Quality & Governance News

Genomic Data Reveals COVID-19 Variants Contribute to Surges

Combining epidemiology with genomic data could help public health officials predict the course of future pandemics.

Genomic data reveals COVID-19 variants contribute to surges

Source: Getty Images

By Jessica Kent

- Analyzing the genomic data of thousands of COVID-19 samples showed that surges in cases are driven by the appearance of new variants, according to a study published in Scientific Reports.

Although SARS-CoV-2 – the virus that causes COVID-19 – has just 15 genes, it is constantly mutating. While most of these changes make little difference, sometimes mutations can make the virus more or less transmissible.

Researchers initially analyzed the genomes of 150 SARS-CoV-2 strains, mostly from outbreaks in Asia prior to March 1, 2020. The team also examined epidemiology and transmission information for those outbreaks.

Researchers classified outbreaks by stage: index (no outbreak), takeoff, exponential growth, and decline. The ease of transmission of a virus is set by the value R or reproductive number, where R is the average number of new infections caused by each new person.

The team then combined all this information into a metric called GENI, or pathogen genome identity. When the group compared GENI scores with the phase of an epidemic, they found that an increase in genetic variation came immediately before a significant spike in cases.

READ MORE: Deep Learning, Genomic Data May Help Predict Alzheimer’s Disease

Researchers noted that this was the case in South Korea in late February. However, in Singapore, bursts of variation were associated with smaller outbreaks that public health officials were able to quickly bring under control.

The team then looked at 20,000 sequences of SARS-CoV-2 viruses collected from February to April 2020 in the UK, and compared them with data on cases.

The results showed that the GENI variation score rose steadily with the number of cases. When the British government imposed a national lockdown in late March, the number of new cases stabilized but the GENI score continued to rise.

This demonstrates that public health measures like banning large gatherings, mask mandates, and social distancing can effectively control the spread of disease as a virus is rapidly evolving.

"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.

READ MORE: Exploring the Intersection of Genomic Data and AI in Healthcare

"In this way you can get a very early warning of when a new outbreak is coming. Here's a recipe for how to go about it."

The study’s results could also help explain superspreader events, where large numbers of people get infected in a single event when public health precautions are relaxed.

Researchers expect that the study’s findings will encourage public health officials to measure virus variation and link it to the local transmission rate.

“Leveraging shared resources opens unexpected collaboration and avenues for applying relevant bioinformatic and disease modelling opportunities across the scientific community to solve global public health problems very quickly,” researchers concluded.

“Based on this approach, we propose a systematic framework to merge epidemiology and genomics that was defined and validated in this work. The advantage of an evidence-based approach is the utility of whole-genome sequencing and surveillance that can be used to predict locations for new cases or used to quantitatively examine intervention effectiveness to control new cases.”

READ MORE: Genomic Data Advances Precision Medicine for Prostate Cancer

The study highlights the importance of genomic data as the virus that causes COVID-19 continues to mutate.

In a recent episode of Healthcare Strategies, David Relman, MD, professor of microbiology at Stanford University and member of the standing committee on Emerging Infectious Diseases and 21st Century Threats at the National Academies of Science, Engineering and Medicine, emphasized the significance of genomic sequencing during the pandemic.

Relman noted that in order to keep up with the rapidly changing virus, leaders and researchers will need to collaborate to develop the tools necessary for enhanced surveillance and prediction.

“First, we have to decide collectively that this is an issue of great importance and priority to our wellbeing. We have to see this infectious agent in a way that informs us as to its possible properties, behavior, evolution, and future trajectory. If we were to do that, then we would say, let’s develop a national strategy for pursuing the genomic surveillance of this or any future infectious agent,” he said.

“Second, let's develop a leadership plan for this process. Because in the United States, we have many, many brilliant creative scientists, but they tend to operate on their own. And for this kind of enterprise, you have to be coordinated. You have to be organized and integrated into one holistic system. We would need to allocate the resources to make sure that the strategy can be pursued and that everyone is properly organized and coordinated and informed.”

These strategies will be crucial in moving past the current pandemic, as well as in getting ahead of future disease outbreaks.

“We need to be doing this as best we know how, which means collecting all the right kinds of data, standardizing it, and sharing it properly. Then, we need to let the public know that what we could learn and predict about this or any future pandemic is the possible future evolutionary path of the infectious agent,” Relman concluded.

“It's immensely important, but we have to start by doing it right.”