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DTSTART:20200308T070000
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DTSTART:20191103T060000
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DTSTART;TZID=America/Toronto:20200604T160000
SEQUENCE:0
TRANSP:TRANSPARENT
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URL:https://uwaterloo.ca/statistics-and-actuarial-science/events/department
 -seminar-grace-yi-department-statistical-and
SUMMARY:Department Seminar by Grace Yi\, Department Statistical and Actuari
 al\nSciences\, Department of Computer Science University of Western Ontari
 o
CLASS:PUBLIC
DESCRIPTION:CAN THE REPORTED COVID-19 DATA TELL US THE TRUTH? SCRUTINIZING 
 THE\nDATA FROM THE MEASUREMENT ERROR MODELS PERSPECTIVE\n\n---------------
 ----------\n\nThe mystery of the coronavirus disease 2019 (COVID-19) and t
 he lack of\neffective treatment for COVID-19 have presented a strikingly n
 egative\nimpact on public health. While research on COVID-19 has been ramp
 ing\nup rapidly\, a very important yet overlooked challenge is on the\nqua
 lity and unique features of COVID-19 data. The manifestations of\nCOVID-19
  are not yet well understood.  The swift spread of the virus\nis largely 
 attributed to its stealthy transmissions in which infected\npatients may b
 e asymptomatic or exhibit only flu-like symptoms in the\nearly stage. Due 
 to the limited test resources and a good portion of\nasymptomatic infectio
 ns\, the confirmed cases are typically\nunder-reported\, error-contaminate
 d\, and involved with substantial\nnoise. If the drastic effects of faulty
  data are not being addressed\,\nanalysis results of the COVID-19 data can
  be seriously biased. \n\nIn this talk\, I will discuss the issues induced
  from faulty COVID-19\ndata and how they may challenge inferential procedu
 res. I will\ndescribe a strategy of employing measurement error models to 
 address\nthe error effects. Sensitivity analyses will be conducted to quan
 tify\nthe impact of faulty data for different scenarios.  In addition\, I
 \nwill present a website of COVID-19 Canada\n(https://covid-19-canada.uwo.
 ca/)\, developed by the team co-led by Dr.\nWenqing He and myself\, which 
 provides comprehensive and real-time\nvisualization of the Canadian COVID-
 19 data.\n\nPLEASE NOTE: This seminar will be given online through Webex.
  To\njoin\, please follow this link: VIRTUAL SEMINAR BY GRACE YI\n[https
 ://uwaterloo.webex.com/uwaterloo/onstage/g.php?MTID=ed7e69860646da98203364
 2dadc0cdb10].
DTSTAMP:20260410T163430Z
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