Mathematical Sciences

Title :

A SEIR model to estimate the effect of pharmaceutical and non-pharmaceutical interventions on the spread of COVID-19

Area of research :

COVID-19 Research, Life Sciences & Biotechnology, Mathematical Sciences

Focus area :

Mathematical modelling for COVID-19

Principal Investigator :

Prof Ramanathan Srinivasan, Indian Institute of Technology (IIT) Madras

Timeline Start Year :


Contact info :


Executive Summary :

A SEIR model, with an easy-to-use software interface, will be developed. It will account for age distribution, the effect of treatment and the difference in propagation by symptomatic and asymptomatic individuals and use a range of parameters to obtain the average and upper and lower limits of estimated values.


A software interface with SEIR model, incorporating age distribution, pharmaceutical (medical treatment) and non-pharmaceutical (lockdown, social distancing and so on) interventions, and symptomatic/asymptomatic modes of transmission was created. A working version of the software, created in May 2021, is available on the link, Existing models use the basic SEIR model or its variants but cannot handle the effect of both pharmaceutical (like treatment) and non-pharmaceutical interventions (like lockdown) together. Similarly, the spread of COVID-19 by symptomatic and asymptomatic patients should be handled separately. The proposed model accounts for these variations as well. Data over a period of time is available, and this can help in narrowing down the parameters such as basic reproduction number under lockdown and unlock phases. The software utility can also be used to predict what will be the loss if lockdown was not implemented or if treatment was not provided.

Organizations involved