Researchers Developled Virtual Phone Virus To Recreate How COVID-19 Spreads
Dhir Acharya - Mar 16, 2021
'Safe Blues' is designed to be injected into existing contact tracing apps’ software suites to collect data on the interactions of the user with others.
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To help evolve the science of contact tracing, researchers have developed a virtual phone virus to mimic the spread of the coronavirus. The infected phones in a controlled environment, the research team aims at getting a better understanding of the virus’s trajectory when they proliferate in a given population.
Researchers from several universities, including Cornell, MIT, along with other colleges in Australia, England, and New Zealand, are working on this new project, aiming to create a quick, privacy-centric way of simulating the spread of COVID-19.
“Safe Blues” is designed to be injected into existing contact tracing apps’ software suites to collect data on the interactions of the user with other people. The data can be collected in real-time and require only 10% of a given population to carry it to make accurate predictions, according to the researchers.
Here’s how Safe Blues works: it uses virus-like tokens spread randomly between mobile devices through Bluetooth pings, mimicking the proliferation of the coronavirus. Then, the anonymized data collected from these interactions can be sent to servers controlled by the research team to show how infections multiply organically.
The researchers say that ideally, Safe Blues would provide real-time population-level estimates of the level of physical proximity as well as near-future projections of the epidemic.
![covid-19 spread](https://img.mobygeek.com/resize/730x-/2021/03/16/europe-covid-crisis-compressed-b72e.jpg)
It’s worth noting that the project is more focused on studying the population that spreads the virus. The researchers note:
“...population behaviour is changing rapidly due to unprecedented social distancing measures and is hard to observe and to predict. As a consequence, achieving tight real-time estimates...[of] the expected number of individuals infected by an infected person, is a difficult task.”
According to the researchers, initial simulation analysis suggests that Safe Blues data may improve COVID-19 infection predictions in the asymptomatic population.
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