Alessandro Vespignani and analysts in Northeastern University's Network Science Institute are predictively modeling the coronavirus pandemic by incorporating social networks, in order to inform policy recommendations.
Vespignani's laboratory and other groups are using publicly available data to plot COVID-19's spread, applying vast amounts of computing power via the cloud.
One project uses census data to outline connections between household members, tracing each member's social links outside the household and repeating the process with nearby households to generate a digital map of community interconnections. Additional links from travel data into and out of the community yield a map of likely interactions, with fewer interactions and potential new infections modeled in response to school closings.
Meanwhile, Vespignani and Harvard Medical School's Mauricio Santillana are measuring daily changes in individual behavior during pandemics by factoring in words mentioned in online searches and social-media comments, to embed within travel and geographical models.
From The New York Times
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Abstracts Copyright © 2020 SmithBucklin, Washington, DC, USA
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