Description
| Product ID: | 9780323950640 |
| Product Form: | Paperback / softback |
| Country of Manufacture: | NL |
| Title: | Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases |
| Subtitle: | Lessons Learned From COVID-19 |
| Authors: | Author: Esteban A. Hernandez-Vargas, Edgar N. Sanchez, Jorge X. Velasco-Hernandez |
| Page Count: | 348 |
| Subjects: | Medical and health informatics, Medical bioinformatics, Applied mathematics, Applied mathematics |
| Description: | Select Guide Rating Mathematical Modeling, Simulations, and Artificial Intelligence for Emergent Pandemic Diseases: Lessons Learned from COVID-19 includes new research, models and simulations developed during the COVID-19 pandemic into how mathematical methods and practice can impact future response. Chapters go beyond forecasting COVID-19, bringing different scale angles and mathematical techniques (e.g., ordinary differential and difference equations, agent-based models, artificial intelligence, and complex networks) which could have potential use in modeling other emergent pandemic diseases. A major part of the book focuses on preparing the scientific community for the next pandemic, particularly the application of mathematical modeling in ecology, economics and epidemiology. Readers will benefit from learning how to apply advanced mathematical modeling to a variety of topics of practical interest, including optimal allocations of masks and vaccines but also more theoretical problems such as the evolution of viral variants. |
| Imprint Name: | Academic Press Inc |
| Publisher Name: | Elsevier Science & Technology |
| Country of Publication: | GB |
| Publishing Date: | 2023-03-30 |
