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Title: Analysis of infectious disease problems (Covid-19) and their global impact
Author: Agarwal, Praveen
Nieto, Juan J.
Ruzhansky, Michael
Torres, Delfim F. M.
Keywords: Epidemic modelling
Model prediction
Pandemic influenza
Reproductive number
Mathematical epidemiology
Statistical models
Dynamical models
Agent-based models
Machine learning models
Issue Date: 2021
Publisher: Springer
Abstract: This book is a collection of selected research articles discussing the analysis of infectious diseases by using mathematical modelling in recent times. Divided into two parts, the book gives a general and country-wise analysis of Covid-19. Analytical and numerical techniques for virus models are presented along with the application of mathematical modelling in the analysis of their spreading rates and treatments. The book also includes applications of fractional differential equations as well as ordinary, partial and integro-differential equations with optimization methods. Probability distribution and their bio-mathematical applications have also been studied. This book is a valuable resource for researchers, scholars, biomathematicians and medical experts.
DOI: 10.1007/978-981-16-2450-6
ISBN: 978-981-16-2449-0
Appears in Collections:CIDMA - Livro
DMat - Livro
SCG - Livro

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