Dynamic models of infectious diseases. Volume 2, Non vector-borne diseases /

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Bibliographic Details
Imprint:New York, NY : Springer, c2013.
Description:1 online resource (xii, 259 pages)
Subject:Communicable diseases -- Epidemiology -- Mathematical models.
HEALTH & FITNESS / Diseases / Contagious
MEDICAL / Infectious Diseases
HEALTH & FITNESS / Diseases / General
MEDICAL / Clinical Medicine
MEDICAL / Diseases
MEDICAL / Evidence-Based Medicine
MEDICAL / Internal Medicine
Communicable diseases -- Epidemiology -- Mathematical models.
Communicable Diseases -- transmission.
Communicable Diseases -- epidemiology.
Models, Theoretical.
Computer Simulation.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/9900332
Hidden Bibliographic Details
Varying Form of Title:Non vector-borne diseases
Other authors / contributors:Sree Hari Rao, Vadrevu, editor of compilation.
Durvasula, Ravi, editor of compilation.
ISBN:9781461492245 (electronic bk.)
1461492246 (electronic bk.)
Notes:Includes index.
Summary:Though great advances in public health are witnessed world over in recent years, infectious diseases, besides insect vector-borne infectious diseases remain a leading cause of morbidity and mortality. Control of the epidemics caused by the non-vector borne diseases such as tuberculosis, avian influenza (H5N1), and cryptococcus gattii, have left a very little hope in the past. The advancement of research in science and technology has paved way for the development of new tools and methodologies to fight against these diseases. In particular, intelligent technology and machine-learning based methodologies have rendered useful in developing more accurate predictive tools for the early diagnosis of these diseases. In all these endeavors the main focus is the understanding that the process of transmission of an infectious disease is nonlinear (not necessarily linear) and dynamical in character. This concept compels the appropriate quantification of the vital parameters that govern these dynamics. This book is ideal for a general science and engineering audience requiring an in-depth exposure to current issues, ideas, methods, and models. The topics discussed serve as a useful reference to clinical experts, health scientists, public health administrators, medical practioners, and senior undergraduate and graduate students in applied mathematics, biology, bioinformatics, and epidemiology, medicine and health sciences.