Literature DB >> 8805756

AIDS, epidemics, and statistics.

R Brookmeyer1.   

Abstract

Statistical thinking has made significant contributions to our understanding of epidemics. Examples where statistics has played an important role in the Acquired Immunodeficiency Syndrome (AIDS) epidemic include estimating the number of individuals infected with the human immunodeficiency virus, estimating the incubation period of the disease, studying the etiology of the disease, and monitoring and forecasting the course of the epidemic. Some parallels with other epidemics in history are drawn. The AIDS epidemic has also raised important questions about the design of clinical studies and whether classical approaches are sufficiently flexible to provide timely answers to therapeutic questions in a growing epidemic. In a public crisis, there is a sense of urgency and data may be collected with unusual sampling schemes and inherent biases. Attention needs to be paid as much to sampling variation as to systematic sources of bias. Accurate disease surveillance data and methods for analyzing such data are crucial for detecting and monitoring future epidemics. There will almost certainly be new epidemics in the future, either of old diseases resurfacing or of new diseases, and statistical reasoning will continue to play a significant role in addressing the challenges of these public health crises.

Entities:  

Keywords:  Acquired Immunodeficiency Syndrome; Bias; Data Collection--EV; Diseases; Epidemics; Error Sources; Estimation Technics; Hiv Infections; Measurement; Research Methodology; Study Design--EV; Viral Diseases; World

Mesh:

Year:  1996        PMID: 8805756

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  5 in total

1.  A Semi-stationary Copula Model Approach for Bivariate Survival Data with Interval Sampling.

Authors:  Hong Zhu; Mei-Cheng Wang
Journal:  Int J Biostat       Date:  2015-05       Impact factor: 0.968

Review 2.  A review of back-calculation techniques and their potential to inform mitigation strategies with application to non-transmissible acute infectious diseases.

Authors:  Joseph R Egan; Ian M Hall
Journal:  J R Soc Interface       Date:  2015-05-06       Impact factor: 4.118

3.  Missing link survival analysis with applications to available pandemic data.

Authors:  María Luz Gámiz; Enno Mammen; María Dolores Martínez-Miranda; Jens Perch Nielsen
Journal:  Comput Stat Data Anal       Date:  2021-12-13       Impact factor: 1.681

4.  Early efforts in modeling the incubation period of infectious diseases with an acute course of illness.

Authors:  Hiroshi Nishiura
Journal:  Emerg Themes Epidemiol       Date:  2007-05-11

5.  Lessons from previous predictions of HIV/AIDS in the United States and Japan: epidemiologic models and policy formulation.

Authors:  Hiroshi Nishiura
Journal:  Epidemiol Perspect Innov       Date:  2007-06-13
  5 in total

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