Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.
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ABSTRACT:
SUBMITTER: Stolerman LM
PROVIDER: S-EPMC9848273 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
Publications
Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.
Stolerman Lucas M LM Clemente Leonardo L Poirier Canelle C Parag Kris V KV Majumder Atreyee A Masyn Serge S Resch Bernd B Santillana Mauricio M
Science advances 20230118 3
Coronavirus disease 2019 (COVID-19) continues to affect the world, and the design of strategies to curb disease outbreaks requires close monitoring of their trajectories. We present machine learning methods that leverage internet-based digital traces to anticipate sharp increases in COVID-19 activity in U.S. counties. In a complementary direction to the efforts led by the Centers for Disease Control and Prevention (CDC), our models are designed to detect the time when an uptrend in COVID-19 acti ...[more]
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