COVID-19 Analysis in 4D

Many variables are at work in the COVID-19 pandemic.  Analyses in 4 dimensions help visualize them.  In markets, such structures use prices as objective functions.  As the virus seeks to replicate, its goal is to infect hosts.  We see each infection as a case.

At right, we plot countries’ populations against their COVID-19 cases on April 28, 2020.  Each dot signifies one of the 163 nations in the study.  Unchecked, only the size of the global community caps the number of cases.  However, we observe a yellow line marking the disease’s Infection Limit on that date.  That line is well-correlated (98.6% R^2); there is little chance it came about accidentally (P-value of 8.21E-10).  Countries on or close to that frontier are worse off than those far away from it.

The green side plane represents an equation derived from the population (set to 720,000,000), density, and GDP per capita (P-values in turn of 3.13E-35, 0.68%, and 5.90E-35).  While we would expect infection rates to go up with density and population, its strong relationship to GDP is unexpected.  Wealthier nations have more resources to fight such outbreaks, but it appears their travel patterns more than offset that.

#covid19 #covid19research #covid19analytics