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Computer Model Tracks Cellphone Data to Predict Covid Spread

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Tracking infections via smartphone.

Binghamton University researchers developed a new algorithm that narrows the geographic scope of COVID predictions, making it more useful for regional and local officials looking to curb the spread of the virus.

Credit: Penn Medicine News

Binghamton University's Arti Ramesh and Anand Seetharam have designed an algorithm to predict the spread of Covid-19 by tracking cellphone data.

The scientists matched cellphone data with coronavirus infection rates in Rio de Janeiro's municipal districts to construct a mathematical model that predicts how cases would shift the next week for Rio’s municipal districts; forecasts were based on current Covid rates blended with mobility trends between districts with the most cases.

Seetharam said, "This is one of the first studies that has quantified mobility in a manner that it can be used to demonstrate how cases are going to spread. It’s not just the number of cases in a particular region that contributes to future cases in that region."

From Binghamton University
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Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA


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