National modelling led by Centre for Complex Systems researchers shows that a pandemic peak is in sight, but we must brace for a surge of infections upon.
Your Facebook data could soon help authorities predict and stop the spread of the coronavirus in the early stages of an outbreak.
Harvested by the social media giant with permission, Facebook s data shows a user s movements throughout the day.
Using the de-identified information, Australian researchers have built a model that can predict how clusters would spread.
Using the de-identified information, Australian researchers have built a model that can predict how clusters would spread (stock)
The team, from The University of Melbourne, The University of Adelaide, Monash University and The University of NSW, then applied to model to three real Australian outbreaks, comparing the prediction with actual case numbers.
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GPS data could help map COVID-19 transmission risk
The study found de-identified GPS data could be used to identify areas with heightened COVID-19 transmission risk.
Human mobility data gathered from de-identified mobile devices could help map coronavirus (COVID-19) transmission and support contact tracing efforts, according to new research.
The Australian research, published today in Journal of the Royal Society Interface, analysed the Cedar Meats outbreak in Melbourne, the Crossroads Hotel outbreak in Western Sydney and community transmission in Victoria between June and July 2020.
The transmission patterns were then compared to near-real-time population mobility GPS data gathered from the Facebook Data for Good program.
The research found locations where people had predictable and periodic movement – such as travelling to and from work – provided more useful indicators of virus spread than social settings. In the case studies, the data was therefore more useful in predicting virus spread in the Cedar Meats outbreak than the Crossroads Hotel outbreak.
When it came to analysing Victoria’s second wave, which started with the confined suburb lockdowns in late June and early July, the analysis found mobility data could have alerted the government the spread had already moved beyond the suburbs initially confined to lockdown.
“Our examination of the second wave of community transmission in Victoria showed that several weeks before it was recognised, the spatial distribution of a small number of active cases was indicative of the outbreak distribution more than 30 days later when interventions were introduced,” the researchers said in the paper.