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2022 | Book

Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation

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About this book

The book focuses on mathematical modelling of COVID-19 pandemic using the Susceptible, Infectious, and Recovered (SIR) model. The predictive modelling of the disease, with the exact facts and figures, provides a ground to reason about growing trends and its future trajectory. The book emphasizes on how the pandemic actually spreads out, lockdown impact analysis, and future course of actions based on mathematical calculations. Moreover, since COVID-19 spread outburst has been twice, the intensity studies and comparative analysis of the two waves of COVID-19 are another interesting feature of the book content. The book is a knowledge base for various researchers and academicians to dive into the detailing of the COVID spread (mathematical) model and understand how it could be explored to draw outcomes. To represent the factual information and analytical results effectively, graphical and diagrammatic representations have been appended at appropriate places. To keep the explanation simple and yet concrete, mathematical concepts have also been introduced; to carry out analysis to generate results for understanding the viral dynamics.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
According to WHO [2], the novel Coronavirus (Covid-19) epidemic began in Wuhan, China, on the 2nd of January, 2020, and was declared a Public Health Emergency of International Concern (PHEIC) on the 30th of January, 2020.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 2. Epidemic Studies and Mathematical Setup of SIR Model
Abstract
This chapter deals with a brief overview of the epidemic modelling of various viral spreads. The chapter discusses the prediction and trend analysis mechanisms using Machine Learning (ML), statistical, and Deep Learning (DL) approaches.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 3. Understanding and Analysing the Spread Pattern of Covid-19
Abstract
The chapter here defines the exponential trajectory of the growth dynamics of the disease. From infection growth trend to recovery and casualty growth rate, all follow an exponential rise with respect to time.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 4. SIR Model-Based Experimental Investigations over Covid-19
Abstract
In this chapter, simulations of real data have been conducted using the SIR model. The chapter also investigates the effect of lockdown for the four prominently Covid-19 hit areas of India. Afterwards, the estimated fraction of the population that will get infected is determined.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 5. Result Analysis of SIR-Based Covid-19 Model
Abstract
After collecting insights from Chap. 4, several facets of Covid-19 modelling have been explored in this chapter.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 6. Exploring Covid-19 Second Wave Dynamics Using SIR Epidemic Model
Abstract
This chapter illustrates the SIR model-based exploration of the second wave dynamics of Covid-19 for the same selected regions of India. The chapter explains the model-based variability in the growth trend, lockdown impact, vaccination, herd immunity, etc.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Chapter 7. Conclusions and Future Scope
Abstract
This chapter concludes and summarizes the analysis presented in the book. Further, the possibilities of exploration of study in various aspects have also been discussed in brief.
Rahul Saxena, Mahipal Jadeja, Vikrant Bhateja
Backmatter
Metadata
Title
Exploring Susceptible-Infectious-Recovered (SIR) Model for COVID-19 Investigation
Authors
Rahul Saxena
Mahipal Jadeja
Vikrant Bhateja
Copyright Year
2022
Publisher
Springer Nature Singapore
Electronic ISBN
978-981-19-4175-7
Print ISBN
978-981-19-4174-0
DOI
https://doi.org/10.1007/978-981-19-4175-7

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