Literature DB >> 11338334

Advances in medical statistics arising from the AIDS epidemic.

N G Becker1, I C Marschner.   

Abstract

Many statisticians have contributed to studies of the HIV epidemic and progression to AIDS. They have developed new statistical methodology, where needed, to address HIV-related issues. The transfer of methods from one area to another often involves a substantial delay. This paper points to methods that were developed in the HIV context and have either already found applications in other areas of medical research or have the potential for such applications, with the hope that this will promote a speedier transfer of the research methods. Among the new tools that HIV studies have placed firmly into the pool of statistical methods for medical research are the methods of back-calculation, methods for the analysis of retrospective ascertainment data and methods of analysis for the combined data from clinical trials and associated longitudinal studies. Notions that have been stimulated substantially are use of surrogate endpoints in clinical trials and screening blood products by the use of pooled serum samples. Research activity in many other areas has been boosted substantially through contributions motivated by HIV/AIDS studies. Noteworthy examples are analyses for doubly-censored lifetime data and methods for assessing vaccines for transmissible diseases.

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Year:  2001        PMID: 11338334     DOI: 10.1177/096228020101000204

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  3 in total

1.  Bayesian evidence synthesis for a transmission dynamic model for HIV among men who have sex with men.

Authors:  A M Presanis; D De Angelis; A Goubar; O N Gill; A E Ades
Journal:  Biostatistics       Date:  2011-04-27       Impact factor: 5.899

2.  Predicting super spreading events during the 2003 severe acute respiratory syndrome epidemics in Hong Kong and Singapore.

Authors:  Yuguo Li; Ignatius T S Yu; Pengcheng Xu; J H W Lee; Tze Wai Wong; Peng Lim Ooi; Adrian C Sleigh
Journal:  Am J Epidemiol       Date:  2004-10-15       Impact factor: 4.897

3.  Back-projection of COVID-19 diagnosis counts to assess infection incidence and control measures: analysis of Australian data.

Authors:  I C Marschner
Journal:  Epidemiol Infect       Date:  2020-05-18       Impact factor: 2.451

  3 in total

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