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001			76084
003			ES-MaUEC
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007			cr nn 008mamaa
008			131130s2013 xxu| s |||| 0|eng d
020			_a9781461492245
024	7		_a10.1007/978-1-4614-9224-5 _2doi
040			_aES-MaUEC
050		4	_aRA643 _b.D96 2013 EB
082	0	4	_a570
700	1		_aSree Hari Rao, V. _eeditor literario. _984948 _0Local _1http://viaf.org/viaf/315256387
245	0	0	_aDynamic Models of Infectious Diseases _nVolume 2, _pNon Vector-Borne Diseases _cedited by V. Sree Hari Rao, Ravi Durvasula.
264		1	_aNew York _bSpringer International Publishing _c2013
300			_a1 recurso en línea (XII, 259 páginas) _b69 ilustraciones, 42 ilustraciones en color
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
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		7	_aBioinformática _2embne _9160489
700	1		_aDurvasula, Ravi _eeditor literario _984520 _0Local _0http://id.loc.gov/authorities/names/n2013182066 _1http://viaf.org/viaf/297852655
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-1-4614-9224-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
907			_a.b12817028 _b10-10-17 _c01-10-14
942			_2lcc _cLE
945			_aQH301-705 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11546244 _z06-04-17
988	0	0	_aEBOOK, EBSPRINGER, GOBI_sep2018
988			_aEbook_one2one
998			_aSI _a_alco _a_vill _b10/2018 _cm _dz _ef _feng _gxxu _h0
999			_c76084 _d76084 _x1