Handbook of Statistics: Disease Modelling and Public Health, Part B, Volume 37 addresses new challenges in existing and emerging diseases. As a two part volume, this title covers an extensive range of techniques in the field, with this book including chapters on Reaction diffusion equations and their application on bacterial communication, Spike and slab methods in disease modeling, Mathematical modeling of mass screening and parameter estimation, Individual-based and agent-based models for infectious disease transmission and evolution: an overview, and a section on Visual Clustering of Static and Dynamic High Dimensional Data.
This volume covers the lack of availability of complete data relating to disease symptoms and disease epidemiology, one of the biggest challenges facing vaccine developers, public health planners, epidemiologists and health sector researchers.
- Presents a comprehensive, two-part volume written by leading subject experts
- Provides a unique breadth and depth of content coverage
- Addresses the most cutting-edge developments in the field
Section VI : Statistical Methodologies 1. Imputation of Area-Level Covariates by Registry Linking J.S. Rao and Jie Fan 2. Asymptotic Approaches to Discovering Cancer Genomic Signatures Maciej Pietrzak and Grzegorz A. Rempala 3. Emerging Statistical Methodologies in the Field of Microbiome Studies Siddhartha Mandal
Section VII : Advanced Mathematical Methods 4. Reaction-Diffusion Equations and Their Application on Bacterial Communication Christina Kuttler 5. Hepatitis C Virus (HCV) Treatment as Prevention: Epidemic and Cost-Effectiveness Modeling Natasha K. Martin and Lara K. Marquez 6. Mathematical Modeling of Mass Screening and Parameter Estimation Masayuki Kakehashi and Miwako Tsunematsu 7. Inferring Patterns, Dynamics, and Model-Based Metrics of Epidemiological Risks of Neglected Tropical Diseases Anuj Mubayi 8. Theory and Modeling for Time Required to Vaccinate a Population in an Epidemic Taejin Lee, Kurien Thomas and Arni S.R. Srinivasa Rao
Section VIII : Public Health and Epidemic Data Modeling 9. Frailty Models in Public Health David D. Hanagal 10. Structural Nested Mean Models and History-Adjusted Marginal Structural Models for Time-Varying Effect Modification: An Application to Dental Data Murthy N. Mittinty 11. Conditional Growth Models: An Exposition and Some Extensions Clive Osmond and Caroline H.D. Fall 12. Parametric Model to Predict H1N1 Influenza in Vellore District, Tamil Nadu, India Daphne Lopez and Gunasekaran Manogaran 13. Public Health Eye Care: Modeling Techniques to Translate Evidence Into Effective Action Gudlavalleti V.S. Murthy and Neena S. John 14. Individual-Based Models for Public Health Benjamin Roche and Raphaël Duboz