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Epidemiological Modeling with Application to Covid-19 (Advanced Studies in Complex Systems)

Operational Research

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Description

Epidemiological Modeling with Application to Covid-19 presents information about statistical, numerical, stability, and theoretical analyses for nine different Covid-19 models. Those models are considered with classical and fractional derivatives, which is a generalization of the classical analysis. The authors present their newly introduced rate indicator function for the prediction of the waves of Covid-19 spread. Moreover, future prediction of Covid-19 spread is presented for some countries. The authors also provide a new approach to modeling epidemiological issues in general, which has been tested against the spread of COVID-19 in several nations. This book provides in-depth analysis of the spread of Covid-19, including discussion of theoretical and numerical results, including a novel modeling method called strength numbers that was created under the umbrella of acceleration, which provides a determiner of the power of disease spread. These significant characteristics might be the key to understanding and anticipating the spread of infections and diseases more generally. Provides in-depth analysis of the spread of Covid-19, including discussion of theoretical and numerical results Introduces a new concept called the rate indicator function for a new perspective on the spread of virological disease in epidemiology Presents a novel modeling method called strength numbers created under the umbrella of acceleration, which provides a determiner of the power of disease spread Provides a new approach to developing mathematical equations that may be used to show how an infectious disease spreads using the available starting data

Product Specifications

Format: paperback
ASIN: 0443238677
Category: Books > Subjects > Business, Finance & Law > Management > Operational Research
Domain: Amazon UK
Release Date: 05 December 2026
Listed Since: 02 August 2023

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Epidemiological Modeling with Application to Covid-19 (Advanced Studies in Complex Systems)

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