The Omicron variant quickly took over the global coronavirus landscape after it was first reported in South Africa in late November 2021. The United States became the 24th country to report a case of Omicron infection when health officials announced on December 1, 2021 that a new strain had been identified in a patient in California.

How do scientists know which versions of the coronavirus are present? How quickly can you tell which virus variants are invading a population?

Alexander Sundermann and Lee Harrison are epidemiologists studying new approaches to outbreak detection. Here they explain how the genomic surveillance system works in the US and why it is important to know which virus variants are in circulation.

What is Genome Monitoring?

Genome monitoring offers an early warning system for SARS-CoV-2. Just as a smoke alarm helps firefighters see where a fire is breaking out, genome monitoring helps public health officials see which coronavirus variants are where.

Laboratories are sequencing the genome in coronavirus samples taken from COVID-19 tests on patients. These are diagnostic PCR tests that have found positive for SARS-CoV-2. Then scientists can tell from the genome of the virus which coronavirus variant infected the patient.

By sequencing enough coronavirus genomes, scientists can get a representative picture of which variants are circulating in the population as a whole. Some variants have genetic mutations that affect the prevention and treatment of COVID-19. In this way, genome surveillance can make decisions about the right countermeasures and help control and extinguish the fire before it spreads.

For example, the Omicron variant has mutations that reduce the effectiveness of existing COVID-19 vaccines. In response, officials recommended booster shots to improve protection. Similarly, mutations in Omicron reduce the effectiveness of some monoclonal antibodies that are used to both prevent and treat COVID-19 in high-risk patients. Knowing which variants are circulating is therefore crucial in determining which monoclonal antibodies are likely to be effective.

How does genome surveillance work in the US?

The U.S. Centers for Disease Control and Prevention runs a consortium called the National SARS-CoV-2 Strain Surveillance (NS3) System. It collects around 750 SARS-CoV-2 positive samples per week from state public health laboratories in the United States. Regardless of the CDC’s efforts, commercial, university, and health laboratories are sequencing additional samples.

Each type of laboratory has its own strengths in genome surveillance. Commercial laboratories can quickly sequence large numbers of tests. Scientific partners can provide research expertise. And public health laboratories can provide insights into local transmission dynamics and outbreaks.

Regardless of the source, the sequence data are usually made publicly available and thus contribute to genomic monitoring.

What data is tracked?

When a laboratory sequences a SARS-CoV-2 genome, it uploads the results to a public database that contains when and where the coronavirus sample was taken.

The Open Access Global Initiative on Sharing Avian Influenza Data (GISAID) is an example of one of these databases. Scientists launched GISAID in 2008 to quickly and easily determine which strains of influenza are circulating around the world. Since then, GISAID has grown and panned to offer access to SARS-CoV-2 genome sequences.

The database compares the genetic information of a sample with all other samples collected and shows how that particular strain has evolved. To date, over 6.7 million SARS-CoV-2 sequences from 241 countries and territories have been uploaded to GISAID.

Taken together, this patchwork of genomic surveillance data provides a picture of the current variants that are spreading in the United States. For example, on December 4, 2021, the CDC forecast that Omicron would account for 0.6% of COVID-19 cases in the United States, which rose to 95% by January 1, 2022. The surveillance issued a strong warning of how quickly this variant caught on and allowed researchers to study which countermeasures would work best.

It is important to note, however, that genomic surveillance data are often dated. The time between a patient performing a COVID-19 test and uploading the viral genomic sequence to GISAID can be many days or even weeks. Because of the multiple steps in the process, the average time from collection to GISAID in the US is seven days (Kansas) to 27 days (Alaska). The CDC uses statistical methods to estimate the share of variants for the most recent past pending official data.

How many COVID-19 samples will be sequenced?

In early 2021, the CDC and other public health laboratories sequenced a total of around 10,000 COVID-19 samples per week. Given that hundreds of thousands of cases were diagnosed each week during most of the pandemic, epidemiologists believed that number was too small to provide a complete picture of the circulating strains. More recently, the CDC and public health laboratories have sequenced closer to about 60,000 cases per week.

Despite this improvement, there is still a large gap in the percentages of COVID-19 cases sequenced from state to state, ranging from a low of 0.19% in Oklahoma to a high of 10.0% in North Dakota within the United States last 30 days are enough.

Additionally, the US has a much lower overall percentage of COVID-19 cases compared to some other countries: 2.3% in the US compared to 7.0% in the UK, 14.8% in New Zealand and 17 % in Israel.

Which COVID-19 tests are sequenced?

Imagine if researchers were only collecting COVID-19 tests from one neighborhood in an entire state. The monitoring data would be skewed to the variant circulating in this neighborhood, since people are likely to transmit the same exposure locally. The system may not even register another variant that is gaining traction in another city.

For this reason, scientists try to collect a diverse sample from one region. Geographically and demographically representative random samples give the researchers a good overview of which variants are predominant or which are decreasing.

Why aren’t patients getting results differently in the United States?

There are several reasons why patients generally are not informed of the results when their sample is sequenced.

First, the time lag from sample collection to sequence results is often too long to make the information clinically useful. Many patients are well advanced by the time their variant is identified.

Second, the information is often not relevant to patient care. The treatment options are largely the same, regardless of which variant caused a COVID-19 infection. In some cases, a doctor can select the most appropriate monoclonal antibodies for treatment depending on the variant a patient has, but this information can often be gleaned from faster laboratory methods.

As 2022 begins, it’s more important than ever to have a robust genomic surveillance program that can detect the next new coronavirus variant. A system that provides a representative picture of current variants and a fast turnaround time is ideal. Appropriate investments in genome monitoring for SARS-CoV-2 and other pathogens, as well as in data infrastructure, will help the US fight future waves of COVID-19 and other infectious diseases.

Alexander Sundermann, Clinical Research Coordinator & DrPH Candidate in Epidemiology, University of Pittsburgh Health Sciences and Lee Harrison, Professor of Epidemiology, Medicine and Infectious Diseases and Microbiology, University of Pittsburgh Health Sciences

This article was republished by The Conversation under a Creative Commons license. Read the original article.


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