Predicting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phones.

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Bibliographic Details
Title: Predicting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phones.
Authors: Rüdiger S; Machine Leaning Unit, Department of Engineering, NET CHECK GmbH, 10829 Berlin, Germany; sten.ruediger@googlemail.com., Konigorski S; Digital Health-Machine Learning, Hasso-Plattner-Institut, Universität Potsdam, 14482 Potsdam, Germany.; Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029., Rakowski A; Digital Health-Machine Learning, Hasso-Plattner-Institut, Universität Potsdam, 14482 Potsdam, Germany., Edelman JA; Digital Health-Machine Learning, Hasso-Plattner-Institut, Universität Potsdam, 14482 Potsdam, Germany., Zernick D; Machine Leaning Unit, Department of Engineering, NET CHECK GmbH, 10829 Berlin, Germany., Thieme A; Department of Radiation Oncology, Charité-Universitätsmedizin Berlin, 13353 Berlin, Germany.; Digital Clinician Scientist Program, Berlin Institute of Health (BIH), 10178 Berlin, Germany.; Department of Medicine, Stanford University, Stanford, CA 94305.; Department of Biomedical Data Science, Stanford University, Stanford, CA 94305., Lippert C; Digital Health-Machine Learning, Hasso-Plattner-Institut, Universität Potsdam, 14482 Potsdam, Germany.; Hasso Plattner Institute for Digital Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029.
Source: Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2021 Aug 03; Vol. 118 (31).
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: National Academy of Sciences Country of Publication: United States NLM ID: 7505876 Publication Model: Print Cited Medium: Internet ISSN: 1091-6490 (Electronic) Linking ISSN: 00278424 NLM ISO Abbreviation: Proc Natl Acad Sci U S A Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1091-6490
DOI:10.1073/pnas.2026731118