| Description |
1 online resource (610 pages) |
| Contents |
Chapter 1 Mathematical Models for HIV Transmission Among Injecting Drug Users Vincenzo Capasso and Daniela Morale; 1. Introduction; 2. One Population Model; 2.1. Force of infection and social rules; 2.2. Qualitative analysis; 3. Multipopulation Models; 3.1. The force of infection; 3.2. Interaction among different populations; 3.3. Qualitative analysis; 3.4. About the uniqueness of the positive endemic equilibrium; 4. The Multistage Model; 5. Multipopulation models with multiple stages of infection; References |
|
Chapter 2 Estimation of HIV Infection and Seroconversion Probabilities in IDU and Non-IDU Populations by State Space Models Wai-Yuan Tan, Li-Jun Zhang and Lih-Yuan Deng1. Introduction; 2. A Stochastic Model for HIV Infection and HIV Seroconversion; 2.1. Stochastic equations for the state variables; 2.2. The expected numbers of the state variables; 2.3. The probability distribution of the state variables; 3. Statistical Models and Data for HIV Seroconversion; 3.1. The time to event models for HIV seroconversion; 3.2. The data and a statistic model for seroconversion |
|
3.3. Statistical inferences on HIV seroconversion3.4. The Bayesian approach for estimating seroconversion; 3.5. A likelihood ratio test for comparing several HIV seroconversion distributions; 3.6. Estimation of HIV infection; 4. A State Space Model for HIV Seroconversion; 4.1. The stochastic system model and the probability distribution of state variables; 4.2. The observation model and the probability distribution of the number of the observed seroconvertors; 4.3. The contribution to the observed number of seroconverters by the data; 4.4. The conditional posterior distribution |
|
5. Simultaneous Estimation of Unknown Parameters and State Variables6. An Illustrative Example; 7. Conclusions and Discussion; Acknowledgements; References; Chapter 3 A Bayesian Monte Carlo Integration Strategy for Connecting Stochastic Models of HIV / AIDS with Data Charles J. Mode; 1. Introduction; 2. Basic Bayesian Concepts; 3. A Monte Carlo Integration Strategy; 4. On the Conditional Likelihood Function of the Data Given a Point in the Parameter Space and a Realization of the Process; 5. A Weighted Boot Strap Method for Resampling the Posterior Distribution |
|
6. Resampling the Posterior Distribution Based on the Largest Probabilities7. A Criterion for Selecting Sample Size; 8. Strategies for Confronting Issues of Computer Performance; 9. On Choosing Prior Distributions of the Parameters; References; Chapter 4 A Class of Methods for HIV Contact Tracing in Cuba: Implications for Intervention and Treatment Ying-Hen Hsieh, Hector de Arazoza, Rachid Lounes and Jose Joanes; 1. Introduction; 2. The Models; 2.1. The k2X model; 2.2. The k2Y model; 2.3. The k2XY model; 2.4. The k2XY/(X + Y) model; 3. Fitting the Models to Cuban Data |
| Summary |
With contributions from an international team of leading researchers, the book pulls together updated research results in the area of HIV/AIDS modeling to provide readers with the latest information in the field. Topics covered include: AIDS epidemic models; vaccine models; models for HIV/cell dynamics and interactions; cellular kinetics; viral dynamics with antiviral treatments; modeling of drug resistance and quasispecies. Extensive deterministic models, statistical models, stochastic models and state space models on treating AIDS patients with anti-retroviral drugs are provided, as well as a |
| Notes |
4. Discussion and Concluding Remarks |
|
Print version record |
| Subject |
Medicine -- Mathematical models.
|
|
Biomathematics.
|
|
Biomathematics
|
|
Medicine -- Mathematical models
|
| Form |
Electronic book
|
| Author |
Wu, Hulin
|
| ISBN |
9789812569264 |
|
981256926X |
|
