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Scientists develop method to detect regions at risk of spreading Covid-19

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Researchers have developed a new, non-invasive strategy to use data from existing cellular wireless networks to identify potential hotspots for the further spread of COVID-19, a breakthrough that may help contain the pandemic.

Scientists, including Edwin Chong of Colorado State University in the United States, say the new technique can help identify the busiest areas, such as downtown, where asymptomatic carriers are more likely to come into close contact with a large number of healthy people.

The technique, described in the IEEE Open Journal of Engineering in Medicine and Biology, can help regions avoid scenarios where the virus wreaks havoc in densely populated areas of a country.

Using this strategy, the scientists said they hoped to understand how mobile device users move and congregate over time in an area using so-called transfer and (re) protocols. cell selection.

They explained that these protocols are cellular network technologies that allow people to move freely with their mobile devices without losing service.

Using this data that scientists collected via these networks, they measured cell transfer and (re) selection activity, called HO / CS rate, to assess the local movement of people and the population density of the region.

With real-time updates available, they said the data allowed them to report areas at risk for further monitoring.

According to the researchers, the higher the HO / CS rates received in real-time updates, the higher the density and mobility of people in these locations – indicating a higher risk of spreading infectious diseases like COVID-19.

“Our results could help risk managers plan and mitigate risks,” said Chong, who is a leading researcher in cellular wireless networks.

“This could encourage them to close a busy place, for example, or to implement stricter social distancing measures to slow the spread of the virus,” he added.

According to scientists, the approach could also be used to estimate the fraction of people staying at home to determine if communities are following recommended public health policies.

Chong said he is also sensitive to and concerned about privacy and security issues.

Unlike contact search apps that require widespread adoption, he said the new approach protects the privacy and anonymity of individuals without requiring the active participation of device users.

“Our method overcomes the disadvantages of contact tracing applications. All we have to do is perform the measurements using anonymous data that is already collected for other reasons. We do not track individuals”, a said Chong.

According to the Colorado State University scientist, the technique has applications beyond COVID-19.

“It can help with other epidemiological risks, like the flu. Regardless of the disease, it is very important to have tools that help risk managers to focus and prioritize to protect our citizens”, did he declare.

(Only the title and image of this report may have been edited by Business Standard staff; the rest of the content is automatically generated from a syndicated feed.)

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