A study of SARS-CoV-2 genomes and epidemic case data has shown that COVID outbreaks emerge with new variants.
“As variants emerge, you’re going to get new outbreaks,” said Bart Weimer, professor of population health and reproduction at the UC Davis School of Veterinary Medicine. The study combined classical epidemiology with genomics, providing a tool for public health authorities to predict the course of pandemics.
SARS-CoV-2 only has 15 genes, but is mutating constantly. The majority of these changes have little impact, but occasionally they result in the virus becoming more or less transmissible.
Together with graduate student DJ Darwin R Bandoy, Prof Weimer at first analysed the genomes of 150 SARS-CoV-2 strains, mostly from outbreaks in Asia prior to March 1, 2020, along with epidemiology and transmission information on those outbreaks.
The classified outbreaks by stage: index (no outbreak), takeoff, exponential growth and decline. Virus transmissibility is set by the value R, or reproductive number, where R is the average number of new infections caused by each infected person.
They combined all this information into a metric called GENI, for pathogen genome identity. Comparing GENI scores with epidemic phases showed that an increase in genetic variation immediately preceded exponential growth in cases, for example in South Korea in late February. In Singapore, however, bursts of variation were associated with smaller outbreaks that were quickly brought under control.
Prof Weimer and Bandoy then looked at 20 000 sequences of SARS-CoV-2 viruses collected over February to April 2020 in the United Kingdom, and compared them with COVID cases data.
They found that the GENI variation score rose steadily with the number of cases. When a national lockdown was imposed in late March, the number of new cases stabilised but the GENI score continued to rise. This shows that control measures such as banning gatherings, mask mandates and social distancing are effective in controlling spread of disease in the face of rapid virus evolution.
It could also help explain “superspreader” events when large numbers of infections result from relaxed precautions at an event.
Prof Weimer said he hopes that health authorities will adopt this method of measuring virus variation and linking it to the local transmission rate, R.
“In this way you can get a very early warning of when a new outbreak is coming,” he said. “Here’s a recipe for how to go about it.”
Source: Medical Xpress
Journal information: Scientific Reports (2021). DOI: 10.1038/s41598-021-86265-4
