Stochastic Modeling of AIDS Epidemiology and HIV Pathogenesis

Stochastic Modeling of AIDS Epidemiology and HIV Pathogenesis PDF

Author: W. Y. Tan

Publisher: World Scientific

Published: 2000

Total Pages: 458

ISBN-13: 9789810241223

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This book discusses systematically treatment on the development of stochastic, statistical and state space models of the HIV epidemic and of HIV pathogenesis in HIV-infected individuals, and presents the applications of these models. The book is unique in several ways: (1) it uses stochastic difference and differential equations to present the stochastic models of the HIV epidemic and HIV pathogenesis; in this sense, the deterministic models are considered as special cases when the numbers of different type of people or cells are very large (2) it provides, a critical analysis of deterministic and statistical models in the literature; (3) it develops state space models by combining stochastic models and statistical models; and (4) it provides a detailed discussion on the pros and cons of the different modeling approaches. This book is the first to introduce state space models for the HIV epidemic. It is also the first to develop stochastic models and state space models for the HIV pathogenesis in HIV-infected individuals.

Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention

Deterministic and Stochastic Models of AIDS Epidemics and HIV Infections with Intervention PDF

Author: W. Y. Tan

Publisher: World Scientific

Published: 2005

Total Pages: 610

ISBN-13: 9812561390

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- Only book on extensive, deterministic models, statistic models, stochastic models and state space models and statistical methods for HIV epidemic involving IV drug usage and HIV epidemic in homosexual populations. - Provides most recent biological insights into HIV pathogenesis and HIV kinetics at the cellular level, and illustrates how to build up mathematical models based on these biological insights. - Only publication that provides in-depth analysis of HAART treatment protocols and discusses possible improvements to the HAART protocol. The book also provides connection between pharmacokinetics with treatment in HIV-infected individuals.

Stochastic Processes In Epidemiology: Hiv/aids, Other Infectious Diseases And Computers

Stochastic Processes In Epidemiology: Hiv/aids, Other Infectious Diseases And Computers PDF

Author: Charles J Mode

Publisher: World Scientific

Published: 2000-06-09

Total Pages: 765

ISBN-13: 9814494186

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AIDS (autoimmune deficiency syndrome) is a devastating human disease caused by HIV, a human immunodeficiency virus, which may be transmitted by either sexual or other contacts in which body fluids are exchanged. Cases of AIDS have been reported in a majority of countries throughout the world, indicating that the HIV/AIDS epidemic is international in scope.This book deals with the mathematical and statistical techniques underlying the models used to understand the population dynamics of not only HIV/AIDS but also other infectious diseases. Attention is given to the development strategies for the prevention and control of the international epidemic within the frameworks of the models. Two distinguishing features of the book are the incorporation of stochastic and deterministic formulations within a unifying conceptual framework and the discussion of issues related to the mathematical designs of models, which are necessary for the rigorous utilization of computer-intensive methods. The book will be of value to applied mathematicians, biomathematicians, biostatisticians, epidemiologists and other scientists interested in applying mathematics and computers to not only the HIV/AIDS epidemic but also other fields of epidemiology.

Stochastic Analysis of AIDS Epidemiology

Stochastic Analysis of AIDS Epidemiology PDF

Author: Moremi Morire OreOluwapo Labeodan

Publisher:

Published: 2013

Total Pages:

ISBN-13:

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In this thesis, some issues about the human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) have been addressed by concentrating on the stochastic modelling of the dynamics of the viruses. The aim of this thesis is to determine parameters such as the mean number of free HIV, infectious free HIV and non-infectious free HIV which are essential in determining incubation period of the virus, the disease progression of an infected individual and the efficacy of the treatment used. This thesis comprises of six chapters. The first two chapters are introductory to the viruses and reasons why HIV-1 is given priority over HIV-2 are given. The pathogenesis of the virus is addressed. This is because knowledge of the pathogenesis and strains of the virus has become essential in the study of HIV in vivo dynamics which is still paving ways into extensive research of the ways to contain the disease better. In chapter three the distribution functions of the HIV incubation period and seroconversion time are determined via stochastic models by building on previous work of Lui et al. (1988) and Medley et al. (1988). Also AIDS incidence projection was done using the Backcalculation method. Chapter four deals with the formulation of stochastic model of the dynamics of HIV in an infected individual. Two stochastic models are proposed and analysed for the dynamics of the viral load in a HIV infected person and the multiplication process of the virions inside an infected T4 cell. Also a numerical illustration of the stochastic models derived is given. In chapter five, the T4 cell count which is considered one of the markers of disease progression in HIV infected individual is examined. WHO has recently advocated that countries encourage HIV infected individuals to commence antiretroviral treatments once their T4 cell count is 350 cells per ml of blood. This is because when the T4 cell count is low, the T4 cells are unable to mount an effective immune response against antigens (and any such foreign matters in the body) and consequently, the individual becomes susceptible to opportunistic infections and lymphomas. We developed a stochastic catastrophe model to obtain the mean, variance and covariance of the uninfected, infected and lysed T4 cells: also the amount of toxin produced in a HIV infected person from the time of infection to the present time is derived. A numerical illustration of the correlation structure between uninfected and infected T4 cells, and infected and lysed T4 cells is portrayed. Antiretrioviral treatments were introduced while we await a cure. Treatment with single drug failed due to the fact that HIV evolved rapidly because of its high replication rate. Thus drug resistance to single therapeutic treatment in HIV infected individuals has promoted research into combined treatments. In chapter six a stochastic model under combined therapeutic treatment is derived. Mean numbers of free HIV, infectious free HIV and non-infectious free HIV are obtained. Variance and co-variance structures of our parameters were obtained unlike in previous work of Perelson et al. (1996), Tan and Xiang (1999).

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems PDF

Author: W. Y. Tan

Publisher: World Scientific

Published: 2002

Total Pages: 464

ISBN-13: 9789810248697

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This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems.One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and the multilevel Gibbs sampling method to solve many problems in genetics, carcinogenesis, AIDS and other biomedical systems.As another feature, the book develops many state space models for many genetic problems, carcinogenesis, AIDS epidemiology and HIV pathogenesis. It shows in detail how to use the multilevel Gibbs sampling method to estimate (or predict) simultaneously the state variables and the unknown parameters in cancer chemotherapy, carcinogenesis, AIDS epidemiology and HIV pathogenesis. As a matter of fact, this book is the first to develop many state space models for many genetic problems, carcinogenesis and other biomedical problems.

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems (second Edition)

Stochastic Models with Applications to Genetics, Cancers, AIDS and Other Biomedical Systems (second Edition) PDF

Author: W. Y. Tan

Publisher: World Scientific

Published: 2015-10-28

Total Pages: 523

ISBN-13: 981439095X

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"This book presents a systematic treatment of Markov chains, diffusion processes and state space models, as well as alternative approaches to Markov chains through stochastic difference equations and stochastic differential equations. It illustrates how these processes and approaches are applied to many problems in genetics, carcinogenesis, AIDS epidemiology and other biomedical systems. One feature of the book is that it describes the basic MCMC (Markov chain and Monte Carlo) procedures and illustrates how to use the Gibbs sampling method and the multilevel Gibbs sampling method to solve many problems in genetics, carcinogenesis, AIDS and other biomedical systems. As another feature, the book develops many state space models for many genetic problems, carcinogenesis, AIDS epidemiology and HIV pathogenesis. It shows in detail how to use the multilevel Gibbs sampling method to estimate (or predict) simultaneously the state variables and the unknown parameters in cancer chemotherapy, carcinogenesis, AIDS epidemiology and HIV pathogenesis. As a matter of fact, this book is the first to develop several state space models for many genetic problems, carcinogenesis and other biomedical problems. To emphasize special applications to medical problems, in this new edition the book has added a new chapter to illustrate how to develop biologically-supported stochastic models and state space models of carcinogenesis in human beings. Specific examples include hidden Markov models and state space models for human colon cancer, human liver cancer and some human pediatric cancers such as retinoblastoma and hepatoblastoma. The book also gives examples to illustrate how to develop procedures to assess cancer risk of environmental agents through initiation-promotion protocols."--