The Data Tells Me So

 As a closet (and old) Statistician, I am very disturbed about the data analysis going on around COVID-19 - the clinical trials, the data reported about breakthrough cases, the death data, hospitalizations, comorbidity, .. etc. etc.  And the old adage "The Devil is in the Detail" totally applies.   

Add to this Devil Data Detail problem is the Media Mania Mega horn creating confirming bias in the face of the large spectrum of human fear, uncertainty and doubt.  Then you have the desire to correlate political views into a divisive intellectual divide of blaming, shaming, and defaming each other.  

I recognize this is a global moving target of information, science, and parity.  Another global humanity test on the scale of World War survival impact.  How we respond globally and not nationally will be how we measure success.   India (who declared premature victory) and Brazil (who declared premature fearlessness) are now suffering.  The USA, UK and Israel now cautiously tempted to forecast freedom are in danger of their own nationalistic premature conclusions of what we believe "the science tells us".

Unfortunately the data is still in process.   150 million known (or estimated) positive COVID-19 cases and 3.157 million deaths is just a drop in the bucket of an estimated world population of 7.86 Billion (as of 4pm EST). This is still considered a small sample size to Statisticians.   

As a confirmed skeptic, the data I look at only provides "recent-cy bias" (if that's a word) for those declaring victory.  The only certainty I claim is that the healthcare science knows .... what it knows but doesn't know (or publish) what it doesn't know.   The famous Donald Rumsfeld quote that set the reporters into paradoxical philosophy - "There are Known Knowns".  

Please don't tell me - "The Science Tells Me So"; or "The Data Tells Me So";