Genomic variation provides insight into the spread of coronavirus

The worldwide spread of COVID-19 has caused an unprecedented crisis of infectious disease, which has led to more than 180,000 pandemics in more than 100 countries. Reproductive number (R) is an outbreak metric that estimates pathogen transmission

According to researchers at UC Davis, the spread of SARS-CoV-2 around the globe has changed its infection rate with genomic variations. Monitoring the viral genome can help public institutions focus on areas where they are experiencing increased infection.

What we’re trying to do is establish whether genomic mutations in the virus can predict changes in infectivity,” said Burt Weir, a professor of population health and reproduction at the University of California, Davis, School of Veterinary Medicine. Said.

Genomic variation provides insight into the spread of coronavirus
Genomic variation provides insight into the spread of coronavirus

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Weimer and graduate student DJ Darwin R. Bandoy analyze the genomes of 150 SARS-CoV-2 strains, primarily from outbreaks in Asia before March 1, and epidemiological and transmission information about their occurrence.

They classified outbreaks by stage: index (no outbreak), takeoff, exponential increase, and decrease. Ease of transmission of the virus is established by the value R or the number of reproduction. 

All of this information was combined to create a metric called GENI to identify the pathogen’s genome.

Although there are only 15 genes, Weirmer says that SARS-CoV-2 is constantly mutating as it spreads around the world. Most of these changes make little difference, but the virus can be infected. For example, the estimate for R on March 1 was less than 2 in China and 8 in Italy.

Comparing the GENI score with the epidemic stage, for example, in late February Korea, found that the increase in genetic variation was just before exponential growth.

However, in Singapore, the explosion of fluctuations was associated with a smaller outbreak that public health authorities could quickly control.

The team will use a larger set of 2,000 SARS-CoV-2 genomes for more detailed analysis.

This combination of genomic and epidemiological information allows authorities to better predict where the spike in COVID-19 cases is occurring, Weimar said.

The worldwide spread of COVID-19 has caused an unprecedented crisis of infectious disease, which has led to more than 180,000 pandemics in more than 100 countries. Reproductive number (R) is an outbreak metric that estimates pathogen transmission

According to researchers at UC Davis, the spread of SARS-CoV-2 around the globe has changed its infection rate with genomic variations. Monitoring the viral genome can help public institutions focus on areas where they are experiencing increased infection.

What we’re trying to do is establish whether genomic mutations in the virus can predict changes in infectivity,” said Burt Weir, a professor of population health and reproduction at the University of California, Davis, School of Veterinary Medicine. Said.

Genomic variation provides insight into the spread of coronavirus
Genomic variation provides insight into the spread of coronavirus

A preprint describing the work is available online and the document has been submitted for publication.

Weimer and graduate student DJ Darwin R. Bandoy analyze the genomes of 150 SARS-CoV-2 strains, primarily from outbreaks in Asia before March 1, and epidemiological and transmission information about their occurrence.

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All of this information was combined to create a metric called GENI to identify the pathogen’s genome.

Although there are only 15 genes, Weirmer says that SARS-CoV-2 is constantly mutating as it spreads around the world. Most of these changes make little difference, but the virus can be infected. For example, the estimate for R on March 1 was less than 2 in China and 8 in Italy.

Comparing the GENI score with the epidemic stage, for example, in late February Korea, found that the increase in genetic variation was just before exponential growth.

However, in Singapore, the explosion of fluctuations was associated with a smaller outbreak that public health authorities could quickly control.

The team will use a larger set of 2,000 SARS-CoV-2 genomes for more detailed analysis.

This combination of genomic and epidemiological information allows authorities to better predict where the spike in COVID-19 cases is occurring, Weimar said.

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