SEIRD model to study the asymptomatic growth during COVID-19 pandemic in India

TL;DR

This study uses a modified SEIRD model to analyze the role of asymptomatic individuals in COVID-19 spread in India, highlighting the importance of testing and quarantine in controlling symptomatic cases.

Contribution

Introduces a modified SEIRD model to estimate asymptomatic infection dynamics and assess their impact on COVID-19 spread in India.

Findings

Asymptomatic infections significantly increase total COVID-19 cases.

Quarantining asymptomatic individuals can substantially reduce symptomatic cases.

Model predictions align with reported data, validating the approach.

Abstract

According to the current perception, symptomatic, presymptomatic, and asymptomatic infectious persons can infect the healthy population susceptible to the SARS-Cov-2. More importantly, various reports indicate that the number of asymptomatic cases can be several-fold higher than the reported symptomatic cases. In this article, we take the reported cases in India and various states within the country till September 1, as the specimen to understand the progression of the COVID-19. Employing a modified SEIRD model, we predict the spread of COVID-19 by the symptomatic as well as asymptomatic infectious population. Considering reported infection primarily due to symptomatic we compare the model predicted results with the available data to estimate the dynamics of the asymptomatically infected population. Our data indicate that in the absence of the asymptomatic infectious population, the number of symptomatic cases would have been much less. Therefore, the current progress of the symptomatic infection can be reduced by quarantining the asymptomatically infectious population via extensive or random testing. This study is motivated strictly towards academic pursuit; this theoretical investigation is not meant for influencing policy decisions or public health practices.