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Estimating the herd immunity threshold by accounting for the hidden asymptomatics using a COVID-19 specific model

Kaushal, S and Rajput, AS and Bhattacharya, S and Vidyasagar, M and Kumar, A and Prakash, MK and Ansumali, S (2020) Estimating the herd immunity threshold by accounting for the hidden asymptomatics using a COVID-19 specific model. In: PLoS ONE, 15 (12).

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Official URL: https://dx.doi.org/10.1371/journal.pone.0242132

Abstract

A quantitative COVID-19 model that incorporates hidden asymptomatic patients is developed, and an analytic solution in parametric form is given. The model incorporates the impact of lock-down and resulting spatial migration of population due to announcement of lock-down. A method is presented for estimating the model parameters from real-world data, and it is shown that the various phases in the observed epidemiological data are captured well. It is shown that increase of infections slows down and herd immunity is achieved when active symptomatic patients are 10-25 of the population for the four countries we studied. Finally, a method for estimating the number of asymptomatic patients, who have been the key hidden link in the spread of the infections, is presented. © 2020 Kaushal et al.

Item Type: Journal Article
Publication: PLoS ONE
Publisher: Public Library of Science
Additional Information: Copyright to this article belongs to Public Library of Science
Keywords: analytic method; Article; coronavirus disease 2019; herd immunity; home quarantine; human; incidence; mathematical model; pandemic; population migration; virus transmission; virus virulence
Department/Centre: Division of Mechanical Sciences > Mechanical Engineering
Date Deposited: 20 Jan 2021 10:17
Last Modified: 20 Jan 2021 10:17
URI: http://eprints.iisc.ac.in/id/eprint/67619

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