


eBook/Digital Version available from:

Score: 86 

Charting the Next Pandemic: Modeling Infectious Disease Spreading in the Data Science Age 

ISBN: 9783319932897,
209 pages,
Soft Cover ISBN10: 3319932896 

Copyright: 
2019 

Edition: 
1st 

Author: 
Pastore y Piontti, Ana; Perra, Nicola; Rossi, Luca; Samay, Nicole; Vespignani, Alessandro 

Specialties:

Epidemiology
, Infectious Disease
, Public Health 

Publisher: 
Springer 

List Price: 
$79.99 

Google: 






At A Glance

This book provides an introduction to the computational and complex systems modeling of the global spreading of infectious diseases. The latest developments in the area of contagion processes modeling are discussed, and readers are exposed to real world examples of datamodel integration impacting the decisionmaking process. Recent advances in computational science and the increasing availability of realworld data are making it possible to develop realistic scenarios and realtime forecasts of the global spreading of emerging health threats. The first part of the book guides the reader through sophisticated complex systems modeling techniques with a nontechnical and visual approach, explaining and illustrating the construction of the modern framework used to project the spread of pandemics and epidemics. Models can be used to transform data to knowledge that is intuitively communicated by powerful infographics and for this reason, the second part of the book focuses on a set of charts that illustrate possible scenarios of future pandemics. The visual atlas contained allows the reader to identify commonalities and patterns in emerging health threats, as well as explore the wide range of models and data that can be used by policy makers to anticipate trends, evaluate risks and eventually manage future events. Charting the Next Pandemic puts the reader in the position to explore different pandemic scenarios and to understand the potential impact of available containment and prevention strategies. This book emphasizes the importance of a global perspective in the assessment of emerging health threats and captures the possible evolution of the next pandemic, while at the same time providing the intelligence needed to fight it. The text will appeal to a wide range of audiences with diverse technical backgrounds. 
Reviewer:

Eric Kontowicz,
MPH
(University of Iowa College of Public Health)


Range

Question

Score

110 
Are the author's objectives met? 
8 
110 
Rate the worthiness of those objectives. 
10 
15 
Is this written at an appropriate level? 
5 
15 
Is there significant duplication? (1=significant, 5=insignificant) 
3 
15 
Are there significant omissions? (1=significant, 5=insignificant) 
5 
15 
Rate the authority of the authors. 
5 
15 
Are there sufficient illustrations? 
5 
15 
Rate the pedagogic value of the illustrations. 
3 
15 
Rate the print quality of the illustrations. 
3 
15 
Are there sufficient references? 
5 
15 
Rate the currency of the references. 
4 
15 
Rate the pertinence of the references. 
3 
15 
Rate the helpfulness of the index. 
4 
15 
If important in this specialty, rate the physical appearance of the book 
4 
110 
Is this a worthwhile contribution to the field? 
10 
110 
If this is a 2nd or later edition, is this new edition needed? 
N/A 


Reviewer:

Eric Kontowicz,
MPH
(University of Iowa College of Public Health)


Description

This book describes what data is needed and how to think about structuring it to enable predictive modeling of select infectious diseases. This is further positioned within the context of the Global Epidemic and Mobility (GLEAM) framework. 

Purpose

The purpose is to explain how realworld data, through the use of simulation, can help predict/forecast the global spread of infectious disease. As the authors note in the introduction, their aim is to be able to forecast the spread of infectious disease in a way similar to weather forecasting. While not everyone needs to know how to perform all these simulations, a general understanding of how they are performed can help in appropriate data collection and accurate interoperations of results. 

Audience

According to the authors, this book is intended for nonexperts in the field. However, readers need to have a basic understanding of infectious diseases and their general biology. The authors use too much technical jargon when talking about the model building. They have vast experience in modeling infectious diseases and working with large amounts of data. 

Features

The book covers what it takes, in terms of both data and modeling, to chart the next pandemic. It uses model pandemics of historical context to show the value of the GLEAM framework in forecasting the next pandemic. The infectious diseases used in this book are influenza, coronaviruses, and Ebola virus, with a final summary of the computational modeling of "Disease X". The book does a particularly good job of supplementing the text with high quality figures, which are the true highlight. It also does a very good job of explaining what each figure is showing and how. This is particularly important for the second part of the book, which is mainly driven by figures. The only shortcoming is the change in the legend on heat maps. For example, figures 2.1 and 2.2 have legends that are counterintuitive to what would be expected. Normally the darker area indicates more densely populated or more risk, but the opposite is true for these figures. This is further complicated in Figure 2.12, where the darker areas have higher density of either physicians or hospital beds. 

Assessment

This book is rather informative about what it takes to appropriately model the rise and spread of an infectious disease. It is useful in highlighting what types of data are needed to model these complex disease processes and how to properly incorporate these variables into model building. 







