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Differential Equations and Population Dynamics I: Introductory Approaches
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Differential Equations and Population Dynamics I: Introductory Approaches

Differential Equations and Population Dynamics I: Introductory Approaches

Arnaud / Griette Ducrot

458 pages, parution le 20/06/2022

Résumé

This book provides an introduction to the theory of ordinary differential equations and its applications to population dynamics.

Part I focuses on linear systems. Beginning with some modeling background, it considers existence, uniqueness, stability of solution, positivity, and the Perron-Frobenius theorem and its consequences.

Part II is devoted to nonlinear systems, with material on the semiflow property, positivity, the existence of invariant sub-regions, the Linearized Stability Principle, the Hartman-Grobman Theorem, and monotone semiflow.

Part III opens up new perspectives for the understanding of infectious diseases by applying the theoretical results to COVID-19, combining data and epidemic models. Throughout the book the material is illustrated by numerical examples and their MATLAB codes are provided.

Bridging an interdisciplinary gap, the book will be valuable to graduate and advanced undergraduate students studying mathematics and population dynamics.


Part I Linear Differential and Difference Equations : 1 Introduction to Linear Population Dynamics.- 2 Existence and Uniqueness of Solutions.- 3 Stability and Instability of Linear Systems.- 4 Positivity and Perron-Frobenius Theorem.- Part II NonLinear Differential : 5 Nonlinear Differential Equation.- 6 The Linearized Stability Principle and the Hartman-Grobman Theorem.- 7 Positivity and Invariant Sub-Regions.- 8 Monotone Semiflows.- Part III Applications to Epidemic Models : 9 Understanding and Predicting Unreported Cases in the 2019-nCov Epidemic Outbreak in Wuhan, China, and the Importance of Major Public Health Interventions.- 10 The COVID-19 Outbreak in Japan: Unreported Age-Dependent Cases.- 11 Clarifying Predictions for COVID-19 from Testing Data: The Example of New York State.- 12 SI Epidemic Model Applied to COVID-19 Data in Mainland China.- 13 A Robust Phenomenological Approach to Investigating COVID-19 Data for France.- 14 What Can We Learn From COVID-19 Data By Using Epidemic Models With Unidentified Infectious Cases?.- 15 Supplementary material.

Arnaud Ducrot is professor of mathematics at the University Le Havre Normandie, France. His research interests include analysis, dynamical systems and mathematical aspects of population dynamics and the natural sciences.

Quentin Griette is an associate professor in mathematics at the University of Bordeaux, France. His areas of expertise include ordinary differential equations, reaction-diffusion systems and the numerical computation of their solutions.

Zhihua Liu is a professor of mathematics at Beijing Normal University, China. Her research interests include differential equations, dynamical systems and applications in epidemics and population dynamics.

Pierre Magal is professor of mathematics at the University of Bordeaux, France. His research interests include differential equations, dynamical systems, numerical simulations and mathematical biology.

Caractéristiques techniques

  PAPIER
Éditeur(s) Springer
Auteur(s) Arnaud / Griette Ducrot
Parution 20/06/2022
Nb. de pages 458
EAN13 9783030981358

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