COVID-19 in India: An Interdisciplinary Study of Demographic, Structural, and Epidemiological Factors

Abstract

In this study, we carried out a comprehensive analysis of SARS-CoV-2 mutations and their spread in India over the past two years of the pandemic (27th Jan 2020 – 8th Mar 2022). The analysis covers four important timelines, viz., the early phase, followed by the first, second, and third waves of the pandemic in the country. Phylogenetic analysis of the isolates indicated multiple independent entries of coronavirus in the country, while principal component analysis identified few state-specific clusters. Genetic analysis of isolates during the first year revealed that though lockdown helped in controlling the spread of the virus, region-specific sets of shared mutations were developed during the early phase due to local community transmissions. We thus report the evolution of state-specific subclades, namely, I/GJ20A (Gujarat), I/MH-2 (Maharashtra), I/Tel-A-20B, I/Tel-B-20B (Telangana), and I/AP-20A (Andhra Pradesh) that explain the demographic variation in the impact of COVID-19 across states. In the second year of the pandemic, India faced an aggressive second wave while the third wave was quite mild in terms of severity. Here we also discuss the prevalence and impact of different lineages and Variants of Concerns/Interests, viz., Delta, Kappa, Omicron, etc. observed during this period. From the genetic analysis of mutation spectra of Indian isolates, the insights gained into its transmission, geographic distribution, containment, and impact are discussed. Next, we evaluated the impact of some important India-specific mutations on protein function using structure and network-based analysis. Finally, we performed epidemiological modeling of the dominant variants in India during the Second (Delta and Kappa) and Third (Omicron) waves of the pandemic using multi-strain SEIR models to estimate the transmission factor (β) for the different variants. This interdisciplinary study provides valuable insights into the demographic, structural, and epidemiological factors influencing the spread of COVID-19 in India. The findings can inform and aid policymakers and public health officials in responding to future waves of COVID-19 or any other pandemic caused by a novel pathogen.