Version 1
: Received: 26 May 2021 / Approved: 27 May 2021 / Online: 27 May 2021 (10:33:34 CEST)
How to cite:
Banerjee, S. Understanding the Dynamics of Pathogenic Infection in a Population. Preprints2021, 2021050664. https://doi.org/10.20944/preprints202105.0664.v1
Banerjee, S. Understanding the Dynamics of Pathogenic Infection in a Population. Preprints 2021, 2021050664. https://doi.org/10.20944/preprints202105.0664.v1
Banerjee, S. Understanding the Dynamics of Pathogenic Infection in a Population. Preprints2021, 2021050664. https://doi.org/10.20944/preprints202105.0664.v1
APA Style
Banerjee, S. (2021). Understanding the Dynamics of Pathogenic Infection in a Population. Preprints. https://doi.org/10.20944/preprints202105.0664.v1
Chicago/Turabian Style
Banerjee, S. 2021 "Understanding the Dynamics of Pathogenic Infection in a Population" Preprints. https://doi.org/10.20944/preprints202105.0664.v1
Abstract
In this article we have presented a new perception of herd immunity threshold (HIT) which considers that only a “band of population” are susceptible to any pathogenic infection. This is termed as the “effective herd immunity threshold” (EHIT) and the progression of the disease (caused by this pathogenic infection) is mainly determined by this EHIT value. We have argued here that this EHIT value (considering the immunity band picture in the population) will be substantially lower than the estimated canonical HIT values obtained from various existing models. We propose that the actual prediction of the disease progression should now be calculated using the EHIT values.
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
