Disease Modelling and Public Health, Part B (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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

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Produktdetails

• Verlag: Elsevier Science & Techn.
• Seitenzahl: 390
• Erscheinungstermin: 31. Oktober 2017
• Englisch
• ISBN-13: 9780444639769
• Artikelnr.: 50143229

Autorenporträt

Arni S.R. Srinivasa Rao works in pure mathematics, applied mathematics, probability, and artificial intelligence and applications in medicine. He is a Professor at the Medical College of Georgia, Augusta University, U.S.A, and the Director of the Laboratory for Theory and Mathematical Modeling housed within the Division of Infectious Diseases, Medical College of Georgia, Augusta, U.S.A. Previously, Dr. Rao conducted research and/or taught at Mathematical Institute, University of Oxford (2003, 2005-07), Indian Statistical Institute (1998-2002, 2006-2012), Indian Institute of Science (2002-04), University of Guelph (2004-06). Until 2012, Dr. Rao held a permanent faculty position at the Indian Statistical Institute. He has won the Heiwa-Nakajima Award (Japan) and Fast Track Young Scientists Fellowship in Mathematical Sciences (DST, New Delhi). Dr. Rao also proved a major theorem in stationary population models, such as, Rao's Partition Theorem in Populations, Rao-Carey Theorem in stationary populations, and developed mathematical modeling-based policies for the spread of diseases like HIV, H5N1, COVID-19, etc. He developed a new set of network models for understanding avian pathogen biology on grid graphs (these were called chicken walk models), AI Models for COVID-19 and received wide coverage in the science media. Recently, he developed concepts such as "Exact Deep Learning Machines?, and "Multilevel Contours? within a bundle of Complex Number Planes.

Inhaltsangabe

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