Mathematical equation to evaluate the risk of infecting a guest with | Phalanges



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Mathematical equation to evaluate the risk of contagion of one of the guests with Corona.

American researchers devised a simple way to find out the range of the probability that one of the guests at an event was infected with the emerging corona virus, based on a mathematical equation presented on the Internet that received great popularity.
If there are 10 people at the same table, then the risk of at least one of those present becoming infected with the virus is 32 percent in Paris, 18 percent in Washington, and 58 percent in Prague, for example.
This simple math equation is based on real-time data on the spread of the Covid-19 epidemic presented in an easy-to-read manner on a website that has been increasingly successful since its inception in July at the initiative of researchers from the Georgia Technical Institute in the United States whose methodology was approved in an article published in the journal Nature. Of yore.
The website “Covid-19 Risk”, available in English, was the victim of its success yesterday, due to the large number of visits it received and messages indicating that an error sometimes occurred.
Researchers estimate the probability of risk based on the official total of cases counted each day at a given site. The model also takes into account that the actual number of infections is 5 to 10 times higher than the total number of positive diagnostic tests.
The user can base one of these two assumptions (5 or 10 times) on his calculations.
The percentages reported above are based on the assumption that the risk is ten times greater.
The user can also choose the size of the event while specifying the number of people expected to participate in it, be it 10, 25, 50 or one hundred, up to 5,000.
The site takes a strict approach, according to its founder, Joshua Weitz, as a person is supposed to remain contagious for ten days, while other researchers believe that this period ranged from 5 to 6 days, although viral deposits remain later.
The approved model does not take into account that the person infected with the virus is most likely to stay at home and not participate in the event after symptoms appear, since the infected person is based on the fact that the Most infections are caused by people who are largely or completely without symptoms or who are unaware of their infection.
“We hope that this information will deter people from organizing big events,” said Joshua Weitz.

Source: National Information Agency



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