beforehand about the spread of new variants.
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Researchers at Simon Fraser University (SFU) say that gene data can be used to better prepare for virus subvariants.

Researchers at Simon Fraser University (SFU) say gene data can be used to better prepare for virus subvariants, like COVID-19.

Caroline Colijn, a researcher and professor at SFU, explains genes can be an indicator of when new variants of a virus spread.

“We could see that there were some variants that were rising even as total numbers were declining, and that meant we could predict that the Delta wave was coming, we could predict that the Alpha wave was coming,” she explained.

The group says by looking at a virus’s genes, it can help predict when the virus will mutate.

By using a combination of math and gene mapping, researchers say it could help the healthcare system learn beforehand about the spread of new variants.

“Genomic sequencing technologies have improved to the point where it is possible to consistently sample over time to understand how pathogens mutate and evolve to produce new variants or strains,” SFU said in a release.

“It has become more feasible to integrate genomic data from viruses and other pathogens into predictive mathematical models that forecast the spread of an infection,” it goes on to say.

Colijn explains that by using gene forecasting, it could help identify the severity of different virus strains, allowing researchers to prepare in advance.

“We use genomic data to understand how the diversity of the bacteria is proceeding through time and in particular how vaccination, which targets some types of the bacteria, how that targeting of some types will leave a population,” she added.

She also notes that it could also lead to faster vaccine development, and help improve many aspects of virus prevention.

“We might have a better idea of what strains to look out for, what strains will become the worst stains after we’ve removed the currently worst strains with vaccination,” she said.

The group is advocating the use of their data in the healthcare system, to better prepare for virus subvariants.

“We should be building methods, models, and tools to incorporate that sequence data into how we make projections, and how we think about what might the future burden of disease be,” she explained.

Colijn says although gene data is already collected across Canada, using it for forecasting is fairly new.

But the outcome could impact the number of healthcare workers and vaccine stocks an area needs.

Colijn says researchers should build tools to better incorporate this data, noting some universities in B.C. already have data that could be used.

Her team notes that gene forecasting can also provide more insight into how viruses avoid our immune system.

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