Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases

The contributions by epidemic modeling experts describe how mathematical models and statistical forecasting are created to capture the most important aspects of an emerging epidemic.Readers will discover a broad range of approaches to address questions, such as

• Can we control Ebola via ring vaccination strategies?
  
• How quickly should we detect Ebola cases to ensure epidemic control?
  
•  What is the likelihood that an Ebola epidemic in West Africa leads to secondary outbreaks in other parts of the world?  
• When does it matter to incorporate the role of disease-induced mortality on epidemic models?
•  What is the role of behavior changes on Ebola dynamics? 
• How can we better understand the control of cholera or Ebola using optimal control theory?
• How should a population be structured in order to mimic the transmission dynamics of diseases such as chlamydia, Ebola, or cholera?
• How can we objectively determine the end of an epidemic?
• How can we use metapopulation models to understand the role of movement restrictions and migration patterns on the spread of infectious diseases?
  
• How can we capture the impact of household transmission using compartmental epidemic models?
  
• How could behavior-dependent vaccination affect the dynamical outcomes of epidemic models? 
  

This book will be of interest to researchers in the field of mathematical epidemiology, as well as public health workers.

Preface
1  A Reality of Its Own
3  Modeling the Impact of Behavior Change on the Spread of Ebola
3  A model for coupled outbreaks contained by behavior change
4  Real-time assessment of the international spreading risk associated with the 2014 West African Ebola    Outbreak
5  Modeling the case of early detection of Ebola virus disease
6  Modeling ring vaccination strategies to control Ebola virus disease epidemics
7  Estimation of the number of sickbeds during Ebola epidemics using optimal control theory
8  Inverse problems and Ebola virus disease using an age of infection model
9  Assessing the Efficiency of Movement
10 Restriction as a Control Strategy of Ebola
11 Patch models of EVD transmission dynamics
12 From bee species aggregation to models of disease avoidance: The \emph{Ben-Hur} effect}
13 Designing Public Health Policies to Mitigate the Adverse Consequences of Rural-Urban Migration via      Meta-Population Modeling
14 Age of Infection Epidemic Models
15 Optimal Control of Vaccination in an Age-Structured Cholera Model
16 A Multi-risk Model for Understanding the Spread of Chlamydia
17 The 1997 Measles Outbreak in Metropolitan São Paulo, Brazil: Strategic Implications of Increasing        Urbanization
18 Methods to determine the end of an infectious disease epidemic: A short review
19 Statistical considerations in infectious disease randomized controlled trials
20 Epidemic models with and without mortality: when does it matter?
21 Capturing Household Transmission in Compartmental Models of Infectious Disease
22 Bistable endemic states in a Susceptible-Infectious-Susceptible model with behavior-dependent Vaccination
Index

Gerardo Chowell is an associate professor and a Second Century Initiative Scholar (2CI) in the School of Public Health at Georgia State University in Atlanta. His research program includes the development and application of quantitative approaches for understanding the transmission dynamics and control of infectious diseases including influenza, Ebola, and dengue fever. His work has appeared in high-impact journals including The New England Journal of Medicine, PLOS Medicine, and BMC Medicine, and has been cited by major media outlets including the Washington Post and TIME magazine.