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Mathematics of Public Health

Overview of attention for book
Cover of 'Mathematics of Public Health'

Table of Contents

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    Book Overview
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    Chapter 1 Mathematical Models: Perspectives of Mathematical Modelers and Public Health Professionals
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    Chapter 2 Discovering First Principle of Behavioural Change in Disease Transmission Dynamics by Deep Learning
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    Chapter 3 Understanding Epidemic Multi-wave Patterns via Machine Learning Clustering and the Epidemic Renormalization Group
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    Chapter 4 Contact Matrices in Compartmental Disease Transmission Models
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    Chapter 5 An Optimal Control Approach for Public Health Interventions on an Epidemic-Viral Model in Deterministic and Stochastic Environments
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    Chapter 6 Modeling Airborne Disease Dynamics: Progress and Questions
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    Chapter 7 Modeling Mutation-Driven Emergence of Drug-Resistance: A Case Study of SARS-CoV-2
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    Chapter 8 A Categorical Framework for Modeling with Stock and Flow Diagrams
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    Chapter 9 Agent-Based Modeling and Its Trade-Offs: An Introduction and Examples
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    Chapter 10 Mathematical Assessment of the Role of Interventions Against SARS-CoV-2
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    Chapter 11 Long-Term Dynamics of COVID-19 in a Multi-strain Model
Attention for Chapter 8: A Categorical Framework for Modeling with Stock and Flow Diagrams
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Readers on

mendeley
3 Mendeley
Summary
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Chapter title
A Categorical Framework for Modeling with Stock and Flow Diagrams
Chapter number 8
Book title
Mathematics of Public Health
Published in
Fields Institute Communications, January 2023
DOI 10.1007/978-3-031-40805-2_8
Book ISBNs
978-3-03-140804-5, 978-3-03-140805-2
Authors

Baez, John C., Li, Xiaoyan, Libkind, Sophie, Osgood, Nathaniel D., Redekopp, Eric

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 67%
Unknown 1 33%
Readers by discipline Count As %
Unspecified 2 67%
Unknown 1 33%

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