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Mathematical Analysis for Transmission of COVID-19 (Mathematical Engineering)
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Description
Product Description This book describes various mathematical models that can be used to better understand the spread of novel Coronavirus Disease 2019 (COVID-19) and help to fight against various challenges that have been developed due to COVID-19. The book presents a statistical analysis of the data related to the COVID-19 outbreak, especially the infection speed, death and fatality rates in major countries and some states of India like Gujarat, Maharashtra, Madhya Pradesh and Delhi. Each chapter with distinctive mathematical model also has numerical results to support the efficacy of these models. Each model described in this book provides its unique prediction policy to reduce the spread of COVID-19. This book is beneficial for practitioners, educators, researchers and policymakers handling the crisis of COVID-19 pandemic. From the Back Cover This book describes various mathematical models that can be used to better understand the spread of novel Coronavirus Disease 2019 (COVID-19) and help to fight against various challenges that have been developed due to COVID-19. The book presents a statistical analysis of the data related to the COVID-19 outbreak, especially the infection speed, death and fatality rates in major countries and some states of India like Gujarat, Maharashtra, Madhya Pradesh and Delhi. Each chapter with distinctive mathematical model also has numerical results to support the efficacy of these models. Each model described in this book provides its unique prediction policy to reduce the spread of COVID-19. This book is beneficial for practitioners, educators, researchers and policymakers handling the crisis of COVID-19 pandemic. About the Author Prof. Nita H Shah received her Ph.D. in Statistics from Gujarat University in 1994. From February 1990 till now, Prof. Nita is HOD of the Department of Mathematics in Gujarat University, India. She is Postdoctoral Visiting Research Fellow of the University of New Brunswick, Canada. Prof. Nita's research interests include inventory modeling in supply chain, robotic modeling, mathematical modeling of infectious diseases, image processing, dynamical systems and its applications. Prof. Nita has completed 3 UGC sponsored projects. Prof. Nita has published 13 monographs, 5 textbooks and 475+ peer-reviewed research papers. Five edited books are prepared for IGI Global and Springer with Co-Editor as Dr. Mandeep Mittal. Her papers are published in high impact Elsevier, Inderscience and Taylor and Francis journals. By the Google Scholar, the total number of citations is over 3129 and the maximum number of citations for a single paper is over 174. The H-index is 78 up to November 19, 2020 and i-10 index is 73. She has guided 28 Ph.D. students and 15 M.Phil. students till now. Eight students are pursuing research for their Ph.D. degree and one Postdoctoral Fellow of D. S. Kothari, UGC. She has traveled in USA, Singapore, Canada, South Africa, Malaysia and Indonesia for giving talks. She is Vice-President of Operational Research Society of India. She is a council member of Indian Mathematical Society. Dr. Mandeep Mittal started his career in the education industry in 2000 with Amity Group. Currently, he is working as Head and Associate Professor in the Department of Mathematics, Amity Institute of Applied Sciences, Amity University Uttar Pradesh, Noida. He earned his post doctorate from Hanyang University, South Korea, 2016, Ph.D. (2012) from the University of Delhi, India, and postgraduation in Applied Mathematics from IIT Roorkee, India (2000). He has published more than 70 research papers in the International Journals and International conferences. He authored one book with Narosa Publication on C language and edited five research books with IGI Global and Springer. He is a series editor of Inventory Otimization, Springer Singapore Pvt. Ltd. He has been awarded Best Faculty Award by the Amity School of Engineering and Technol
Product Specifications
- Format
- Hardcover
- ASIN
- 9813362634
- Domain
- Amazon UK
- Release Date
- 02 April 2021
- Listed Since
- 21 November 2020
Barcode
No barcode data available
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