The study found new methods of more accurate epidemiological modeling

According to a recent study published in Scientific Reports by researchers at the University of California, Irvine, and others, a new epidemiological model based on alternative thinking about how infectious diseases spread, especially in the early stages of a pandemic, provides a blueprint for more accurate epidemiological modeling and improved disease transmission prediction and response.In the paper, scientists say standard epidemic models mistakenly believe that the rate at which infectious diseases spread depends on a simple product of the number of infected and susceptible populations. The authors suggest that transmission does not occur through a complete mix of entire populations, but at the sub-group boundaries of infected individuals.


Thryphon Georgiou
, professor of mechanical and aeronautical engineering at UCI, said: "The epidemiological model of the
"
standard relies on the hypothesis of a strong mix between infected and unseeded people, and there is a wide range of links between these groups. Instead, we emphasize the spread that occurs in geographically concentrated cells. Therefore, we believe that the use of fractional indices helps us to more accurately predict disease infection and transmission rates.
”
the researchers proposed an alternative to the

-small-number power
"
of the idioplasm model, which considers vulnerable, infected and rehab. The exponential values in these fractional
fSIR
) models depend on a variety of factors, such as the nature and extent of exposure between infected and healthy sub-groups.

, in the early stages of the epidemic, infections spread from infectious transmitters to the general population. Because the number of susceptible populations is much larger than the number of infected people, the boundaries of infected cells are scaled by fractions smaller than one of the cell areas.
The researchers tested their theory through a series of numerical simulations. They also fitted the fractional model to john
.
data from the Hopkins Center for Systems Science and Engineering. The data cover the coVID-19 epidemic in Italy, germany
France and Spain
previous months. Through both processes, they found that the index was in the range of
0.6
and
0.8
and 0.8.

"The
"
-score index affects the early and late stages of an epidemic in different ways, so determining the correct index extends the duration at which reliable predictions can be made compared to previous models," Georgiou said.
”
in the current
In the context of the coVID-19
pandemic, a better understanding of the spread of infection may help to make decisions related to cover-up systems and social alienation provisions in the community.
"We need to
accurate
that can help policymakers choose the right action plan to help prevent further spread of infectious diseases," Giorgio said.
"
(
cyy123.com
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