COVID19 tissue simulator

This model simulates viral dynamics of SARS-CoV-2 (coronavirus / COVID19) in a layer of epithelium and several submodels (such as single-cell response, pyroptosis death model, tissue-damage model, lymph node model and immune response). It is being rapidly prototyped and refined with community support (see below).

Please note that this is a stochastic model: for some simulation runs, you may see the immune system fail to respond. Users are encouraged to try the simulation multiple times.

This multiscale simulator combines several model components:

Please cite this project via the preprint:

M. Getz et al., Iterative community-driven development of a SARS-CoV-2 tissue simulator. bioRxiv 2020.04.02.019075, 2020, (Preprint). doi: 10.1101/2020.04.02.019075.

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Caveats and disclaimers

This model is under active development using rapid prototyping:

This model will be continually refined with input from the community, particularly experts in infectious diseases. The validation state will be updated as this progresses.

GUI Overview

Clicking the 'Run' button will use the specified parameters and start a simulation. When clicked, it creates an "Output" widget that can be clicked/expanded to reveal the progress of the simulation. When the simulation generates output files, they can be visualized in the "Out: Plots" tab. The "# cell frames" will be dynamically updated as those output files are generated by the running simulation. When the "Run" button is clicked, it toggles to a "Cancel" button that will terminate (not pause) the simulation.

Model details

This model is being rapidly prototyped. Biological and mathematical detail can be found at:

We request community help in estimating parameters and improving model assumptions at the link above.

This model and cloud-hosted demo are part of the education and outreach for the IU Engineered nanoBIO Node and the NCI-funded cancer systems biology grant U01CA232137. The models are built using PhysiCell: a C++ framework for multicellular systems biology.

Basic instructions

Modify parameters in the "Config Basics", "Microenvironment", "User Params", or "Cell Types" tabs. Click the "Run" button once you are ready.

To view the output results, click the "Out: Plots" tab, and move the slider bar to advance through simulation frames. Note that as the simulation runs, the "# cell frames" field will increase, so you can view more simulation frames.

Since there are multiple substrates defined in the Microenvironment, you can select a different one from the drop-down widget in the Plots tab. You can also provide fixed min,max values for the colormap range of values.

Note that you can download full simulation data for further exploration in your tools of choice.

About the software:

This model and cloud-hosted demo are part of the education and outreach for the IU Engineered nanoBIO Node and the NCI-funded cancer systems biology grant U01CA232137. The models are built using PhysiCell: a C++ framework for multicellular systems biology [1] for the core simulation engine and xml2jupyter [2] to create the graphical user interface (GUI).

  1. A. Ghaffarizadeh, R. Heiland, S.H. Friedman, S.M. Mumenthaler, and P. Macklin. PhysiCell: an open source physics-based cell simulator for 3-D multicellular systems. PLoS Comput. Biol. 14(2):e1005991, 2018. DOI: 10.1371/journal.pcbi.1005991.
  2. R. Heiland, D. Mishler, T. Zhang, E. Bower, and P. Macklin. xml2jupyter: Mapping parameters between XML and Jupyter widgets. Journal of Open Source Software 4(39):1408, 2019. DOI: 10.21105/joss.01408.