000 03810nam a22004815i 4500
001 978-1-4614-9224-5
003 DE-He213
005 20140220082832.0
007 cr nn 008mamaa
008 131130s2013 xxu| s |||| 0|eng d
020 _a9781461492245
_9978-1-4614-9224-5
024 7 _a10.1007/978-1-4614-9224-5
_2doi
050 4 _aQH301-705
072 7 _aPSA
_2bicssc
072 7 _aSCI086000
_2bisacsh
072 7 _aSCI064000
_2bisacsh
082 0 4 _a570
_223
100 1 _aSree Hari Rao, V.
_eeditor.
245 1 0 _aDynamic Models of Infectious Diseases
_h[electronic resource] :
_bVolume 2: Non Vector-Borne Diseases /
_cedited by V. Sree Hari Rao, Ravi Durvasula.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXII, 259 p. 69 illus., 42 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aControl of Infectious Diseases: Dynamics and Informatics -- Evaluating the evolutionary dynamics of viral populations -- Percolation Methods for Seir Epidemics on Graphs -- Dynamics of tuberculosis in a developing country: Nigeria as a case study -- Component Signaling Systems of M. tuberculosis: Regulators of Pathogenicity and More -- Mycobacterium tuberculosis evolution, host-pathogen interactions and implications for tuberculosis control -- Trends in HIV transmission according to differences in numbers of sexual partnerships among men who have sex with men in China -- The Impact of Cryptococcus gattii with a Focus on the Outbreak in North America -- Modeling the Spread and Outbreak Dynamics of Avian Influenza (H5N1) Virus and its Possible Control -- Index.
520 _aThough 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.
650 0 _aLife sciences.
650 0 _aEmerging infectious diseases.
650 0 _aBioinformatics.
650 0 _aBiological models.
650 1 4 _aLife Sciences.
650 2 4 _aSystems Biology.
650 2 4 _aInfectious Diseases.
650 2 4 _aBioinformatics.
700 1 _aDurvasula, Ravi.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461492238
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-9224-5
912 _aZDB-2-SBL
999 _c96110
_d96110