PyRoss is a numerical library for mathematical modelling of infectious disease in Python. The library supports structured compartment models formulated as systems of differential equations. Currently, these are the SIR, SEIR, SEAIR, and SEAIRQ models.
The library was developed to model the outbreak of the novel coronavirus COVID-19 and to assess the age-structured impact of social distancing measures in India.
The library is named after Sir Ronald Ross, doctor, mathematician and poet. In 1898 he made "the great discovery" in his laboratory in Calcutta "that malaria is conveyed by the bite of a mosquito". He won the Nobel Prize in 1902 and laid the foundations of the mathematical modelling of infectious diseases.
ArcGIS Dashboard Link: https://arcg.is/O1eaC
We have tuned some aspects of the model to bring the results on ArcGIS dashboard & fit the model with current data. And as well as introducing a lag of 10 days which is due to factors, like delay in reporting, testing & individual patient reasons. So the model shows the actual situation which was 10 days back. The model gives a base line picture or best case scenario, hence asymptomatic are also considered symptomatic, with a provision of keeping them separate, when sufficient data is available.
- Assumptions: homogenous mixture of population, 10 day lag, more info. in paper.
- Factors included: single & multiple lockdown’s effect on spread, social distancing, different age groups have different interaction with virus, contact patterns of age groups at work, home etc.
Note: We recommend consulting an epidemiologist, for future tweaks or insights taken, from the model.
(Both SEIR & SIR implementation have 10 days lag, modification.)
Kindly, raise an issue on GitHub, for any doubts.
Clone (or download) the repository.
create a new conda env. or clone the ArcGIS Pro default env., while using the the environment file.
then in the python command prompt, go to the cloned directory and type:
python setup.py installThe authors are part of The Rapid Assistance in Modelling the Pandemic (RAMP) taskforce. They can be contacted at: rs2004@cam.ac.uk (Rajesh Singh) and ra413@cam.ac.uk (R. Adhikari) or via the main GitHub Repo.
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Age-structured impact of social distancing on the COVID-19 epidemic in India, Rajesh Singh and R. Adhikari, arXiv:2003.12055.
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See the author's examples at examples folder .
Age and social contact data that is needed to construct structured compartment models can be found at the following links:
Age structure: Population Pyramid website.
Contact structure: Projecting social contact matrices in 152 countries using contact surveys and demographic data, Kiesha Prem, Alex R. Cook, Mark Jit, PLOS Computational Biology, (2017) DOI, Supporting Information Text and Supporting Information Data.
The list of COVID-19 cases is obtained from the Worldometer website.
This code is released under the MIT license.