Identifiability and Observability in Epidemiological Models Identifiability and Observability in Epidemiological Models
SpringerBriefs on PDEs and Data Science

Identifiability and Observability in Epidemiological Models

A Primer

Nik Cunniffe والمزيد
    • ‏39٫99 US$
    • ‏39٫99 US$

وصف الناشر

This book introduces the concepts of identifiability and observability in mathematical epidemiology, as well as those of observers’ constructions. It first exposes and illustrates on several examples the mathematical definitions and properties of observability and identifiability. A chapter is dedicated to the well-known Kermack McKendrick model, for which the complete analysis of identifiability and observability is not available in the literature. Then, several techniques of observer constructions, in view of online estimation of state and parameters, are presented and deployed on several models. New developments relevant for applications in epidemiology are also given. Finally, practical considerations are discussed with data and numerical simulations related to models previously analysed in the book.

The book will be appealing to epidemiological modellers and mathematicians working on models in epidemiology.This book contributes to Sustainable Development Goal 3 (SDG3): Good Health and Well Being.

النوع
علم وطبيعة
تاريخ النشر
٢٠٢٤
٢ يوليو
اللغة
EN
الإنجليزية
عدد الصفحات
١٢٠
الناشر
Springer Nature Singapore
البائع
Springer Nature B.V.
الحجم
٤٫٧
‫م.ب.‬
Time-Delayed Linear Quadratic Optimal Control Problems Time-Delayed Linear Quadratic Optimal Control Problems
٢٠٢٥
Control in Finite and Infinite Dimension Control in Finite and Infinite Dimension
٢٠٢٤
Notes on Tug-of-War Games and the p-Laplace Equation Notes on Tug-of-War Games and the p-Laplace Equation
٢٠٢٤
Optimal Transport and Applications to Geometric Optics Optimal Transport and Applications to Geometric Optics
٢٠٢٣
Time Dependent Phase Space Filters Time Dependent Phase Space Filters
٢٠٢٣
A Variational Theory of Convolution-Type Functionals A Variational Theory of Convolution-Type Functionals
٢٠٢٣