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Quantitative Biology > Populations and Evolution

arXiv:2006.00045 (q-bio)
COVID-19 e-print

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[Submitted on 29 May 2020]

Title:Estimating Hidden Asymptomatics, Herd Immunity Threshold and Lockdown Effects using a COVID-19 Specific Model

Authors:Shaurya Kaushal, Abhineet Singh Rajput, Soumyadeep Bhattacharya, M. Vidyasagar, Aloke Kumar, Meher K. Prakash, Santosh Ansumali
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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 lockdown and resulting spatial migration of population due to announcement of lockdown. A method is presented for estimating the model parameters from real-world data. It is shown that increase of infections slows down and herd immunity is achieved when symptomatic patients are 4-6\% of the population for the European countries we studied, when the total infected fraction is between 50-56 \%. 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.
Subjects: Populations and Evolution (q-bio.PE); Physics and Society (physics.soc-ph)
Cite as: arXiv:2006.00045 [q-bio.PE]
  (or arXiv:2006.00045v1 [q-bio.PE] for this version)
  https://doi.org/10.48550/arXiv.2006.00045

Submission history

From: Santosh Ansumali [view email]
[v1] Fri, 29 May 2020 19:27:42 UTC (1,547 KB)
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