Scientists develop new method for locating areas at risk of Kovid-19 outbreak

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HOUSTON: Researchers have developed a new, non-invasive strategy that can pinpoint potential hotspots for increased Kovid-19 proliferation using data from existing cellular wireless networks, an advance that could help prevent epidemics is.
According to scientists, including Edwin Chong of Colorado State University in the US, novel technology can help identify the most congested areas, such as the city center, where large numbers of healthy people are likely to come into close contact. .
The technique, described in the IEEE Open Journal of Engineering in Medicine and Biology, may help avoid scenarios in areas where the virus causes havoc in densely populated areas in the country.
Using the strategy, the scientists said they hope to understand how mobile device users move and gather over time in an area known as the handover and cell (re) selection protocol.
He points out that these protocols are cellular network technologies that allow people to roam freely with their mobile devices without losing service.
Using this data, which scientists collected through these networks, they measured handover and cell (re) selection activity called HO / CS rates to evaluate the local movement of people and the population density of the area.
With real-time updates available, he said the data allows him to mark at-risk areas for further monitoring.
According to researchers, the higher the rate of HO / CS received in real-time updates, the higher the density and mobility of people at these locations – the higher the risk of spreading infectious diseases such as Kovid-19.
“Our findings can help risk managers with planning and mitigation,” Chong, a leading researcher in cellular wireless networks.
“It may prompt them to do away with busy plazas, for example, or implement strict social removal measures to slow the spread of the virus,” he said.
According to scientists, this approach can also be used to estimate the fraction of people living in a home to determine whether communities are recommending public health policies.
Chong said he is also sensitive and concerned about privacy and security issues.
Unlike contact tracing applications that require widespread adoption, he said the new approach protects the privacy and anonymity of individuals without the need for active participation from device users.
Chong said, “Our approach eliminates the downside of contact tracing apps. All we have to do is make measurements using the anonymous data already being collected for other reasons. We are not tracking individuals , “Chong said.
According to a Colorado State University scientist, the technique has applications beyond the Kovid-19.
“It can help with other epidemiological risks, such as the flu. Despite the disease, it is very important to have tools that help risk managers focus and prioritize the safety of our citizens.” They said.

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