International team of scientists develops machine learning model that could help inform COVID-19 containment measures

Newly published paper presents research that could make an important contribution to discussions about policies to ease lock-down measures

17 April 2020 Press Release Valérie Callaghan
Thumb ticker md fig exp2

This figure shows the cumulative number of people who tested positive for COVID-19 in the simulation (without lockdown measures) and those who actually tested positive (with lockdown measures).

In a paper released last week, researchers from two Max Planck Institutes, the Zerobase Foundation, ETH Zurich, and the École Polytechnique Fédérale de Lausanne present a new model that uses data from contact tracing technologies to make predictions about the spread of the virus


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