Disease Modelling and Public Health, Part B: Volume 37

Informationen zum Autor 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. PhD, Professor, Indian Institute of Public Health, Hyderabad, India C. R. Rao is a world famous statistician who earned a place in the history of statistics as one of those who developed statistics from its adhoc origins into a firmly grounded mathematical science.? He was employed at the Indian Statistical Institute (ISI) in 1943 as a research scholar after obtaining an MA degree in mathematics with a first class and first rank from Andhra University in1941 and MA degree in statistics from Calcutta University in 1943 with a first class, first rank, gold medal and record marks which remain unbroken during the last 73 years. At the age of 28 he was made a full professor at ISI in recognition of his creativity.? While at ISI, Rao went to Cambridge University (CU) in 1946 on an invitation to work on an anthropometric project using the methodology developed at ISI. Rao worked in the museum of archeology and anthropology in Duckworth laboratory of CU during 1946-1948 as a paid visiting scholar. The results were reported in the book Ancient Inhabitants of Jebel Moya? published by the Cambridge Press under the joint authorship of Rao and two anthropologists. On the basis of work done at CU during the two year period, 1946-1948, Rao earned a Ph.D. degree and a few years later Sc.D. degree of CU and the rare honor of life fellowship of Kings College, Cambridge. He retired from ISI in 1980 at the mandatory age of 60 after working for 40 years during which period he developed ISI as an international center for statistical education and research. He also took an active part in establishing state statistical bureaus to collect local statistics and transmitting them to Central Statistical Organization in New Delhi. Rao played a pivitol role in launching undergraduate and postgraduate courses at ISI. He is the author of 475 research publications and several breakthrough papers contributing to statistical theory and methodology for applications to problems in all areas of human endeavor. There are a number of classical statistical terms named after him, the most popular of which are Cramer-Rao inequality, Rao-Blackwellization, Rao's Orthogonal arrays used in quality control, Rao's score test, Rao's Quadratic Entropy used in ecological work, Rao's metric and distance which are incorporated in most statistical books. He is the author of 10 books, of which two important books are, Linear Statistical Inference ...

Klappentext

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.

Inhalt

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