Researchers Are Working on a Virtual Phone Virus That ‘Mimics’ the Spread of Covid-19

Researchers Are Working on a Virtual Phone Virus That ‘Mimics’ the Spread of Covid-19
Photo: Sean Gallup, Getty Images
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In an effort to assist the evolving science of contact tracing, researchers have created a virtual phone virus that is meant to “mimic” the spread of Covid-19. By “infecting” phones within a controlled environment, the researchers hope to gain a better understanding of the trajectory of viruses as they proliferate within a given population.

Academics at a number of universities — including MIT, Cornell, and several other colleges in England, Australia, and New Zealand — are behind the new project, which seeks to create a quick, privacy-centric way to simulate Covid’s spread, if not outright track it.

They are calling it “Safe Blues” and it’s designed to be injected into the software suites of existing contact tracing apps to collect data on users’ interactions with others. Data from the project can be collected in real-time and, unlike traditional contact tracing programs (which require high rates of participation to succeed), it would “require only about 10% of a given population to carry it in order to make accurate predictions,” researchers have said.

How it works is this: the Safe Blues uses “virus-like tokens” (also called “strands”) which are spread randomly between mobile devices via Bluetooth pings, in a way meant to mimic the proliferation of the biological virus. The anonymised data from these interactions can then be sent back to servers controlled by the researchers, showing how infections may multiply organically. Ideally, researchers say “Safe Blues” would give them “real-time population-level estimates of the level of physical proximity and near-future projections of the epidemic.”

Like other contact tracing solutions, this is less about studying the virus’s behaviour than it is the population that spreads it. In a recently published overview of the project, researchers note that:

…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.

“Our initial simulation analysis hints that Safe Blues data may help improve predictions of COVID-19 infection within the asymptomatic population,” researchers further claim.

The program is only in developmental stages, at this point. Researchers are currently working on launching a pilot program at the University of Aukland in New Zealand, where the virus can be spread safely within the controlled environment of a college campus (before it is, presumably, let loose in the wild, if that ever occurs).