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HIV Transmission = Statistical Modelling /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	HIV Transmission/ by D. M. Basavarajaiah, Bhamidipati Narasimha Murthy.
Reminder of title:	Statistical Modelling /
Author:	Basavarajaiah, D. M.
other author:	Narasimha Murthy, Bhamidipati.
Description:	XXXV, 318 p. 84 illus., 46 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Health promotion. -
Online resource:	https://doi.org/10.1007/978-981-15-0151-7
ISBN:	9789811501517

HIV Transmission = Statistical Modelling /
Basavarajaiah, D. M.

HIV TransmissionStatistical Modelling /[electronic resource] :by D. M. Basavarajaiah, Bhamidipati Narasimha Murthy. - 1st ed. 2020. - XXXV, 318 p. 84 illus., 46 illus. in color.online resource.

Chapter 1. Introduction -- Chapter 2. Statistical Modeling of HIV Transmission -- Chapter 3. HIV Vertical Transmission DTSM Simulation Models - Global and National Prospective -- Chapter 4. Large Data matrices random walk Model and application of entropy in HIV Mother to Child transmission (MTCT) -- Chapter 5. Statistical Models of Postnatal Transmission of HIV type- I infection from Mother to Child on Global Perspectives -- Chapter 6. Survivability and Growth Models approach to CD4 Counts of PLHIVs -- Chapter 7. Predictive Model approach to HIV TB co-infection in Vertical transmission -- Chapter 8. Bayesian Artificial Neural network (ANN) Model approach to AIDS associated illness -- Chapter 9. HIV -Projection Models -- Chapter 10. Stochastic Simulation modeling techniques of HIV/AIDS -- Chapter 11. Meta analysis of Genetic variants of HIV Mother to Child Transmission -- Chapter 12. Statistical Perspective approach to Selection of Sample -- Chapter 13. Summary and implications for future research work. .

This book presents models describing HIV transmission rates at population level, discussing the main statistical methods and analytical interventions. It also assesses the practical applicability of the various modelling techniques, offering readers insights into what methods are available and, more importantly, when they should be used to address HIV transmission at global level. The book includes realistic simulation models fitted to clarify the rate of HIV mother-to-child transmission (HIV MTCT), and substantiates the conclusions that can be drawn as well as the appropriate time for making global-level clinical decisions concerning people living with HIV/AIDS (PLHIVs). Intended for students, academics and researchers, the book offers more than just an introduction to the topic – it also features in-depth, yet easy-to-understand, descriptions of a new mathematical/statistical HIV mother-to-child transmission model, making it a useful resource for clinicians, public health workers and policymakers involved in implementing HIV-prevention programmes at national /global level. .

ISBN: 9789811501517

Standard No.: 10.1007/978-981-15-0151-7doiSubjects--Topical Terms:

565089
Health promotion.

LC Class. No.: RA427.8

Dewey Class. No.: 613

HIV Transmission = Statistical Modelling /
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505 0 $a Chapter 1. Introduction -- Chapter 2. Statistical Modeling of HIV Transmission -- Chapter 3. HIV Vertical Transmission DTSM Simulation Models - Global and National Prospective -- Chapter 4. Large Data matrices random walk Model and application of entropy in HIV Mother to Child transmission (MTCT) -- Chapter 5. Statistical Models of Postnatal Transmission of HIV type- I infection from Mother to Child on Global Perspectives -- Chapter 6. Survivability and Growth Models approach to CD4 Counts of PLHIVs -- Chapter 7. Predictive Model approach to HIV TB co-infection in Vertical transmission -- Chapter 8. Bayesian Artificial Neural network (ANN) Model approach to AIDS associated illness -- Chapter 9. HIV -Projection Models -- Chapter 10. Stochastic Simulation modeling techniques of HIV/AIDS -- Chapter 11. Meta analysis of Genetic variants of HIV Mother to Child Transmission -- Chapter 12. Statistical Perspective approach to Selection of Sample -- Chapter 13. Summary and implications for future research work. .
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