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Cellular data could be used to implement localised Covid-19 lockdowns

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Scientists believe they can draw on data from existing cellular wireless networks to pinpoint potential hotspots for increased transmission of Covid-19.

With the UK announcing its first local lockdown in Leicester today, such data could help governments going forward to pinpoint where such measures may be necessary to prevent broader spread of the virus.

The method is able to identify the most crowded areas with hustle and bustle, such as a city centre, where asymptomatic carriers have a higher probability of coming into close contact with large numbers of healthy people.

With mobile phone ownership nearly ubiquitous in developed countries, the technique allows tracking of large numbers of device users as they move and gather over time.

The researchers from Colorado State University used what are known as handover and cell selection protocols - the cellular network technologies that allow us to move about freely with our mobile devices without losing service.

Using data collected through these networks they were able to calculate localised population density and mobility, offer real-time updates and flag at-risk areas for further monitoring.

Their method builds on the premise that higher density and mobility increase the risk of spreading infectious diseases.

“Our findings could help risk managers with planning and mitigation,” said lead researcher Edwin Chong. “It might prompt them to cordon off a busy plaza, for example, or implement stricter social distancing measures to slow the spread of the virus.”

Chong said their approach could also be used to estimate the percentage of people staying home to determine whether communities are following recommended public health policies.

Chong referred to mobile devices as “always-on human trackers” and understands the concerns around privacy and security with such an approach.

Unlike contact-tracing applications that are often difficult to deploy and require widespread adoption, his approach protects the privacy and anonymity of individuals without needing active participation from device users.

“Our method overcomes the downsides of contact-tracing apps,” Chong said. “All we have to do is perform the measurements using anonymous data that is already being collected for other reasons. We are not tracking individuals.”

As nations step up efforts to plan for future outbreaks, he added that the technique has applications beyond Covid-19.

“It can help with other epidemiological risks, such as the flu. Regardless of the disease, it’s very important to have tools that help risk managers focus and prioritise to protect our citizens,” he said.

Yesterday, researchers from Oxford University’s Leverhulme Centre for Demographic Science published details about their online tool which combines data from multiple sources to help identify likely Covid-19 “pressure points”.

Earlier this month, the UK Government abandoned its attempts to develop a contact-tracing app in favour of adopting a system made by Apple and Google that has already been implemented in other countries in Europe.

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