Scientists have created a digital ‘virus’, which spreads between smartphones via Bluetooth, to learn more about the spread of real diseases.
They say the technology — called ‘Safe Blues’ — provides an accurate model of Covid-19 and can be used to track transmission as it happens.
The digital feedback is anonymous, instant and avoids the time lag seen with real viruses, as ‘infection’ is detected immediately.
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This diagram shows the basis of how Safe Blues works. Individuals of the population with Safe Blues enabled devices take part in spreading ‘strands’. SARS-CoV-2-infected individuals are in red and others are in green. The Safe Blues system operates independently of the health status of individuals
Harmless tokens are passed between devices only when certain criteria is met, such as a set distance between phones.
However, with a real virus, a person can be infected for a week or more before a positive case is registered, making it difficult to get real-time data on an epidemic.
An Android app for Safe Blues has been created which researchers are now testing on participants at the University of Auckland City Campus. It is not available on iOS.
It works in a similar way to the Covid-19 contact-tracing apps which have deployed globally and runs in the background.
An Android app for Safe Blues has been created which researchers are now testing on participants at the University of Auckland City Campus. It is not available on iOS
Participants are entered into a prize draw for iPads, phones, and FitBit trackers to encourage participation.
Writing on the app’s website, the developers say: ‘With a pandemic such as COVID-19, the data is always lagging and biased since the time between a patient being infected with SARS-CoV-2 and being recorded as positive can be a week or more.
‘Consequently there can be a time lag of the order of several weeks between the initiation of a regulatory measure and its observed effect.
‘There is thus a pressing need for real time information on the level of physical proximity while respecting personal privacy.
‘Safe Blues fills this need, providing real time population-level estimates of the level of physical proximity and near-future projections of the epidemic.’
The data collected from the app will be compared to epidemiological data.
Machine learning then uses the pooled information to create more accurate projections about an epidemic’s progression.
