Understanding statistics in epidemics and pandemics: lessons learned from COVID-19

Published on October 31, 2021   35 min

A selection of talks on Microbiology

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0:00
Hello, my name is Sarah Ransdell and I'm a professor in the department of Health Science. I'm at Nova Southeastern University, it's in Fort Lauderdale, Florida, in the United States. I'm happy to talk to you today about understanding statistics in epidemics and pandemics, especially some lessons we've learned coming through COVID-19.
0:28
First I'll preview what I'm going to speak about. The first thing I want to discuss - because it's important to understanding statistics - is the difference between an epidemic and a pandemic. The second thing I want to talk about is: where do we get our information? Secondary science sources are based on primary sources. Primary sources are straight from the horse's mouth, that is, the researcher who conducted the study. Secondary science sources are those that have been - I won't say simplified, but made a little bit more palatable - for the general science, and generally literate, population. Third, I'll talk about how sources differ in quality and purpose. That's our main objective in the information age, not to find information but to know when the information we find is good. Fourth, I'll talk about reading secondary science sources, the ones that you and I and most of us with an internet connection can find any day, using things like .gov or .org. Next I'll talk about the important distinction between statistics for description, and statistics for hypothesis testing, or inferential statistics. Next I'll talk about the rather tricky business of reading tables and figures, and finally I'll end with an example. I'll talk about how we read primary science sources, those of us in health science and all the sciences in all the departments all over the world, and how that becomes a permanent internet record called a DOI or 'document object identifier'. I'll let you peek a little bit into what science media looks like, so that I can conclude by saying how science media is very different from social media. Social media is for social things, and science media is for science things.

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