DATA SCIENCE FOR COVID-19

This course (IDST290-002) is a one-credit-hour course intended primarily for "Carolina Away" students in Fall 2020. The principal instructors are STOR graduate students Alexander Murph and Benjy Leinwand, with professors Serhan Ziya, Jan Hannig and myself serving as faculty advisors. Although the course has its own sakai page, restricted to registered students, materials that we intend for public viewing will be placed on this web page. Please check for updates!

The course will include a total of ten lectures by different speakers on different aspects of how data science has been used in research involving COVID-19. A public-view version of the syllabus is here. The talks scheduled for September 14 and November 16 will be public lectures and instructions how to access them will be posted nearer the dates. The remaining talks are not intended as public lectures but if you would like to join them, please send me an email and we will add you to the zoom invitation so long as places are available.

Feedback or requests: please email Richard Smith at rls "at" email "dot" unc "dot" edu.

Guest Lecture by Christl Donnelly: 9:20 am, Monday September 14.

Webinar Registration

Recommended background reading:

Report 1 - Estimating the potential total number of novel Coronavirus (2019-nCoV) cases in Wuhan City, China (January 2020)
Report 9 - Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand (March 16, 2020)
Estimates of the severity of coronavirus disease 2019: a model-based analysis (March 30, 2020)

Richard Smith's video about "Report 9" (15 minutes; made on March 25 2020)
Slides from the above video
Additional slides prepared for August 31 talk

Other papers and technical reports (most of these are likely to be on the reading list for the course!):

All Imperial College reports
IHME (University of Washington) paper
UNC/Duke group on epidemiological modeling for COVID-19 in North Carolina
Paper by Professor Ziya and colleagues about "flattening the curve" in North Carolina
Paul Delamater's webpage
The COV-IND project (nice example of COVID modeling in India; one of Jun Yan's webinar series) Webpage - Paper - eSIR Package in R
Paper by Peter Song and co-authors (methodogical basis for eSIR package, see above)
Policy Forum paper in Science (advocated a randomized experimentation approach to reopening)
Harvard paper on COVID-19 and air pollution
Special issue of Journal of Data Science
Wikipedia page about the SIR model
MAA article about the SIR model
IDM explanation of the SEIR model (linked from Paul Delamater's webpage)

Bin Yu's group at Berkeley:
xxxxxx Webpage
xxxxxxPreprint on Arxiv
xxxxxxVideo of July 24 talk

Other commentaries or useful links:

Schedule for Jun Yan's webinar series (includes videos)
Bill Gates Interview
World Economic Forum commentary
Harvard Global Health Institute
David Katz in the New York Times
John Ioannidis commentary