/covid-variant-simulation

This is a project in the course Computational Life Sciences at the Baden-Wuerttemberg Cooperative State University Stuttgart (DHBW Stuttgart). Inspired by the rise of the novel corona-variant ‚Omikron‘, the main research question was: How do two similar variants behave when they are initially put in the same environment. Do they coexist or compete? An SEIRD-model is used, which was created with NetLogo. The stochastic exploration of data using R shows that the chance of emerging competition between two similar variants is very high.

Primary LanguageNetLogoOtherNOASSERTION

covid-variant-simulation

Disclaimer: This is just a script for data exploration. Code might not be idempotent.

Simulations and data can be found in the netlogo folder. The presentation is available as VirusVariants.pdf.

Abstract

This is a project in the course Computational Life Sciences at the Baden-Wuerttemberg Cooperative State University Stuttgart (DHBW Stuttgart). Inspired by the rise of the novel corona-variant ‚Omikron‘, the main research question was: How do two similar variants behave when they are initially put in the same environment. Do they coexist or compete? An SEIRD-model is used, which was created with NetLogo. The stochastic exploration of data using R shows that the chance of emerging competition between two similar variants is very high.

Getting started - set up renv

See https://www.rstudio.com/blog/renv-project-environments-for-r/.

In R-Console:

Setup renv:

  1. load renv library(renv) (make sure that renv is installed first install.packages("renv"))
  2. renv::restore()

To save the current env: renv::snapshot()

Execution time

Approx. 10 min for 2nd experiment