https://github.com/microprediction/pandemic
A 2d contagion model with commuting modeled as regime switching Ornstein-Uhlenbeck walks on the plane
https://github.com/microprediction/pandemic
Last synced: about 1 month ago
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A 2d contagion model with commuting modeled as regime switching Ornstein-Uhlenbeck walks on the plane
- Host: GitHub
- URL: https://github.com/microprediction/pandemic
- Owner: microprediction
- Created: 2020-04-06T00:34:55.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2020-11-12T13:54:54.000Z (over 4 years ago)
- Last Synced: 2025-03-25T03:13:01.947Z (about 1 month ago)
- Language: Python
- Homepage:
- Size: 3.82 MB
- Stars: 8
- Watchers: 4
- Forks: 7
- Open Issues: 5
-
Metadata Files:
- Readme: README.md
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README
# Pandemic
An agent model in which commuting, compliance, testing and contagion parameters drive
infection in a population of thousands of millions. Agents follow Ornstein-Uhlenbeck processes
in the plane and collisions drive transmission. Results are stored at
SwarmPrediction.com for further analysis, and can be retrieved by anyone.
### Motivaton
Covered in this [post](https://www.linkedin.com/pulse/pandemic-minimalist-2d-ornstein-uhlenbeck-model-peter-cotton-phd) with
the followup [here](https://www.linkedin.com/pulse/dear-new-zealand-heres-how-simulate-covid-19-all-your-cotton-phd/) where possible
improvements are also discussed and acknowledgements are made. See also the SwarmPrediction.Com [list of articles](www.swarmprediction.com/articles.html). The author is not an epidemiologist. The model expresses no opinions
on the health aspects of COVID-19. The model offers a novel motion model with some interesting
analytic properties also discussed in the [article](https://www.linkedin.com/pulse/dear-new-zealand-heres-how-simulate-covid-19-all-your-cotton-phd/) referenced
above and presented in a more technical [working paper](https://www.overleaf.com/read/sgjvfxydcwpk) shared on Overleaf.
### Basic Usage
pip install pandemic
>> from pandemic import run
>> run()
See also examples of
library use and examples of using the public
database of simulations generated by this model.
### Other entry points.
- pandemic.simulation.simulate is the main routine
- pandemic.client offers an alternative in object oriented style
### Modifying
See pandemic/client.py for examples of extending the newer style to include data storage, lockdown and so forth.
#### Docker
Pandemic can be run in a docker container.
```
docker run xtellurian/pandemic
```
### Crowd-sourced surrogate model
See SwarmPrediction.com for an explanation of
a SETI-like project to crowd-source a surrogate model.
### Basic elements of the model
Covered in detail in this [article](https://www.linkedin.com/pulse/dear-new-zealand-heres-how-simulate-covid-19-all-your-cotton-phd/). As noted some analytical properties of
special cases of the model are discussed in a [working paper](https://www.overleaf.com/read/sgjvfxydcwpk).
### Contributing
Opinions and issues are most welcome.