MODERATOR NOTE: coronavirus resources & updates: https://wolfr.am/coronavirus
The notebook here is also (without output) placed in GitHub: https://github.com/antononcube/SystemModeling/blob/master/Projects/Coronavirus-propagation-dynamics/WL-notebooks/Basic-experiments-workflow-for-simple-epidemiological-models.nb .
Many thanks for the effort you put into this. I also much enjoy your website and learn a lot from it.
Regards, Robert
Thank your kind words! I put a fix into the notebook -- I forgot to run it with the most recent package updates.
Nice live-stream today!
-- you have earned Featured Contributor Badge
Your exceptional post has been selected for our editorial column Staff Picks http://wolfr.am/StaffPicks and Your Profile is now distinguished by a Featured Contributor Badge and is displayed on the Featured Contributor Board. Thank you, keep it coming, and consider contributing to the The Notebook Archive!
Thanks, Dan!
Probably refined models can be made that have more population compartments and have time-dependent rates that reflect the medical observations and enacted policies.
My work is posted now: [Notebook] Epidemiological Models for Influenza and COVID-19
I'll get a a look at your repo later today.
Very nice!
Our models are very similar, right down to some of the assumptions! I see that your fits suffer from the same problems as mine: a long exponential tail on the confirmed cases (aka, infected) and the recovered rises too slowly.
Bob
Thank you for your comment, Bob!
The purpose of that notebook is to show the general workflow with a simple model. There are multiple ways to make the SEI2R model more comprehensive. The directions I have in mind can be found in the repository Coronavirus propagation dynamics.
