Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases

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 disease spread 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 illustrated through various infectious disease studies, Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases also 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.

Preface Acknowledgements Editors Contributors Part I Overview Chapter 1 Introduction to Analyzing and Modeling Spatial and Temporal Dynamics of Infectious Diseases Dongmei Chen, Bernard Moulin and Jianhong Wu Chapter 2 Modeling the Spread of Infectious Diseases: A Review Dongmei Chen P art II Mathematical Modeling of Infectious Diseases Chapter 3 West Nile Virus: A Narrative from Bioinformatics and Mathematical Modeling Studies U S N Murty, Amit Kumar Banerjee and Jianhong Wu Chapter 4 West Nile Virus Risk Assessment and Forecasting Using Statistical and Dynamical Models Ahmed Abdelrazec, Yurong Cao, Xin Gao, Paul Proctor, Hui Zheng and Huaiping Zhu Chapter 5 Using Mathematical Modeling to Integrate Disease Surveillance and Global Air Transportation Data Julien Arino and Kamran Khan Chapter 6  Malaria Models with Spatial Effects Daozhou Gao and Shigui Ruan Chapter 7 Avian Influenza Spread and Transmission Dynamics Lydia Bourouiba, Stephen Gourley, Rongsong Liu, John Takekawa and Jianhong Wu 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 Spatio–temporal Mapping Methods Heather Richardson and Dongmei Chen Chapter 9 Cloud computing–enabled cluster detection using a flexibly –shaped scan statistic for real–time syndromic surveillance P. Belanger and K. Moore Chapter 10 Mapping the distribution of Malaria: Current Approaches and Future Directions L.R. Johnson, K.D. Lafferty, A. McNally, E. Mordecai, K. Paaijmans, S. Pawar and S.J. Ryan Chapter 11 Statistical Modeling of Spatio–Temporal Infectious Disease Transmission Rob Deardon, Xuan Fang and Grace Pui Sze Kwong Chapter 12 Spatio–temporal dynamics of schistosomiasis in China: Bayesian–based geostatistical analysis Zhi–Jie Zhang Chapter 13 Spatial analysis and statistical modeling of 2009 H1N1 pandemic in the Greater Toronto Area Frank Wen, Dongmei Chen and Anna Majury Chapter 14 West Nile virus mosquito abundance modeling using a non–stationary spatio–temporal Geostatistics Eun–Hye Yoo, Dongmei Chen and Curtis Russel Chapter 15 Spatial Pattern Analysis of Multivariate Disease Data Cindy X. Feng and Charmaine Dean Part IV Geosimulation Tools to 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 Bernard Moulin, Mondher Bouden and Daniel Navarro Chapter 17 ZoonosisMAGS Project (Part 2): Complementarity of a Rapid–Propotyping Tool and of a Full–Scale Geosimulator for Population–Based Geosimulation of Zoonoses Bernard Moulin, Daniel Navarro, Dominic Marcotte and Said Sedrati Chapter 18  Web–Mapping and Behaviour Pattern Extraction Tools to Assess Lyme Disease Risk for Humans in Peri–Urban Forests Hedi Haddad, Bernard Moulin, Franck Manirakiza Christelle Méha, Vincent Godard and Samuel Mermet Chapter 19  An Integrated Approach for Communicable Disease Geosimulation based on Epidemiological, Human Mobility and Public Intervention Models Hedi Haddad, Bernard Moulin and Marius Thériault Chapter 20 Smartphone Trajectories as Data Sources for Agent–based Infection Spread Modeling M.R. Friesen and R.D. McLeod

Dongmei Chen, PhD, is Associate Professor in the Department of Geography and Director of the Laboratory for Geographic Information and Spatial Analysis at Queen′s University, Canada. Bernard Moulin, PhD, is Professor in the Department of Computer Science and Software Engineering at Laval University, Canada.  Jianhong Wu, PhD, is Canada Research Chair and University Distinguished Research Professor in the Department of Mathematics and Statistics and Director of the Center for Disease Modeling at York University, Canada.