| Description |
1 online resource (635 pages) |
| Series |
Infosys Science Foundation series in Mathematical sciences |
|
Infosys Science Foundation series. Mathematical sciences.
|
| Contents |
Intro -- Preface -- Acknowledgements -- Contents -- About the Editors -- General Analysis -- Continued and Serious Lockdown Could Have Minimized Many Newly Transmitted Cases of Covid-19 in the U.S.: Wavelets, Deterministic Models, and Data -- 1 Introduction -- 2 Methods, Models and Data -- 3 Data -- 4 Results -- 5 Concluding Remarks -- References -- Dynamical Analysis of a Caputo Fractional Order SIR Epidemic Model with a General Treatment Function -- 1 Introduction -- 2 Mathematical Model and Preliminaries -- 3 Preliminaries -- 4 The Well-Posedness of the Model and Equilibria |
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4.1 Existence of Endemic Equilibrium -- 5 Local Stability Analysis -- 6 Global Stability Analysis -- 6.1 Infection-Free Equilibrium -- 6.2 Endemic Equilibrium -- 7 Numerical Simulations -- 8 Concluding Remarks -- References -- Protective Face Shield Effectiveness: Mathematical Modelling -- 1 Introduction -- 2 Practical Application of Face Shields -- 3 Mathematical Modelling -- 3.1 Euler Form of Equations -- 3.2 Lagrangian Form of Equations -- 3.3 Model Description -- 3.4 Numerical Methods -- 3.5 Computer Simulation -- 4 Full-Scale Experiment -- 5 Conclusion -- References |
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On the Evolution Equation for Modelling the Covid-19 Pandemic -- 1 Introduction -- 2 The Evolution Equation -- 2.1 The Classical Kolmogorov-Feller Equation -- 2.2 The Generalised Kolmogorov-Feller Equation -- 2.3 Orthonormal Memory Functions -- 2.4 Time Series Models -- 2.5 Logarithmic Scale Analysis -- 3 Random Walk Fields -- 4 Self-Affine Random Walk Fields -- 4.1 Solution for Eq. (7) -- 4.2 Solution for Eq. (8) -- 4.3 Random Walk Analysis -- 4.4 Example Results -- 5 The Bio-Dynamics Hypothesis -- 5.1 Self-affine Structures of a Virus -- 5.2 A Parametric Self-affine Model -- 5.3 Discussion |
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6 Summary, Conclusions and Future Research -- 6.1 Summary -- 6.2 Conclusions -- 6.3 Future Research -- References -- Modelling the Dynamics of Fake News Spreading Transmission During Covid-19 Through Social Media -- 1 Introduction -- 2 Methodology/Proposal -- 2.1 SIR Model for Fake News Transmission -- 2.2 Fake News Transmission Rate Through Different Social Media Platforms -- 2.3 Fake News Transmission Rate Among Users of Different Age Groups -- 2.4 Fake News Transmission Rate Among Users of Facebook from Different Countries -- 3 Results, Interpretation and Discussion -- 4 Conclusion |
| Summary |
This edited volume is a collection of selected research articles discussing the analysis of infectious diseases by using mathematical modelling in recent times. Divided into two parts, the book gives a general and country-wise analysis of Covid-19. Analytical and numerical techniques for virus models are presented along with the application of mathematical modelling in the analysis of their spreading rates and treatments. The book also includes applications of fractional differential equations as well as ordinary, partial and integrodifferential equations with optimization methods. Probability distribution and their bio-mathematical applications have also been studied. This book is a valuable resource for researchers, scholars, biomathematicians and medical experts |
| Bibliography |
References-Generalized Logistic Equations in Covid-Related Epidemic Models-1 Introduction-2 Logistic Coefficients Models-2.1 Computable Examples-3 Carrying Capacity Periodically Variable-3.1 Existence of Periodic Solution-3.2 Cosinusoidal Carrying Capacity-4 Periodic Harvesting-4.1 Global Features of the Solution-4.2 Closed-Form Integration and Examples-4.3 A Sample Problem-References-A Transition of Shared Mobility in Metro Cities-A Challenge Post-Lockdown Covid-19-1 Introduction-2 BPR Model-3 Data Analysis & Implementation-3.1 Data Description |
| Notes |
3.2 Model Application & Results |
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Online resource; title from PDF title page (SpringerLink, viewed October 12, 2021) |
| Subject |
COVID-19 (Disease) -- Mathematical models
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Covid-19 -- Modelos matemáticos
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COVID-19.
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Models matemàtics.
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| Genre/Form |
Llibres electrònics.
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| Form |
Electronic book
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| Author |
Agarwal, Praveen, editor.
|
|
Nieto, Juan J., editor.
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Ruzhansky, M. (Michael), editor.
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Torres, Delfim F. M., editor.
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| ISBN |
9789811624506 |
|
981162450X |
|
