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.
Contents:
- Biology and Epidemiology of HIV/AIDS
- Models of Incubation and Infectious Periods
- Continuous Time Markov and Semi-Markov Jump Processes
- Semi-Markov Jump Processes in Discrete Time
- Models of HIV Latency Based on a Log-Gaussian Process
- The Threshold Parameter of One-Type Branching Processes
- A Structural Approach to SIS and SIR Models
- Threshold Parameters for Multi-Type Branching Processes
- Computer Intensive Methods for the Multi-Type Case
- Nonlinear Stochastic Models in Homosexual Populations
- Stochastic Partnership Models in Homosexual Populations
- Heterosexual Population with Partnerships
- Age-Dependent Stochastic Models with Partnerships
- Epilogue — Future Research Directions
Readership: Mathematical & quantitative biologists, epidemiologists, mathematicians, operations research workers, statisticians and biostatisticians.
