Handbook of Infectious Disease Data Analysis (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)

Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material Contents Editors Contributors I Introduction 1 Introduction • Leonhard Held, Niel Hens, Philip D. O’Neill, and Jacco Wallinga II Basic Concepts 2 Population Dynamics of Pathogens • Ottar N. Bjørnstad 3 Infectious Disease Data from Surveillance, Outbreak Investigation, and Epidemiological Studies • Susan Hahné and Richard Pebody 4 Key Concepts in Infectious Disease Epidemiology • Nicholas P. Jewell 5 Key Parameters in Infectious Disease Epidemiology • Laura F. White 6 Contact Patterns for Contagious Diseases • Jacco Wallinga, Jan van de Kassteele, and Niel Hens 7 Basic Stochastic Transmission Models and Their Inference • Tom Britton 8 Analysis of Vaccine Studies and Causal Inference • M. Elizabeth Halloran III Analysis of Outbreak Data 9 Markov Chain Monte Carlo Methods for Outbreak Data • Philip D. O’Neill and Theodore Kypraios 10 Approximate Bayesian Computation Methods for Epidemic Models • Peter J. Neal 11 Iterated Filtering Methods for Markov Process Epidemic Models • Theresa Stocks 12 Pairwise Survival Analysis of Infectious Disease Transmission Data • Eben Kenah 13 Methods for Outbreaks Using Genomic Data • Don Klinkenberg, Caroline Colijn, and Xavier Didelot IV Analysis of Seroprevalence Data 14 Persistence of Passive Immunity, Natural Immunity (and Vaccination) • Amy K. Winter and C. Jessica E. Metcalf 15 Inferring the Time of Infection from Serological Data • Maciej F. Boni, Kåre Mølbak, and Karen A. Krogfelt 16 The Use of Seroprevalence Data to Estimate Cumulative Incidence of Infection • Benjamin J. Cowling and Jessica Y. Wong 17 The Analysis of Serological Data with Transmission Models • Marc Baguelin 18 The Analysis of Multivariate Serological Data • Steven Abrams 19 Mixture Modeling • Emanuele Del Fava and Ziv Shkedy V Analysis of Surveillance Data 20 Modeling Infectious Disease Distributions: Applications of Point Process Methods • Peter J. Diggle 21 Prospective Detection of Outbreaks • Benjamin Allévius and Michael Höhle 22 Underreporting and Reporting Delays • Angela Noufaily 23 Spatio-Temporal Analysis of Surveillance Data • Jon Wakefield, Tracy Qi Dong, and Vladimir N. Minin 24 Analysing Multiple Epidemic Data Sources • Daniela De Angelis and Anne M. Presanis 25 Forecasting Based on Surveillance Data • Leonhard Held and Sebastian Meyer 26 Spatial Mapping of Infectious Disease Risk • Ewan Cameron Index Recent Years Have Seen An Explosion In New Kinds Of Data On Infectious Diseases, Including Data On Social Contacts, Whole Genome Sequences Of Pathogens, Biomarkers For Susceptibility To Infection, Serological Panel Data, And Surveillance Data. The Handbook Of Infectious Disease Data Analysisprovides An Overview Of Many Key Statistical Methods That Have Been Developed In Response To Such New Data Streams And The Associated Ability To Address Key Scientific And Epidemiological Questions. A Unique Feature Of The Handbook Is The Wide Range Of Topics Covered. Key Features Contributors Include Many Leading Researchers In The Field Divided Into Four Main Sections: Basic Concepts, Analysis Of Outbreak Data, Analysis Of Seroprevalence Data, Analysis Of Surveillance Data Numerous Case Studies And Examples Throughout Provides Both Introductory Material And Key Reference Material Leonhard Heldis Professor Of Biostatistics At The University Of Zurich. Niel Hensis Professor Of Biostatistics At Hasselt University And The University Of Antwerp. Philip O'neillis Professor Of Applied Probability At The University Of Nottingham. Jacco Wallingais Professor Of Mathematical Modelling Of Infectious Diseases At The Leiden University Medical Center. Numerous Case Studies And Examples Throughout Provides Both Introductory Material And Key Reference Material Leonhard Heldis Professor Of Biostatistics At The University Of Zurich. Niel Hensis Professor Of Biostatistics At Hasselt University And The University Of Antwerp. Philip O'neillis Professor Of Applied Probability At The University Of Nottingham. Jacco Wallingais Professor Of Mathematical Modelling Of Infectious Diseases At The Leiden University Medical Center. ;lt;/b> There are many books on infectious disease epidemiology with an emphasis on mathematical modelling, but less so on dataanalytic aspects. This provides a unique and comprehensive account of state-of-the-art methodology for analysis of infectious disease data.