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Computational Epidemiology

Data-Driven Modeling of COVID-19

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  • 328 pages
  • 12 hours of reading

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Focusing on the intersection of mathematical epidemiology and computational modeling, this textbook addresses the complexities of outbreak dynamics and control, particularly in the context of COVID-19. It offers insights into modern tools such as data science and machine learning, equipping readers with the skills to model and simulate nonlinear dynamic systems. The content is designed to enhance understanding of pandemic-related challenges, making it a vital resource for those interested in public health and disease management.

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Computational Epidemiology, Ellen Kuhl

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Released
2022
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