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Computational Modeling of Infectious Disease: With Applications in Python

Autor Chris von Csefalvay
en Limba Engleză Paperback – 21 feb 2023
Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cutting-edge computational methods. From simple S(E)IR models, and through time series analysis and geospatial models, this book is both a guided tour through the computational analysis of infectious diseases and a quick-reference manual. Chapters are accompanied by extensive practical examples in Python, illustrating applications from start to finish.  This book is designed for researchers and practicing infectious disease forecasters, modelers, data scientists, and those who wish to learn more about analysis of infectious disease processes in the real world.

  • Connects computational infectious disease analysis to state-of-the-art data science
  • Conveys ideas on epidemiology and infectious disease modeling in a clear, accessible way
  • Provides code examples to elucidate best practices
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Specificații

ISBN-13: 9780323953894
ISBN-10: 0323953891
Pagini: 476
Dimensiuni: 152 x 229 x 24 mm
Greutate: 0.74 kg
Editura: ELSEVIER SCIENCE

Public țintă

Researchers and practicing infectious disease forecasters/modelers; data scientists integrating a model of an infectious disease into their existing frameworks; computational scientists who need to understand the underlying logic of infectious disease models; Infectious disease specialists who need solid quantitative grounding for their research
Graduate students in virology, infectious disease medicine, quantitative biology, quantitative ecology, and epidemiology; infectious disease forecasters at public health authorities, hospitals, regulatory bodies, etc.

Cuprins

1. Introduction 2. Simple compartmental models 3. Modeling host factors 4. Host-vector and multi-host systems 5. Multi-pathogen systems 6. Modeling the control of infectious disease 7. Temporal dynamics of infectious disease 8. Spatial models of infectious disease 9. Agent-based models