Scientists Develop Software to Rapidly Detect Epidemics
Researchers at Georgia State University have created lightning-fast computer software. This software is capable of detecting epidemics before they spread around the world. It can also help in detecting the pandemic caused by Covid-19. It is also helpful in tracking and analysing epidemics in different countries.
The team of computer science and mathematics researchers says that this new software can produce results faster than existing computer programs. It works in multiple steps and can process more than 2 million new virus genomes in less than two hours.
It provides information that can be important for countries to make early decisions about lockdowns, social distancing and testing during infectious disease outbreaks.
Georgia computer science professor Alexander Zelikovsky said the future of infectious outbreaks will certainly be driven by huge data.
Their study describing the new approach is able to measure and reconstruct changes in the SARS-CoV-2 phylogeny.
Scums said that the COVID-19 pandemic has been an unprecedented challenge and opportunity for scientists. Never before have researchers around the world sequenced such a complete genome of any virus.
Variants or strains of SARS-CoV-2 are uploaded to the free global Gyside database, where they can be studied by any scientist. For their new work, Jellikowski, Schums and their colleagues analyzed more than 3 million different variants.
Zelikovsky said there are now more than five million genomes in the Gyside database. Scientists around the world are probably sequencing a new version almost every hour.
Zelikovsky said this surprising amount of data helps scientists see the evolution of the virus in action taken in real time. This is possible only when we have software capable of analyzing it rapidly.
In the early days of the pandemic, in March 2020, scientists were acting too slow. Scientists thought that the virus first came to Washington state in February. However, sequencing later presented in a paper by Scums and colleagues showed the arc of viral variants traveling across countries and oceans.
Along with the new studies, scientists found that the virus from variants originating in Europe had also quietly entered New York City in February.
At that time, scientists were sequencing the data very slowly to trace the actual migration of this global virus and its changes in real time.
Scums said the programs were not fast enough, not measurable. The algorithms were not equipped to handle the large amount of data. It can take hours or days to process even a small part of the infected genome, he said.
Zelikovsky, Scums and their colleagues created a new algorithm for sequencing, called SPHERE (Scalable Phylogeney with Recurrent Mutation). The Sphere can rapidly handle large amounts of real-time data and form the evolutionary structure of the virus and its variations. These scenes can be easily understood at a glance. The computer program itself is freely available for download for any researcher in the world.
When the researchers applied their algorithm to genomes from the Gyside database, they found their Sphere approach to be highly reliable for tracking how viruses spread. The Sphere could help scientists track how a virus is evolving in real time.
Zelikovsky said we can see how the changes spread from country to country and from region to region. We can determine how the lockdown and closure effect spread. What are the consequences for government policy?
Zelikovsky said the Sphere algorithm could prove invaluable in future pandemics. You can track chains of transmission very quickly. Seeing those links will help governments make sound decisions about social policies like distancing or lockdowns in times of high transmission.
The sphere can also show the effects of different modes of outbreaks. For example, Schums said, Sweden took a more relaxed approach to the COVID-19 pandemic than other Nordic countries. Analysis of sequencing data shows that the “transmission chain” is longer in Sweden. This means that one strain in Sweden can infect many more people one after the other.
Zelikovsky said the danger of long links is that a new strain could emerge. Could be one of those variants that is very good at infecting people. It will help us to face this kind of global pandemic.
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