Tuesday, February 23, 2021 00:41 AM (GMT + 7)
Youyang Gu – a 27-year-old boy living with his parents in California, USA – was dubbed the “prophet” of the Covid-19 translation when the data he gave out was precisely superior to the translation forecast systems Other reputable diseases.
Youyang Gu – young man who designs a Covid-19 translation warning system with unexpected accuracy (photo: Bloomberg)
In 2020, when the Covid-19 epidemic begins to spread around the world, countries will mainly rely on two of the most modern forecasting systems to assess the severity of the disease.
These two systems, one developed by Imperial College London, UK, and the other by the American Institute of Health Metrology and Evaluation (IHME).
However, these two arguably the world’s most reputable warning systems regularly release different metrics.
Last summer, IHME forecasted that the US could record about 60,000 people dying from the Covid-19 epidemic, but the figure given by the Royal University of London was 2 million.
However, both of the above systems gave inaccurate results. By early August 2020, the US had recorded about 160,000 deaths from the virus.
Youyang Gu – who holds a master’s degree in mathematics and computer science at the prestigious Massachusetts Institute of Technology (MIT) – is dissatisfied with how both Covid-19 alert systems work.
Despite having no medical expertise, Gu is confident he can build a more accurate warning system about the disease.
Gu’s warning system makes an important contribution to disease control in the US (Image: Bloomberg)
After a week of research, Gu successfully built a Covid-19 death prediction system. Not stopping there, Gu also set up a website to announce data about the disease to everyone.
The algorithm designed by Gu provides accurate results, far exceeding the warning systems of both IHME and Imperial College London.
“Gu’s system is the only thing that works. Other models show their uselessness many times, ”said Jeremy Howard – computer data specialist at the University of San Francisco.
“The lives and lives of many people in a pandemic depend greatly on the warning system. Youyang Gu is the only person who knows how to properly process data, ”added Howard.
“Other systems bring together a lot of data sources to predict the death toll from the disease. However, my forecasting system is mainly based on the number of viral deaths in the past. I think this is the data source with the least interference, ”said Gu.
Last April, Gu’s system warned the US it could record about 80,000 deaths from the virus on September 9. The real results were 79,926 deaths.
On May 18 and May 27, Gu’s system continued to forecast the number of deaths caused by Covid-19 in the US at around 90,000 and 100,000, respectively. He continues to be accurate when the actual figures are very close to the warning.
Gu believes that more than half of the US population will be immune to Covid-19 by June of this year (photo: Bloomberg)
Last May, Gu’s warning system said that the US would face a second wave of Covid-19 spread. However, IHME said that the Covid-19 epidemic in the US has gradually been controlled and some states may remove quarantine measures. Again, Gu was right.
IHME then faced countless criticism for the persistent false warning. However, the IHME system is still funded by the Bill & Melinda Gates Foundation of billionaire Bill Gates to overcome.
Due to accurate forecasts of the disease, Gu’s warning system is becoming more and more known and monitored.
The US Centers for Disease Control and Prevention (CDC) also publishes Gu’s warning data on its official website. Gu also met many times with US CDC officials.
In October 2020, Gu’s system forecasts that by November 1, 2020, the US will record 231,000 Covid-19 deaths. In fact, the US recorded 230,995 deaths due to the virus on this date.
Currently, Gu is turning to algorithm design to study the time when the US can achieve community immunity thanks to the Covid-19 vaccine.
He predicts that by June this year, 61% of Americans will be immune to Covid-19 through vaccines and have antibodies after recovering from a viral infection.
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