Mathematical Analysis of Infectious Diseases updates on the mathematical and epidemiological analysis of infectious diseases. Epidemic mathematical modeling and analysis is important, not only to understand disease progression, but also to provide predictions about the evolution of disease. One of the main focuses of the book is the transmission dynamics of the infectious diseases like COVID-19 and the intervention strategies. It also discusses optimal control strategies like vaccination and plasma transfusion and their potential effectiveness on infections using compartmental and mathematical models in epidemiology like SI, SIR, SICA, and SEIR.
The book also covers topics like: biodynamic hypothesis and its application for the mathematical modeling of biological growth and the analysis of infectious diseases, mathematical modeling and analysis of diagnosis rate effects and prediction of viruses, data-driven graphical analysis of epidemic trends, dynamic simulation and scenario analysis of the spread of diseases, and the systematic review of the mathematical modeling of infectious disease like coronaviruses.
1. 15.1 Introduction - p. 259 2. 15.2 Preliminaries - p. 261 3. 15.3 Nonlinear model of HIV infection for CD8+T cells - p. 263 4. 15.4 Existence of solution - p. 265 5. 15.5 Special solution via iteration approach - p. 268 6. 15.6 Application of the HATM to solve the model - p. 272 7. 15.7 Control of accuracy by the CESTAC method and the CADNA library - p. 276 8. 15.8 Numerical results - p. 278 9. 15.9 Conclusion - p. 283 10. References - p. 283 11. Chapter 16. Existence of solutions of modified fractional integral equation models for endemic infectious diseases - p. 287 12. Chapter 17. Numerical solution of a fractional epidemic model via general Lagrange scaling functions with bibliometric analysis - p. 305 13. Index - p. 321
Mathematical Analysis of Infectious Diseases updates on the mathematical and epidemiological analysis of infectious diseases. Epidemic mathematical modeling and analysis is important, not only to understand disease progression, but also to provide predictions about the evolution of disease. One of the main focuses of the book is the transmission dynamics of the infectious diseases like COVID-19 and the intervention strategies. It also discusses optimal control strategies like vaccination and plasma transfusion and their potential effectiveness on infections using compartmental and mathematical models in epidemiology like SI, SIR, SICA, and SEIR.
The book also covers topics like: biodynamic hypothesis and its application for the mathematical modeling of biological growth and the analysis of infectious diseases, mathematical modeling and analysis of diagnosis rate effects and prediction of viruses, data-driven graphical analysis of epidemic trends, dynamic simulation and scenario analysis of the spread of diseases, and the systematic review of the mathematical modeling of infectious disease like coronaviruses.
1. 15.1 Introduction - p. 259 2. 15.2 Preliminaries - p. 261 3. 15.3 Nonlinear model of HIV infection for CD8+T cells - p. 263 4. 15.4 Existence of solution - p. 265 5. 15.5 Special solution via iteration approach - p. 268 6. 15.6 Application of the HATM to solve the model - p. 272 7. 15.7 Control of accuracy by the CESTAC method and the CADNA library - p. 276 8. 15.8 Numerical results - p. 278 9. 15.9 Conclusion - p. 283 10. References - p. 283 11. Chapter 16. Existence of solutions of modified fractional integral equation models for endemic infectious diseases - p. 287 12. Chapter 17. Numerical solution of a fractional epidemic model via general Lagrange scaling functions with bibliometric analysis - p. 305 13. Index - p. 321
