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How Genomic Epidemiology is tracking the spread of COVID-19 locally and globally?

January 15, 2021 - by Parul Saini, Webmedy team

The novel coronavirus is challenging genome sequencing technology and data processing like never before.

In December 2019, new cases of severe pneumonia were first detected in Wuhan, China, and the cause was resolute to be a novel beta coronavirus related to the severe acute respiratory syndrome (SARS) coronavirus that emerged from a bat reservoir in 2002. During the first month of the outbreak, 2,641 cases of COVID-19 led to 1,832 hospital admissions, 207 intensive care admissions, and 126 deaths. Coronavirus disease 2019 (COVID-19), the disease caused by SARS-CoV-2, was declared by the World Health Organization a public health emergency of international concern on January 30, 2020, and a pandemic on March 11, 2020. Covid 19 has created worldwide lockdowns, economic and social disturbance leading to the healthcare sector being overrun.

Multiple outbreaks suggest that preparation and response strategies need modernization. Modern advances in DNA sequencing, genomics, epidemiology, and big data analyses give new models for tracing symptomatic and asymptomatic transmission networks and identifying sites of spread and at-risk populations, thereby enabling the capability to break or delay virus transmission to decrease social and economic disturbance and reduce morbidity and mortality.

Samples and Epidemiological Data

Geneticists have been able to sequence viral genomes for decades, but the latest advancements in technology imply they can now do so in a matter of hours or days. Just as quickly, scientists around the world can share what they learn via a global open-source network known as Nextstrain. This speed and collaboration have been a game-changer, allowing this "genomic epidemiology" to be used in real-time as the COVID-19 pandemic unfolds. Much of the power of genomic epidemiology derives from the fact that most viruses make lots of mistakes when they copy their genomes, so variations in the sequence - that is, new mutations - turn up relatively often. That's particularly true of viruses that use RNA as their genetic material, as coronaviruses do. Very few of these mutations influence how the virus acts - most have no apparent consequence at all - but researchers can use them as markers to make a family tree of the virus and to see whereby the virus has changed over time and how it has extended from locale to locale.

Early in the COVID-19 outbreak, researchers all over the world started sequencing viruses tested from patients and building a family tree of the virus on Nextstrain. Almost instantly, they could see that the tree was short - the virus sequences had not yet acquired many distinct mutations, meaning that the new coronavirus, SARS-CoV-2, hadn't been infecting humans for long. Moreover, the tree had a single trunk, indicating that every virus infecting humans likely dropped from a single case in early December 2019. The SARS Cov-2 virus's genetic mutability also means that epidemiologists can use these variations in their genome to track the speed of the virus during an epidemic. That's because most mutations are essentially random, so each branch of the virus tree is likely to have its own unique set of mutations. If one person's virus contains mutations A, B, and C, for example, that person could have caught it from someone whose virus carries A and B or A and C, but not from someone whose virus has A, B, C, and D.

Following the Genetic Trail

Early in the current pandemic, Nextstrain recorded the presence of identical or near-identical coronavirus genomes from people in countries as widely spaced as Canada, Australia, and the UK. The genomes were so alike that scientists concluded they must have shared a common source. That red flag prompted further interrogation, which revealed that all of the sick had lately traveled to Iran. For the Covid-19 virus, each viral lineage accumulates about 30 new mutations per year, which works out to about one new mutation per two links in the transmission chain. As a result, the same viral genome sequence can be found in various people, so genome-trackers can narrow transmission down to only a handful of suspects. Additional uncertainty comes from the fact that researchers can't probably sequence viruses from every infected individual in a widespread pandemic.

Viral Family Tree

Genomes can be very good at answering a key public health question early in an epidemic: Are new infections in a given locality imported by travelers, or are they homegrown? The latter - the result of the virus circulating within the community - would create a need for the social-distancing measures now familiar to so many of us.

In late February, for example, sequencers found patients in Germany and Italy who shared the same unusual viral mutation. Since the German patient had gotten sick sooner, this led some researchers to suggest that the virus had spread from Germany to Italy. In reality, though, both German and Italian patients could have caught the virus from some third person, yet mysterious, whose virus was not sequenced. Still, these limitations have not kept genomic epidemiology from playing a key role in the COVID-19 pandemic. The approach has helped public health officials identify the pathogen, trace its travels, and recognize community spread promptly. And in the months ahead, the method may have more to contribute. One contribution is likely to come from longer-term studies of where mutations fall in the genome. Most of the genetic changes, remember, make little or no difference to the virus: They are "neutral," in evolutionary biologists' parlance. But mutations that change the shape of key proteins, such as the spike protein on the surface of the virus that binds to receptors in our cells, are more likely to matter.

By using genomic breadcrumbs to track the transmission of the virus, epidemiologists hope to recognize which activities are most likely to spread the virus. The science community is focused on finding as much genomic data as possible. The next step might be to discover links between the genomic sequences of SARS-CoV-2 and its viral properties. This could help scientists understand whether a particular mutation leads to a more severe infection or a set of symptoms.

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