Using data during a pandemic: lessons learned from COVID-19 | Mike Osterholm | Nobel Conference

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Michael Osterholm, PhD, presenting at the 57th annual Nobel Conference: Big Data (R)Evolution at Gustavus Adolphus College in 2021.

"From the Village Watchman to Actionable Data: A Challenging Journey" = Lecture by Michael Osterholm, A Regents Professor and McKnight Presidential Endowed Chair in Public Health; Director, Center for Infectious Disease Research and Policy at the University of Minnesota

Data science can offer powerful tools for tracking the spread of an infectious disease and the effectiveness of vaccines, medical treatment or mitigation efforts. However, the quality of data available in a public health crisis like the COVID-19 pandemic is highly variable. The data obtained from poorly designed studies, or data from comprehensive disease surveillance or from well-designed studies, when disregarded by a public skeptical of science can greatly limit the public impact that data science offers.

How can data be most effectively used to both to reduce the health and economic impact of the current pandemic and to reduce the risk of future pandemics?

Michael Osterholm details the challenges of an implementing an effective use of data science in such public health crises both for this pandemic and for those of the future.
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#CIDRAP
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I challenge Dr. Osterholm to explain the following data from the Taiwanese Health Ministry:

October 1, 2021 -- COVID deaths (843). Post-injection deaths (824)
October 7, 2021 -- COVID deaths (844). Post-injection deaths (849)
October 12, 2021 -- COVID deaths (846). Post-injection deaths (871)
October 31, 2021 -- COVID deaths (847). Post-injection deaths (982)

LpCh