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Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases
Lessons Learned From COVID-19
- 1st Edition - March 21, 2023
- Editors: Edgar N. Sanchez, Esteban A. Hernandez-Vargas, Jorge X. Velasco-Hernandez
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 9 5 0 6 4 - 0
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 0 6 5 - 7
Mathematical Modeling, Simulations, and Artificial Intelligence for Emergent Pandemic Diseases: Lessons Learned from COVID-19 includes new research, models and simulatio… Read more
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Request a sales quoteMathematical 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.
- Provides a comprehensive overview of the state-of-the-art in mathematical modeling and computational simulations for emerging pandemics
- Presents modeling techniques that go beyond COVID-19, and that can be applied to tailoring interventions to attenuate high death tolls
- Includes illustrations, tables and dialog boxes to explain highly specialized concepts and insights with complex algorithms, along with links to programming code
1. Modeling during an unprecedented pandemic
2. Global epidemiology and impact of the SARS-CoV-2 pandemic
3. Analysis of an ongoing epidemic: Advantages and limitations of COVID-19 modeling
4. On spatial heterogeneity of COVID-19 using shape analysis of pandemic curves
5. Pandemic response: Isolationism or solidarity?
6. Optimizing contact tracing: Leveraging contact network structure
7. Applications of deep learning in forecasting COVID-19 pandemic and county-level risk warning
8. COVID-19 population dynamics neural control from a complex network perspective
9. An agent-based model for COVID-19 and its interventions and impact in different social phenomena
10. Implementation of mitigation measures and modeling of in-hospital dynamics depending on the COVID-19 infection status
11. A mathematical model for the reopening of schools in Mexico
12. Mathematical assessment of the role of vaccination against COVID-19 in the United States
13. Ascertainment and biased testing rates in surveillance of emerging infectious diseases
14. Dynamical study of SARS-CoV-2 mathematical models under antiviral treatments
15. Statistical modeling to understand the COVID-19 pandemic
16. After COVID-19: Mathematical models, epidemic preparedness, and external factors in epidemic management
- No. of pages: 348
- Language: English
- Edition: 1
- Published: March 21, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780323950640
- eBook ISBN: 9780323950657
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Edgar N. Sanchez
In 1971, 1972, 1975 and 1976, he worked for different electrical engineering consulting companies in Bogota, Colombia. In 1974 he was a professor in the Electrical Engineering Department of UIS, Colombia. From January 1981 to November 1990, he worked as a researcher at the Electrical Research Institute, Cuernavaca, Mexico. He was a professor of the graduate program in electrical engineering at the Universidad Autonoma de Nuevo Leon (UANL), Monterrey, Mexico, from December 1990 to December 1996. Since January 1997, he has been with CINVESTAV-IPN (Guadalajara Campus, Mexico) as a Professor of Electrical Engineering in their graduate programs. His research interests are in neural networks and fuzzy logic as applied to automatic control systems. He has been the advisor of 21 Ph. D. theses and 40 M. Sc theses.
He was granted a USA National Research Council Award as a research associate at NASA Langley Research Center, Hampton, Virginia, USA (January 1985 to March 1987). He is also a member of the Mexican National Research System (promoted to highest rank, III, in 2005), the Mexican Academy of Science and the Mexican Academy of Engineering. He has published four books, more than 150 technical papers in international journals and conferences, and has served as a reviewer for different international journals and conferences. He has also been a member of many international conferences, both IEEE and IFAC.
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Esteban A. Hernandez-Vargas
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