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Understanding Covid-19 transmission: what the data suggests about how the disease spreads

Understanding Covid-19 transmission: what the data suggests about how the disease spreads

FromLinear Digressions


Understanding Covid-19 transmission: what the data suggests about how the disease spreads

FromLinear Digressions

ratings:
Length:
25 minutes
Released:
Mar 23, 2020
Format:
Podcast episode

Description

Covid-19 is turning the world upside down right now. One thing that’s extremely important to understand, in order to fight it as effectively as possible, is how the virus spreads and especially how much of the spread of the disease comes from carriers who are experiencing no or mild symptoms but are contagious anyway. This episode digs into the epidemiological model that was published in Science this week—this model finds that the data suggests that the majority of carriers of the coronavirus, 80-90%, do not have a detected disease. This has big implications for the importance of social distancing of a way to get the pandemic under control and explains why a more comprehensive testing program is critical for the United States.

Also, in lighter news, Katie (a native of Dayton, Ohio) lays a data-driven claim for just declaring the University of Dayton flyers to be the 2020 NCAA College Basketball champions.

Relevant links:
https://science.sciencemag.org/content/early/2020/03/13/science.abb3221
Released:
Mar 23, 2020
Format:
Podcast episode

Titles in the series (100)

Linear Digressions is a podcast about machine learning and data science. Machine learning is being used to solve a ton of interesting problems, and to accomplish goals that were out of reach even a few short years ago.