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Data-driven machine learning approaches to monitor and forecast the dynamics of disease outbreaks
May 7 @ 11:30 am - 12:30 pm
I will describe data-driven machine learning methodologies that leverage Internet-based information from search engines, Twitter microblogs, crowd-sourced disease surveillance systems, electronic medical records, and weather information to successfully monitor and forecast disease outbreaks in multiple locations around the globe in near real-time. I will present how these approaches can be used to build early warning systems to anticipate COVID-19 outbreaks.