Mathematical And Statistical Approaches To Aids Epidemiology

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.

AIDS has appeared in more than 130 countries, and over 100,000 cases of AIDS have been reported in the U.S. alone. More and more, the public will be depending on statisticians to provide answers about the future course of this epidemic. This comprehensive work confronts the problems that are unique to AIDS research and unites them under a single conceptual framework. It focuses on methods for the design and analysis of epidemiologic studies, the natural history of AIDS and the transmission of HIV, methods for tracking and projecting the course of the epidemic, and statistical issues in therapeutic trials. The various methods of monitoring and forecasting this disease receive comprehensive treatment. These methods include back-calculation, which the authors developed; interpretation of survey data on HIV prevalence; mathematical models for HIV transmission; and approaches that combine different types of epidemiological data. Much of this material -- such as a discussion of methods for assessing safety of the blood supply, an evaluation of survey approaches, and methods to project pediatric AIDS incidence -- is not available in any other work.

In 1974, the Societal Institute of the Mathematical Sciences (SIMS) initiated a series of five-day Research Application Conferences (RAC's) at Alta, Utah, for the purpose of probing in depth societal fields in light of their receptivity to mathematical and statistical analysis. The first eleven conferences addressed ecosystems, epidemiology, energy, environmental health, time series and ecological processes, energy and health, energy conversion and fluid mechanics, environmental epidemiology: risk assessment, atomic bomb survival data: utilization and analysis, modem statistical methods in chronic disease epidemiology and scientific issues in quantitative cancer risk assess ment. These Proceedings are a result of the twelfth conference on Statistical Methodology for Study of the AIDS Epidemic which was held in 1991 at the Mathematical Sciences Research Institute, Berkeley, California. For five days, 45 speakers and observers contributed their expertise in the relevant biology and statistics. The presentations were timely and the discussion was both enlightening and at times spirited. Members of the Program Committee for the Conference were Klaus Dietz (University of Tiibingen, Germany), Vernon T. Farewell (University of Waterloo, Ontario), and Nicholas P. Jewell (University of California, Berke ley) (Chair). The Conference was supported by a grant to SIMS from the National Institute of Drug Abuse. D. L. Thomsen, Jr.

Quantitative Methods in HIV/AIDS Research provides a comprehensive discussion of modern statistical approaches for the analysis of HIV/AIDS data. The first section focuses on statistical issues in clinical trials and epidemiology that are unique to or particularly challenging in HIV/AIDS research; the second section focuses on the analysis of laboratory data used for immune monitoring, biomarker discovery and vaccine development; the final section focuses on statistical issues in the mathematical modeling of HIV/AIDS pathogenesis, treatment and epidemiology. This book brings together a broad perspective of new quantitative methods in HIV/AIDS research, contributed by statisticians and mathematicians immersed in HIV research, many of whom are current or previous leaders of CFAR quantitative cores. It is the editors’ hope that the work will inspire more statisticians, mathematicians and computer scientists to collaborate and contribute to the interdisciplinary challenges of understanding and addressing the AIDS pandemic.

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.

Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour is followed by the introduction of a simple methodology for the estimation of, the basic reproduction number,R . The use of this methodology 0 is illustrated, using regional data for 1918–1919 and 1968 in uenza pandemics.

- 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.