Smart dashboard should predict regional outbreaks COVID-19

The first dashboard in the Netherlands that will predict, with great certainty, where local outbreaks of COVID-19 infections may occur. A multidisciplinary research team led by Nelly Litvak, Professor of Algorithms for Complex Networks at Eindhoven University of Technology (TU/e), will work on this dashboard, thanks to a half million-euro grant from ZonMW. The team has worked since the corona outbreak in March to provide such predictions using aggregated mobility information from cell phone usage. The grant will be used to significantly improve those predictions, through the smart combination with data from the COVID Radar App. This will enable safety regions, responsible for local and regional corona measures, to intervene faster and more effectively in the event of imminent corona outbreaks and can even prevent the emergence of new hotbeds.

The spread detection of COVID-19 infections is currently lagging behind. For example, a couple of days are easily lost to obtaining test results and finding possible new infections through contact research. In addition, tracing the physical movements of these people is difficult or even impossible due to a lack of time.

Project leader Nelly Litvak. Photo: Rob Stork

The new dashboard can make a big difference in this respect, says project leader Nelly Litvak. “By combining the aggregated mobility patterns with the risky behavior data in the mathematical model of the virus’s spread, we can determine the risks of it spreading from one area to another fairly accurately. This should allow mayors of safety regions to detect a potential local wave of infections and take timely measures – something which is very important now that the virus seems to be taking hold again.”

And there seems to be lots of enthusiasm for the dashboard. The safety regions of Groningen and Twente have already promised to provide the team with feedback right from the start so that the first prototypes can be designed to optimize the user experience from the beginning.

Combining data

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