Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 904

Veröffentlichungsjahr: 2014

Beschreibung

Features modern research and methodology on the spread of infectious diseases and showcases a broad range of multi-disciplinary and state-of-the-art techniques on geo-simulation, geo-visualization, remote sensing, metapopulation modeling, cloud computing, and pattern analysis

Given the ongoing risk of infectious diseases worldwide, it is crucial to develop appropriate analysis methods, models, and tools to assess and predict the spread of disease and evaluate the risk. Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features mathematical and spatial modeling approaches that integrate applications from various fields such as geo-computation and simulation, spatial analytics, mathematics, statistics, epidemiology, and health policy. In addition, the book captures the latest advances in the use of geographic information system (GIS), global positioning system (GPS), and other location-based technologies in the spatial and temporal study of infectious diseases.

Highlighting the current practices and methodology via various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases features:

• Approaches to better use infectious disease data collected from various sources for analysis and modeling purposes
• Examples of disease spreading dynamics, including West Nile virus, bird flu, Lyme disease, pandemic influenza (H1N1), and schistosomiasis
• Modern techniques such as Smartphone use in spatio-temporal usage data, cloud computing-enabled cluster detection, and communicable disease geo-simulation based on human mobility
• An overview of different mathematical, statistical, spatial modeling, and geo-simulation techniques

Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases is an excellent resource for researchers and scientists who use, manage, or analyze infectious disease data, need to learn various traditional and advanced analytical methods and modeling techniques, and become aware of different issues and challenges related to infectious disease modeling and simulation. The book is also a useful textbook and/or supplement for upper-undergraduate and graduate-level courses in bioinformatics, biostatistics, public health and policy, and epidemiology.

Leseprobe

Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

Edited by

DONGMEI CHEN

Department of Geography Queen's University Kingston, Canada

BERNARD MOULIN

Department of Computer Science and Software Engineering Laval University Québec, Canada

JIANHONG WU

Department of Mathematics and Statistics York University Toronto, Canada

Copyright © 2015 by John Wiley & Sons, Inc. All rights reserved.

Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada.

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Library of Congress Cataloging-in-Publication Data:

Analyzing and modeling spatial and temporal dynamics of infectious diseases / [edited by] Dongmei Chen, Bernard Moulin, Jianhong Wu. p. ; cm. Includes bibliographical references and index. ISBN 978-1-118-62993-2 (cloth) I. Chen, Dongmei, 1969- editor. II. Moulin, Bernard, 1954- editor. III. Wu, Jianhong, 1964- editor. [DNLM: 1. Communicable Diseases–epidemiology. 2. Spatio-Temporal Analysis. 3. Computer Simulation. 4. Disease Transmission, Infectious–statistics & numerical data. 5. Models, Statistical. WA 950] RC111 616.9–dc23

2014011438

CONTENTS

Foreword: Interdisciplinary Collaborations for Informed Decisions

Acknowledgements

Editors

Contributors

Part I: Overview

Chapter 1: Introduction to Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

1.1 Background

1.2 Infectious Diseases, Their Transmission and Research Needs

1.3 Diseases Covered in This Book and Their Transmission Mechanism

1.4 The Organization And Outline Of This Book

1.5 Conclusion

References

Chapter 2: Modeling the Spread of Infectious Diseases: A Review

2.1 Introduction

2.2 Mathematical Modelling

2.3 Statistical Modeling

2.4 Gravity Models

2.5 Network-Based Models

2.6 Computational Simulation Approaches

2.7 Discussions And Conclusions

Acknowledgments

References

Part II: Mathematical Modeling of Infectious Diseases

Chapter 3: West Nile Virus: A Narrative from Bioinformatics and Mathematical Modeling Studies

3.1 Introduction

References

Chapter 4: West Nile Virus Risk Assessment and Forecasting Using Statistical and Dynamical Models

4.1 Introduction

4.2 Statistical Model for Mosquito Abundance of WNV

4.3 Risk Assessment of WNV Using the Dynamical Model

4.4 Forecasting WNV Risk in Peel Region, Ontario, Using Real Data

4.5 Conclusions

Acknowledgments

References

Note

Chapter 5: Using Mathematical Modeling to Integrate Disease Surveillance and Global Air Transportation Data

5.1 Introduction

5.2 The Network

5.3 Airport Catchment Areas

5.4 Modeling

5.5 Numerical Simulations

5.6 Conclusions

References

Chapter 6: Malaria Models with Spatial Effects

6.1 Introduction

6.2 Malaria Models With Constant Infective Immigrants

6.3 Malaria Models With Discrete Diffusion

6.4 Malaria Models With Continuous Diffusion

6.5 Discussion

Acknowledgments

References

Chapter 7: Avian Influenza Spread and Transmission Dynamics

7.1 Introduction

7.2 Avian Influenza: Issues for Modelling

7.3 HPAI Outbreak Mitigated by Seasonal LPAI

7.4 Local Dynamics and Mitigation Potential

7.5 Conclusion

References

Note

Part III: Spatial Analysis and Statistical Modeling of Infectious Diseases

Chapter 8: Analyzing the Potential Impact of Bird Migration on the Global Spread of H5N1 Avian Influenza (2007–2011) Using Spatiotemporal Mapping Methods

8.1 Introduction

8.2 Methodology

8.3 Results and Discussion

8.4 Conclusion

Acknowledgments

References

Chapter 9: Cloud Computing–Enabled Cluster Detection Using a Flexibly Shaped Scan Statistic for Real-Time Syndromic Surveillance

9.1 Introduction

9.2 Spatial Scan Statistics

9.3 Study Region and Data

9.4 Computational Challenge

9.5 Discussion

Acknowledgments

References

Notes

Chapter 10: Mapping the Distribution of Malaria: Current Approaches and Future Directions

10.1 Introduction

10.2 Mapping and Spatial Models

10.3 Modern Mapping Approaches and Methods

10.4 Future Directions and Conclusions

References

Chapter 11: Statistical Modeling of Spatiotemporal Infectious Disease Transmission

11.1 Introduction

11.2 Infectious Disease Transmission Model

11.3 Statistical and Computational Framework

11.4 Discussion

Acknowledgments

References

Chapter 12: Spatiotemporal Dynamics of Schistosomiasis in China: Bayesian-Based Geostatistical Analysis

12.1 Introduction

12.2 Materials and Methods

12.3 Results

12.4 Discussion

Acknowledgments

References

Chapter 13: Spatial Analysis and Statistical Modeling of 2009 H1N1 Pandemic in the Greater Toronto Area

13.1 Introduction

13.2 Study Area And Data

13.3 Analysis Methods

13.4 The Implementation Of The Glmm And Icar

13.5 Results

13.6 Discussions And Conclusion

References

Chapter 14: West Nile Virus Mosquito Abundance Modeling Using Nonstationary Spatiotemporal Geostatistics

14.1 Introduction

14.2 Methods

14.3 Data Analysis and Results

14.4 Summary and Conclusions

References

Chapter 15: Spatial Pattern Analysis of Multivariate Disease Data

15.1 Introduction

15.2 The CBR Data

15.3 Models and Methods

15.4 Analysis of The CBR Data

15.5 Discussion

Acknowledgments

References

Part IV: Geosimulation and Tools for Analyzing and Simulating Spreads of Infectious Diseases

Chapter 16: The ZoonosisMAGS Project (Part 1): Population-Based Geosimulation of Zoonoses in an Informed Virtual Geographic Environment

16.1 Introduction

16.2 Spatially Explicit Models for Epidemiology

16.3 Simulation Approaches of Disease Propagation

16.4 The Zoonosismags Population-Based Geosimulation Approach

16.5 The Informed Virtual Geographic Environment

16.6 Spatialized Population-Based Approach

16.7 Modeling and Simulating Mobility

16.8 Simulation of The Establishment of Tick Populations

16.9 Conclusion

Acknowledgments

References

Notes

Chapter 17: ZoonosisMAGS Project (Part 2): Complementarity of a Rapid-Prototyping Tool and of a Full-Scale Geosimulator for Population-Based Geosimulation of Zoonoses

17.1 Introduction

17.2 The Zoonosismags Project and Our Double Software Development Strategy

17.3 The MATLAB Simulation Prototyping Tool

17.4 Experiments Carried out with Our MATLAB Simulator

17.5 The C++ Full-Scale Geosimulator

17.6 Current Status Of The Implementation and Future Work

17.7 Conclusion

Acknowledgments

References

Chapter 18: Web Mapping and Behavior Pattern Extraction Tools to Assess Lyme Disease Risk for Humans in Peri-urban Forests

18.1 Assessment Of Human Risk Exposure To Lyme Disease

18.2 The Sénart-Mags Project

18.3 Visitors' Data Collection

18.4 Activity Patterns In The Forét De Sénart: The Conceptual Model

18.5 Activity Patterns Extraction

18.6 Current Results

18.7 Conclusion

Acknowledgments

References

Notes

Chapter 19: An Integrated Approach for Communicable Disease Geosimulation Based on Epidemiological, Human Mobility and Public Intervention Models

19.1 Fundamentals Of Communicable Diseases Spread And Control

19.2 An Overview Of Existing Spatial Infectious Disease Models

19.3 Our Approach

19.4 The P2pcodigeosim Software

19.5 Discussion

19.6 Conclusion

Acknowledgments

References

Notes

Chapter 20: Smartphone Trajectories as Data Sources for Agent-based Infection-spread Modeling

20.1 Introduction

20.2 Cell Phone Data

20.3 Agent-Based Modeling

20.4 Three Abm Simulations

20.5 Extensions

20.6 Conclusions

Acknowledgments

References

Notes

Index

End User License Agreement

List of Tables

Chapter 3

Table 3.1

Chapter 4

Table 4.1

Chapter 6

Table 6.1

Chapter 7

Table 7.1

Table 7.2

Chapter 8

Table 8.1

Table 8.2

Chapter 9

Table 9.1

Chapter 10

Table 10.1

Chapter 11

Table 11.1

Chapter 12

Table 12.1

Table 12.2

Table 12.3

Table 12.4

Chapter 13

Table 13.1

Chapter 14

Table 14.1

Table 14.2

Table 14.3

Table 14.4

Chapter 15

Table 15.1

Chapter 16

Table 16.1

Chapter 17

Table 17.1

Table 17.2

Table 17.3

Table 17.4

Chapter 18

Table 18.1

Chapter 19

Table 19.1

Table 19.2

Table 19.3

Chapter 20

Table 20.1

Table 20.2

Table 20.3

Table 20.4

Guide

Cover

Table of Contents

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Foreword: Interdisciplinary Collaborations for Informed Decisions

When the unexpected occurs, decision makers scramble to understand the immediate threat and to respond as best they can. The many disciplines, subgroups, and communities of the science world may feel that their contribution is not fully appreciated or valued. There is often much lip service to the value of interdisciplinary collaboration, but actual practice lags.

This book is strong evidence for making investments before the crisis, for favoring interdisciplinary collaborations, and for building long-term partnerships across sectors. In January 2008, a group of nine researchers from a diverse range of disciplines pulled together a proposal to build a network of collaboration on the theme of infectious disease spread. This group included specialists in human and animal health, medical geography, and various modeling disciplines (mathematics, statistics, computer science, geomatics). Like many experienced research groups, they sought support from various sources, and were successful with two Networks of Centres of Excellence: MITACS and GEOIDE. As Scientific Director of GEOIDE at that time, I took this proposal alongside the 19 others submitted (pruned down in a preliminary round from 44 expressions of interest).

Decisions are always easy in retrospect, when the results are known. It is hard to know if a collection of disparate researchers can pull together to collaborate on a full-scale project. At that point, 9 years of experience at the GEOIDE Network had given us a sense of how collaborations actually operate. This proposal was selected, through a pilot phase to become one of eight principal projects in Phase IV, the final funding period, of the GEOIDE Network. The GEOIDE Board of Directors had adopted a higher risk strategy of providing larger grants to fewer teams. Consequently, a pilot phase was put in place to provide a bit of assurance that the risk was worthwhile. This book provides the proof that the funding decision was prudent. Canada and the World have benefitted from the research efforts of the original team of nine, augmented over the years through other funding sources.

Their proposal talked about a prudent scientific strategy starting with vector disease spread for West Nile virus, Lyme disease, and avian influenza, leading up to pandemic influenza. In 2008, this last item was a potential threat with an unknown time horizon. The others had tangible outbreaks, of varying size and mechanisms. They were therefore the first targets. As I flew around the world in 2009, public health authorities were nervously meeting airplanes with thermal cameras to attempt to react to the rapid spread of H1N1. Canada ramped up massive vaccinations projects in some provinces, and authorities around the world focused on the emerging threat. The project team showed great flexibility in responding, joining up with other teams around the world to understand the process and to provide guidance for decisions. Already the value of interdisciplinary collaboration was evident, and Canada played a key role in responding to the international developments. Some of these chapters show how the team responded to the changing circumstances for each of their respective disease contexts.

Interdisciplinary work is hard, since the rules of academic research vary across the disciplines. But the work of understanding disease spread is not the sole proprietary of any one group. Innovative approaches require fresh ways of looking as well as time to understand the contribution of others. This book brings together a variety of techniques, each developed from many years' effort in one of the contributing disciplines. These approaches were put to a realistic test, through connection to partners in public health agencies and front-line hospital and clinic settings. The result will enrich each participant, and provide a basis for informed decisions. That was the mission of GEOIDE, and this book provides additional proof that our investments are yielding benefits beyond the lifetime of the Network.

NICHOLAS CHRISMAN

RMIT University, Melbourne, Australia