Research

Mathematical Sciences

Title :

Modelling and prediction of COVID-19 outbreak: Analysing possible effects of lockdown, testing and urbanicity

Area of research :

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

Focus area :

Mathematical modelling for COVID-19

Principal Investigator :

Dr Minerva Mukhopadhyay, Assistant Professor, Indian Institute of Technology (IIT) Kanpur

Timeline Start Year :

2020

Contact info :

Details

Executive Summary :

This study aims to investigate the transmission mechanism of COVID-19 in India at both the national and state levels, with an analysis on possible effects of various measures, such as testing facility, urban connectivity, age, sex, temperature, etc.

Outcome/Output:

Developed model to study the spread of COVID-19 by branching process. However, it requires an estimate of the number of asymptomatic patients. After an extensive literature survey, no reliable method of estimating the number of asymptomatic patients from the reported cases, were obtained. The usual trend is to apply grid search to get the best fitting parameters, and estimate the asymptomatic population accordingly. Further, the model considers the number of asymptomatic population as a part of the data, obtaining the same by maximising the model would lead to double usage of data, which is statistically prohibitive. Therefore, it is estimated that the number of asymptomatic patients from an independent compartmental model using metadata only.

Organizations involved