The COVID- 19 pandemic has wrecked havoc on human society, globally. Phylogeny analyses have revealed that the original SARS CoV-2 strain in India has undergone over 81 mutations and diverged into 6 different clades within the country. Based on these mutations, some clades are more infectious or more lethal than the others.
We attempt to understand the unique evolution of the disease at the population level by first understanding viral evolution at the patient level. We first characterise the viral - immune interactions within a host, and optimise the parameters using clinical data, to explore how patient level heterogeneity impacts clinical outcomes. Next, we embed this model into a network based-model for population scale transmission dynamics. Our goal is to incorporate patient heterogeneity as well as heterogeneity in viral strains in this multiscale model to unveil how this virus evolved.