Epidemiology101 VS covid-19

Trying to put the finishing touches on a Python package [1] for epidemic modeling using Compartmental models. This grew out of a series of blog posts I started writing during the pandemic [2] based on my professional experience in epidemic modeling in a previous life where I was the lead developer for a state of the art global epidemic model [3].

[1] http://github.com/DataForScience/epidemik

[2] https://github.com/DataForScience/Epidemiology101

[3] https://www.gleamviz.org/explore.html

No worries, Google does tend to do a good job of monopolizing attention in whatever they do and Epidemic Modeling is... complicated. Probably much more complicated than pretty much any other kind of modeling since people have the bad habit of thinking and acting in whatever way they want (sometimes with the explicit purpose of breaking your model :).

Now, if you want to see the real-world state-of-the-art epidemic modeling on a global scale, checkout GLEaM/GLEaMViz https://www.gleamviz.org/ (full disclaimer, in a previous life I was the lead developer).

And if you're interested in a basic intro, you can also checkout my (somewhat neglected) series of blog posts from the pandemic days: https://github.com/DataForScience/Epidemiology101

Plotly Dash is a opensource, cross-platform & free. It's also free and super easy to host on something like Heroku for small projects. Throw in another tool here: Jupyter Lab - you can experiment in the latter, build some amazing dataviz yourself using tools like Plotly Express, even add in some interactivity with widgets - then, when you're ready you can refactor your code into a dashboard in Plotly Dash. With a little code & knowledge, you can build something Tableau-like fairly rapidly, and you have the full power of python & data science libraries at your fingertips (BI tools have python integration, but it's very clunky). They have a growing open source community of libraries (built with react & python) and examples/galleries, so there's lots out there to copy. To illustrate this, here's a dashboard built in Plotly over a couple of nights at the start of the pandemic: https://github.com/nite/covid-19 - this should illustrate how quick & easy it is to build something tableau-like, and how to host it in docker/heroku. There's a jupyter Lab notebook in the notebooks directory, and a link to the dashboard live in the readme (takes a min to spin up if no-one has hit it recently)