The 18 research articles of this volume discuss the major themes that have emerged from mathematical and statistical research in the epidemiology of HIV. The opening paper reviews important recent contributions. Five sections follow: Statistical Methodology and Forecasting, Infectivity and the HIV, Heterogeneity and HIV Transmission Dynamics, Social Dynamics and AIDS, and The Immune System and The HIV. In each, leading experts in AIDS epidemiology present the recent results. Some address the role of variable infectivity, heterogeneous mixing, and long periods of infectiousness in the dynamics of HIV; others concentrate on parameter estimation and short-term forecasting. The last section looks at the interaction between the HIV and the immune system.

The disease that came to be called acquired immunodeficiency syndrome (AIDS) was first identified in the summer of 1981. By that time, nearly 100,000 persons in the United States may have been infected with human immunodeficiency virus (HIV). By the time the routes of transmission were clearly identified and HIV was established as the cause of AIDS in 1983, over 300,000 people may have been infected. That number has continued to increase, with approximately 1,000,000 Americans believed to be infected in 1991. The epidemic is of great public health concern because HlV is infectious, causes severe morbidity and death in most if not all of those infected, and often occurs in relatively young persons. In addition, the cost of medical care for a person with HIV disease is high, and the medical care needs of HIV-infected persons place a severe burden on the medical care systems in many areas. Understanding and controlling the HIV epidemic is a particularly difficult challenge. The long and variable period between HIV infection and clinical disease makes it difficult both to forecast the future magnitude of the epidemic, which is important for health care planning, and to estimate the number infected in the last several years, which is important for monitoring the current status of the epidemic.

A self-contained and comprehensive guide to the mathematical modeling of disease transmission, appropriate for graduate students.

Infectious disease accounts for more death and disability globally than either non-infectious disease or injury. This book contains a breadth of different quantitative approaches to understanding the patterns of infectious diseases in populations, and the design of control strategies to lessen their effect. The contributors bring a great variety of mathematical expertise (including deterministic and stochastic modelling and statistical data analysis) and involvement in a wide range of applied fields across the spectrum of biological, medical and social sciences. The aim is to increase interaction between specialities by describing research on many of the infectious diseases that affect humans, including both viral diseases like measles and AIDS and tropical parasitic infections. The papers are divided into groups dealing with problems relating to transmissible diseases, vaccination strategies, the consequences of treatment interventions, the dynamics of immunity, heterogeneity of populations, and prediction.

This book is an outcome of the Second International Conference on Mathematical Population Dynamics. It is intended for mathematicians, statisticians, biologists, and medical researchers who are interested in recent advances in analyzing changes in populations of genes, cells, and tumors.

- 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.

The dynamics of infectious diseases represents one of the oldest and ri- est areas of mathematical biology. From the classical work of Hamer (1906) and Ross (1911) to the spate of more modern developments associated with Anderson and May, Dietz, Hethcote, Castillo-Chavez and others, the subject has grown dramatically both in volume and in importance. Given the pace of development, the subject has become more and more di?use, and the need to provide a framework for organizing the diversity of mathematical approaches has become clear. Enzo Capasso, who has been a major contributor to the mathematical theory, has done that in the present volume, providing a system for organizing and analyzing a wide range of models, depending on the str- ture of the interaction matrix. The ?rst class, the quasi-monotone or positive feedback systems, can be analyzed e?ectively through the use of comparison theorems, that is the theory of order-preserving dynamical systems; the s- ond, the skew-symmetrizable systems, rely on Lyapunov methods. Capasso develops the general mathematical theory, and considers a broad range of - amples that can be treated within one or the other framework. In so doing, he has provided the ?rst steps towards the uni?cation of the subject, and made an invaluable contribution to the Lecture Notes in Biomathematics. Simon A. Levin Princeton, January 1993 Author’s Preface to Second Printing In the Preface to the First Printing of this volume I wrote: \ . .

This is a collection of refereed papers presented at the 4th International Conference on Mathematical Population Dynamics. The selection of papers and their organization were made by the following persons: O Arino, D Axelrod, V Capasso, W Fitzgibbon, P Jagers, M Kimmel, D Kirschner, C Mode, B Novak, R Sachs, W Stephan, A Swierniak and H Thieme.It features some of the new trends in cell and human population dynamics. The main link between the two traits is that human populations of concern here are essentially those subject to cell diseases, either the processes of anarchic proliferation or those by which some cell lines are killed by an infectious agent.The volume is divided into 3 main parts. Each part is subdivided into chapters, each chapter concentrating on a specific aspect. Each aspect is illustrated by one or several examples, developed in sections contributed by several authors. A detailed introduction for each part will enable the reader to refer to chapters of interest. An index and a bibliography for each part is also included for easy reference.This book will be useful for those interested in the subject matter.

The goal of this book is to search for a balance between simple and analyzable models and unsolvable models which are capable of addressing important questions on population biology. Part I focusses on single species simple models including those which have been used to predict the growth of human and animal population in the past. Single population models are, in some sense, the building blocks of more realistic models -- the subject of Part II. Their role is fundamental to the study of ecological and demographic processes including the role of population structure and spatial heterogeneity -- the subject of Part III. This book, which will include both examples and exercises, is of use to practitioners, graduate students, and scientists working in the field.

This book grew out of the discussions and presentations that began during the Workshop on Emerging and Reemerging Diseases (May 17-21, 1999) sponsored by the Institute for Mathematics and its Application (IMA) at the University of Minnesota with the support of NIH and NSF. The workshop started with a two-day tutorial session directed at ecologists, epidemiologists, immunologists, mathematicians, and scientists interested in the study of disease dynamics. The core of this first volume, Volume 125, covers tutorial and research contributions on the use of dynamical systems (deterministic discrete, delay, PDEs, and ODEs models) and stochastic models in disease dynamics. The volume includes the study of cancer, HIV, pertussis, and tuberculosis. Beginning graduate students in applied mathematics, scientists in the natural, social, or health sciences or mathematicians who want to enter the fields of mathematical and theoretical epidemiology will find this book useful.