Surges in COVID-19 cases last year coincided with the emergence of new SARS-CoV-2 variants, a new study has found.
Since its initial declaration as a pandemic in March 2020, SARS-CoV-2 has spread around the world, causing an estimated 129 million cases of COVID-19 and 2.8 million deaths, according to the Johns Hopkins University COVID-19 dashboard.
By studying SARS-CoV-2 samples from early in the pandemic, researchers from the University of California, Davis, developed a metric they dubbed the pathogen genome identity (GENI) score that measures viral genetic diversity. SARS-CoV-2 contains just 15 genes and has a high mutation rate, and variants of concern like B.1.351, B.1.1.7, and P.1 have emerged in recent months.
When the researchers analyzed their GENI score in conjunction with other, classic epidemiological measures, they found that the scores rose just before an exponential growth in cases in South Korea, a finding they replicated using data from the UK. This, they noted in a paper published in Scientific Reports on Thursday, suggests their tool could provide early warning to public health authorities to brace for an uptick in COVID-19 cases.
“As variants emerge, you’re going to get new outbreaks,” Bart Weimer, professor of population health and reproduction at the UC Davis School of Veterinary Medicine, said in a statement.
The approach could be used to forecast where cases might be on the rise and help officials make decisions about when to implement public health interventions. “In this way you can get a very early warning of when a new outbreak is coming,” Weimer said. “Here’s a recipe for how to go about it.”
The GENI score gauges the genetic difference between circulating viral sequences from the outbreak reference sequence, in this case, Wuhan-Hu-1 NC_045512.2.
At the same time, the researchers generated the instantaneous reproductive number (R) — which measures the transmission of a pathogen — as of March 2020, based on serial intervals of either two or seven days for more than a dozen countries. This value ranged from 8.0 in Italy to 4.3 in the US and 1.6 in China, based on the two-day estimate.
This difference in epidemic stages, they noted, was further reflected in the different regions’ epidemic curves, or epicurves. They divided the epicurves into four stages: index, takeoff, exponential, and decline. In March 2020, 52 countries were in the index stage, five in takeoff, three in exponential, and one in decline.
The researchers then examined their GENI score in conjunction with those other measures in Singapore during the index phase of the epidemic there and in South Korea during the exponential phase of its epidemic. The two locations had different GENI scores — Singapore had a score of 2, while South Korea had a score of 4 — indicating GENI could distinguish the two phases.
They further applied this approach to data from more than 20,000 viral genomes from the UK collected between February and April 2020, during times of viral surges there. They again found that increased GENI scores and outbreak surges aligned and additionally reported that there was increased genomic variation in the UK samples, even as efforts like lockdowns were implemented with the aim of slowing the outbreak.
Weimer noted in an email that the approach could further help officials gauge the effectiveness of their pandemic control measures.
Additionally, he said the team is finishing up a follow-up paper that uses additional times, sequences, and variant models, as well as additional data.
This story first appeared in our sister publication, Genomeweb.