Computational Modeling of the COVID-19 Disease: Numerical ODE Analysis with R Programming

Description

The book is intended for readers who are interested in learning about the use of computer-based modelling of the COVID-19 disease. It provides a basic introduction to a five-ordinary differential equation (ODE) model by providing a complete statement of the model, including a detailed discussion of the ODEs, initial conditions and parameters, followed by a line-by-line explanation of a set of R routines (R is a quality, scientific programming system readily available from the Internet). The reader can access and execute these routines without having to first study numerical algorithms and computer coding (programming) and can perform numerical experimentation with the model on modest computers. Contents Preface Chapter 1. Single Area ODE Model (1) Introduction (1.1) USA model (1.1.1) Susceptibles (1.1.2) Asymptomatic infecteds (1.1.3) Symptomatic infecteds (1.1.4) Recovereds (1.1.5) Deaths (1.2) R routines (1.2.1) Main program (1.2.2) ODE routine (1.2.3) Numerical, graphical output (1.2.4) Parameter variation (1.3) Summary and conclusions References Appendix A1 Chapter 2. Detailed Analysis of the ODE Model (2) Introduction (2.1) Time derviatives of the ODE model (2.1.1) Main program (2.1.2) ODE routine (2.1.3) Numerical, graphical output (2.1.4) Analysis of ODE LHS, RHS terms (2.2) Summary and Conclusions Chapter 3. Variants of the Basic ODE Model (3) Introduction (3.1) Limited susceptibles infection (3.1.1) Main program (3.1.2) ODE routine (3.1.3) Numerical, graphical output (3.2) Summary and conclusions Chapter 4. Postulated Vaccine/Therapeutic Drug Treatment (4) Introduction (4.1) ODE model with parameter time variation (4.1.1) Main program (4.1.2) ODE routine (4.1.3) Numerical, graphical output (4.2) Summary and conclusions Chapter 5. ODE Model with Delays (5) Introduction (5.1) ODE model with delays (5.1.1) Main program (5.1.2) ODE routine (5.1.3) Numerical, graphical output 5.2) Summary and conclusions References Index