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UID:20250918T044830EDT-0011KSV49C@132.216.98.100
DTSTAMP:20250918T084830Z
DESCRIPTION:Title: A Tale of Two Models for Covid-19 Scenarios.\n\nAbstract
 : Covid-19 Pandemic is a defining global health event in the 21st century.
  Forecasting the evolution of the pandemic is a key problem for anyone try
 ing to plan ahead. Since March 2020\, IHME has been generating Covid-19 sc
 enarios\, first for US states and then for all Admin-1 locations around th
 e world. These scenarios have been intensively used\; results are uploaded
  weekly to an interactive website: https://covid19.healthdata.org/\n\nIn t
 his talk\, we describe two core mathematical models underlying the IHME sc
 enarios. The first model\, dubbed CurveFit\, used strong assumptions to ge
 t useful predictions using extremely limited data\, and was used during Ma
 rch and April of 2020. The second model\, a data-driven SEIIR model\, was 
 put in play in June 2020\, and provides a flexible way to incorporate rela
 tionships with key drivers such as mobility\, mask use\, and pneumonia sea
 sonality. We describe the mathematics underlying both models\, and discuss
  the interplay between stability\, scalability\, and complexity in mathema
 tical modeling.\n\nFor Zoom meeting information please contact tim.hoheise
 l [at] mcgill.ca\n
DTSTART:20210412T200000Z
DTEND:20210412T210000Z
SUMMARY:Sasha Aravkin (University of Washington)
URL:/mathstat/channels/event/sasha-aravkin-university-
 washington-330277
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