Open-SIR is an Open Source Python project for modelling pandemics and infectious diseases using Compartmental Models, such as the widely used Susceptible-Infected-Removed (SIR) model.

The current stage of the software is Alpha.

• Model the dynamics of infectious diseases
• Parameter fitting
• Calculation of confidence intervals
• CLI for interfacing with non Python environments (Bash, Node.JS, Matlab, etc).

For the API reference and examples of usage, please check the online documentation.

So far, Open-SIR provides an implementation of the SIR model and the novel SIR-X model developed by Maier and Dirk from the Robert Koch Institut.

The figure below illustrates how Open-SIR can be used to fit compartmental models to real data of coronavirus SARS-CoV-2 reported cases in a population of interest.

This is an example of using Open-SIR to fit the model developed by Maier and Brockmann, 2020, Containment explains subexponential growth in confirmed cases of recent COVID-19 in Mainland China, Science, DOI: 10.1126/science.abb4557 to Guangdong data.

Welcome to Open-Sir! Install Open-SIR using pip

git clone https://github.com/open-sir/open-sir.git
cd open-sir
pip install .

Please follow Getting Started to get your hands on Open-SIR.

• José Álamos - RIOT-OS
• Felipe Huerta - PhD Student at Imperial College London

See also the list of contributors who participated in this project.

This project is licensed under the MIT License - see the LICENSE file for details.

• Robert Koch Institut for the clear explanation of SIR and SIR-X models.

Thanks goes to these wonderful people (emoji key):

José Alamos 💻 📖 🚧

Felipe Huerta 💻 📖 ✅

Sebastián Salata 💻 🚧 🚇

Leandro Lanzieri 💻 🚧

This project follows the all-contributors specification. Contributions of any kind are welcome!