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http://hdl.handle.net/10773/32314| Title: | Analysis of infectious disease problems (Covid-19) and their global impact |
| Author: | Agarwal, Praveen Nieto, Juan J. Ruzhansky, Michael Torres, Delfim F. M. |
| Keywords: | Epidemic modelling Covid-19 Model prediction Pandemic influenza Reproductive number Mathematical epidemiology Statistical models Dynamical models Agent-based models Machine learning models |
| Issue Date: | 2021 |
| Publisher: | Springer |
| Abstract: | This book is a collection of selected research articles discussing the analysis of infectious diseases by using mathematical modelling in recent times. Divided into two parts, the book gives a general and country-wise analysis of Covid-19. Analytical and numerical techniques for virus models are presented along with the application of mathematical modelling in the analysis of their spreading rates and treatments. The book also includes applications of fractional differential equations as well as ordinary, partial and integro-differential equations with optimization methods. Probability distribution and their bio-mathematical applications have also been studied. This book is a valuable resource for researchers, scholars, biomathematicians and medical experts. |
| URI: | http://hdl.handle.net/10773/32314 |
| DOI: | 10.1007/978-981-16-2450-6 |
| ISBN: | 978-981-16-2449-0 |
| Appears in Collections: | CIDMA - Livro DMat - Livro SCG - Livro |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| [461]book_COVID-19_Global_Impact.pdf | 18.98 MB | Adobe PDF |  |
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