One cannot watch or read about the news these days without hearing
about the models for COVID-19 or the testing that must occur to
approve vaccines or treatments for the disease. The purpose of
Mathematical Modeling in the Age of a Pandemic is to shed some
light on the meaning and interpretations of many of the types of
models that are or might be used in the presentation of analysis.
Understanding the concepts presented is essential in the entire
modeling process of a pandemic. From the virus itself and its
infectious rates and deaths rates to explain the process for
testing a vaccine or eventually a cure, the author builds,
presents, and shows model testing. This book is an attempt, based
on available data, to add some validity to the models developed and
used, showing how close to reality the models are to predicting
"results" from previous pandemics such as the Spanish flu in 1918
and more recently the Hong Kong flu. Then the author applies those
same models to Italy, New York City, and the United States as a
whole. Modeling is a process. It is essential to understand that
there are many assumptions that go into the modeling of each type
of model. The assumptions influence the interpretation of the
results. Regardless of the modeling approach the results generally
indicate approximately the same results. This book reveals how
these interesting results are obtained.
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