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Titlebook: An Introduction to Mathematical Epidemiology; Maia Martcheva Textbook 2015 Springer Science+Business Media New York 2015 Data Fitting.Epid

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Vector-Borne Diseases,ne disease model is recast as a single delay-differential equation model. The simple model is studied both analytically and numerically, and it is shown to exhibit Hopf bifurcation and chaos. A couple of more complex ODE or DDE models of vector-borne diseases are studied.
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Analysis of Complex ODE Epidemic Models: Global Stability,illustrated on the SIR model with isolation. The concept of backward bifurcation is introduced and illustrated on an SEI model with standard incidence. Castillo-Chavez and Song Theorem for detecting backward bifurcation in higher dimensions is introduced and illustrated on the SEI example.
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Age-Structured Epidemic Models,ions are studied. The chapter also introduces and studies an SIS age-structured model. Intracohort, intercohort, and mixed incidence are discussed. The reproduction number in the age-structured case is derived. Numerical methods for age-structured models are included.
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Immuno-Epidemiological Modeling,ng data, the chapter argues that the transmission rate is not a linear function of the viral load. The epidemiological reproduction number and prevalence of HIV are derived and studied in terms of the within-host viral load. In addition, a nested immuno-epidemiological model with immune response in the within-host model is introduced and studied.
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Introduction,r of definitions of key epidemiological concepts are given. The chapter introduces a brief history of the study and modeling of infectious diseases, highlighting the seminal contributions of Sir Ronald Ross. Finally, the chapter gives a description of the modeling process in biology and a list of th
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