SAIR Model

About this site

This web application provides a district-wise projection from COVID19 situation in India based on a Susceptible-Asymptomatic-Infected-Recoverd (SAIR) (in arXiv) epidemiology model. We are providing data as service to the community.

Epidemiological Model of COVID-19 Growth

The district-wise projections for COVID-19 carrier patients comes from a model that accounts for both hidden asymptomatics and even lockdown effects on the spread of COVID19. The details of this model are publicly accessible (in arXiv, in Phys. Rev. E), and some of the work is currently under scientific peer-review. Some salient features of this model are:

• The explicit use of asymptomatics in the epidemiological model.
• Solution of the inverse problem of estimating parameters.
• Ability to account for lockdowns.

Indian COVID-19 Data

This model uses the patient database from covid19india.org, which is a crowd-sourced (sanitised and self-correcting) public data base of reported COVID-19 positive cases in the country.

Web Team

• Mrunal Nasery
• Salvatore Arcidiacono
• Soumyadeep Bhattacharya

Calculations Team

• Samarth Agrawal
• Shaurya Kausal

Data and preliminary calculations team

• Akshay Chandran
• Abhineet Singh Rajput

Faculty Members

• Associate Prof. Santosh Ansumali, Jawaharalal Nehru Center for Advanced Scientific Research, CTO,Sankhya Sutra Pvt. Ltd.
• Assistant Prof. Aloke Kumar, Indian Institute of Sciences
• Assistant Prof. Meher Prakash, Jawaharalal Nehru Center for Advanced Scientific Research, VNIR Biotechnologies Pvt Ltd (http://vnir.life)
• Prof. P. Sunthar, Indian Institute of Technology, Bombay

A note on the peak

A local peak of infections is obtained only when the reproduction ratio, as plotted above, is less than 1. The reproduction ratio is regulated by the prescribed degree of interpersonal interactions in the population defined by their allowed activities, movement, and (non)adherence to social-distancing defines the peak. If the human behavior changes, the peak changes as well, unless the herd-immunity has been achieved with more than 50% of the population infected.

References

• Shaurya Kaushal, Abhineet Singh Rajput, Soumyadeep Bhattacharya, M. Vidyasagar, Aloke Kumar, Meher K. Prakash, Santosh Ansumali, Estimating Hidden Asymptomatics, Herd Immunity Threshold and Lockdown Effects using a COVID-19 Specific Model, https://arxiv.org/abs/2006.00045, Available at, https://github.com/COVID19Models/SAIRmodel
• Meher K. Prakash, Shaurya Kaushal, Soumyadeep Bhattacharya, Akshay Chandran, Aloke Kumar, and Santosh Ansumali, Minimal and adaptive numerical strategy for critical resource planning in a pandemic, Phys. Rev. E 102, 021301(R)
• Meher K Prakash, Quantitative COVID-19 infectiousness estimate correlating with viral shedding and culturability suggests 68% pre-symptomatic transmissions, https://www.medrxiv.org/content..

Disclaimer

The projections provided on the website are only indicatve, based on a mathematical model. While the model is adaptive and takes into account the developments in the recent past, there is no guarantee that the predictions will be accurate. The maintainers of the website, or individuals and organisations involved in its developement do not take any responsibility for differences between projected values now and the actuals that are realised in the future.