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Computational Modeling of Infectious Disease: With Applications in Python provides an illustrated compendium of tools and tactics for analyzing infectious diseases using cuttin… Read more
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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
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
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