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Mathematical Epidemiology and Fractional Calculus Applications

Springer Verlag, Singapore

ISBN 9789819221233

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Bibliografische Daten

Fachbuch

Buch. Hardcover

2026

10 s/w-Abbildungen, 28 Farbabbildungen.

In englischer Sprache

Umfang: 212 S.

Format (B x L): 15.5 x 23.5 cm

Verlag: Springer Verlag, Singapore

ISBN: 9789819221233

Weiterführende bibliografische Daten

Das Werk ist Teil der Reihe: Industrial and Applied Mathematics

Produktbeschreibung

This book presents cutting-edge mathematical models and advanced applications in epidemiology, enriched by the use of fractional calculus techniques. Highlighting sustainable applications that directly address topics related to SDG 3 (Good Health and Well-Being), it discusses novel research, methodologies and applications within the domains of mathematical epidemiology and fractional calculus, offering insights into disease modeling and analysis that have not been previously documented. This book contributes to the development of epidemiological mapping at the national level and lays a foundation for future investigations into the dynamics of infectious disease inflow. By deepening the understanding of disease transmission and spread, the findings support the formulation of effective public health strategies in anticipation of epidemic outcomes. Furthermore, this book provides a framework for evaluating the effectiveness of control measures, equipping health departments with actionable guidelines for disease prevention and eradication efforts. It offers a comprehensive exploration of mathematical techniques, making it a valuable resource for scientists and public health professionals seeking robust approaches to epidemic simulation and control. This book is intended for epidemiologists, biomedical engineers, researchers, and graduate students engaged in the study of mathematical modeling, dynamical systems, and fractional calculus. Additionally, the book appeals to those interested in advanced computational strategies and fractional calculus methods for epidemic forecasting, intervention and prevention.

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