# Infection Kinetics of Covid-19: Is Lockdown a Potent Containment Tool?

Source: [Infection Kinetics of Covid-19: Is Lockdown a Potent Containment Tool?](<https://www.sota2.com/research/paper/68fa3cc71e209131ce8dd406>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:54:18.951Z

Authors: Amit k Chattopadhyay, Debajyot Choudhury, Goutam Ghosh, Bidisha Kundu, Sujit Kumar Nath

Published: 2020-09-11T08:29:03.000Z

## Abstract

Covid-19 is raging a devastating trail with the highest mortality-to-infected ratio ever for a pandemic. Lack of vaccine and therapeutic has rendered social exclusion through lockdown as the singular mode of containment. Harnessing the predictive powers of Machine Learning within a 6 dimensional infection kinetic model, depicting interactive evolution of 6 infection stages - healthy susceptible ($H$), predisposed comorbid susceptible ($P$), infected ($I$), recovered ($R$), herd immunized ($V$) and mortality ($D$) - the model, PHIRVD, provides the first accurate mortality prediction of 18 countries at varying stages of strategic lockdown, up to 30 days beyond last data training. PHIRVD establishes mortality-to-infection ratio as the correct pandemic descriptor, substituting reproduction number, and highlights the importance of early and prolonged but strategic lockdown to contain secondary relapse.   Significance Statement:   1. Accurate prediction of the day-by-day mortality profiles of 18 countries, 30 days beyond the last data of data training.   2. Precise quantification of the impact of early-vs-later lockdown impositions.   3. Accurate prediction of secondary relapse timelines/   4. Establishment of mortality-to-infected ratio as the correct pandemic descriptor substituting the popular choice of reproduction number, a proven failure in predicting future infection kinetics and secondary surge.   The outcomes have potential to redefine healthy policy landscape, particularly in light of secondary relapse and possible future SARS-COV/Ebola group incursion.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2009.05280>)

[PDF](<https://arxiv.org/pdf/2009.05280.pdf>)