Modeling to Inform Infectious Disease Control: 1st Edition (Hardback) book cover

Modeling to Inform Infectious Disease Control

1st Edition

By Niels G. Becker

Chapman and Hall/CRC

208 pages | 43 B/W Illus.

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Hardback: 9781498731065
pub: 2015-04-28
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Effectively Assess Intervention Options for Controlling Infectious Diseases

Our experiences with the human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and Ebola virus disease (EVD) remind us of the continuing need to be vigilant against the emergence of new infectious diseases. Mathematical modeling is increasingly used in the management of infectious disease control as a way to assess interventions relatively quickly, cheaply, and safely. Modeling to Inform Infectious Disease Control shows readers how to take advantage of these models when developing strategies to mitigate infectious disease transmission.

The book presents a way of modeling as well as modeling results that help to guide the effective management of infectious disease transmission and outbreak response. It discusses the requirements for preventing epidemics and ways to quantify the impact of preventative public health interventions on the size and dynamics of an epidemic. The book also illustrates how data are used to inform model choice.

Accessible to readers with diverse backgrounds, this book explains how to gain insight into the management of infectious diseases through statistical modeling. With end-of-chapter exercises and glossaries of infectious disease terminology and notation, the text is suitable for a graduate-level public health course. Supplementary technical material is provided at the end of each chapter for readers with a stronger background in mathematics and an interest in the art of modeling. In addition, bibliographic notes point readers to literature in which extensions and more general results can be found.


"Infectious disease control is certainly a relevant and timely topic worthy of comprehensive treatment in a dedicated text. …. Practical questions, such as what defines a successful vaccination campaign, are answered throughout. A very interesting point is taken up in Chapter 10, which is how to use infectious disease data to inform model choice, that is, within statistical models. As one typically tries to keep models as simple as possible, it is important to deal with this problem. … Individual chapter contents are thoroughly prepared. Starting with a short motivation, the models and analyses are displayed in single steps, avoiding the use of humbling phrases such as "as easily checked by the reader." … Many real-life examples in the main text and exercises are included, including larger data sets, such as the Hagelloch measles epidemic. By doing so, the book helps to understand how to apply the introduced methods not only to "nice academic examples," but to real-life problems, and to learn about the special difficulties there. … [T]he presented book provides useful and graspable material for interested readers to enter a relevant and important scientific area, whether they be undergraduate statistics students or advanced researchers in interdisciplinary fields."

—Christina Kuttler, Technical University Munich, in Biometrics, March 2018

"This book provides an accessible introduction to the use of mathematical models to inform infectious disease management. The core material is designed to be read by someone with a ‘modest knowledge of mathematics’, possessing the ability to ‘interpret an algebraic formula and [understand] what it means to solve an equation’; some additional knowledge of basic statistics is stated as being useful. … The core material is complemented by more technical supplementary material at the end of each chapter, for readers with greater knowledge of mathematics. Exercises are included in each chapter which support the material and would be suitable for use as part of an introductory course…The language in the book is direct and clear, and the material is well motivated. … Overall, this book is a valuable resource to those new to infectious disease (stochastic) modelling. It is rather unique in the level of assumed knowledge, the probabilistic foundation (including handling of branching process and stochastic household model results), the provision of tangible and realistic insight into how these models inform public health management, and the integration of data. To achieve this all within just over 200 pages is a great feat."

—Joshua V. Ross School of Mathematical Sciences, The University of Adelaide, in Australian & New Zealand Journal of Statistics, 2016

"This new book seeks to fill an important gap in the literature on infectious disease modeling, namely separating the now well-developed mathematical and statistical theory of infectious diseases from its public health application to infectious disease control. Professor Becker bridges the two worlds by presenting a logical succession of simple models that relate to some of the pressing questions arising in outbreak control. The approach is very effective and has resulted in an engaging volume that, in my estimation, will become a classic of the literature and thus a worthy successor to the author’s earlier landmark volume on the subject. It will be essential reading for a broad range of scientists working on infectious diseases, notably statisticians, modelers, and epidemiologists with an interest in quantitative methods."

Paddy Farrington, The Open University, UK

Table of Contents




Scope and layout of the book

Minor outbreaks when infectives are homogeneous

When are outbreaks certain to be minor?

Preventing epidemics by mass immunization

Reproduction number

What is a minor outbreak?

Probability of a minor outbreak

Importation of the infectious disease

Estimating R

Minor outbreaks in a community of households

Modified allocation of offspring

Household reproduction number

When are outbreaks certain to be minor?

Mass immunization

Are results affected by the way the infection is imported?

Estimating RH

Minor outbreaks when individuals differ

Type-specific offspring distributions

When are outbreaks certain to be minor?

Mass immunization

Types of individual in a community of households

Two reproduction numbers for a community of households

Transmission intensity function

Describing transmission intensity by a function

Estimating the transmission intensity function

Role of the transmission intensity function in modeling

Partially effective vaccines

Vaccine effect on transmission between individuals

Impact of mass immunization on the reproduction number

Estimating vaccine effects

Social distancing

What is social distancing?

Reduced mixing

Isolating symptomatic infectives

Targeting high transmission intensities

Reducing epidemic size

Simulated epidemics

The nature of our deterministic epidemic model

Epidemic size in a homogeneous community

Mass immunization

Herd immunity

Estimating the reproduction number

Types of individual

Dynamics of infection incidence

The epidemic curve

Estimating parameter values from daily incidence data

Endemic transmission

Using data to inform model choice

Model-free comparison of data on outbreak size

Transmission among homogeneous individuals

Allowing transmission rates to differ between individuals

Terminology and notation


Subject index

Discussion, Exercises, Supplementary material, and Bibliographic notes appear at the end of each chapter.

About the Author

Niels G. Becker is an emeritus professor of biostatistics at the Australian National University, where he was the director of the National Centre for Epidemiology and Population Health from 2007 until 2011. Dr. Becker has published more than 150 peer-reviewed articles. His research interests include the control of infectious diseases, triggers of adverse health events, and the analysis of foodborne disease data.

About the Series

Chapman & Hall/CRC Biostatistics Series

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
MEDICAL / Infectious Diseases
MEDICAL / Epidemiology