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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.
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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.