Literature DB >> 7846403

Using time of first positive HIV test and other auxiliary data in back-projection of AIDS incidence.

I C Marschner1.   

Abstract

Estimation of HIV incidence by the method of back-projection typically uses data on the time of diagnosis of AIDS cases, together with known information about the incubation distribution of AIDS. This paper discusses back-projection using auxiliary data on AIDS cases, particularly the time of first positive HIV test. We discuss the possibility that certain types of auxiliary data, including time of first positive test, can be useful in back-projection because they provide extra information about the incubation period of AIDS cases. Under a back-projection model, theoretical efficiency calculations are given comparing back-projection with and without the time of first positive HIV test of AIDS cases. These calculations suggest that such data have the potential to significantly improve HIV incidence estimates, particularly in the recent past. Smoothed non-parametric estimates of both HIV incidence and time-dependent testing rates are described. These can be obtained using the EM algorithm, in conjunction with a smoothing step or a penalized likelihood. The benefit of these methods in practice needs to be assessed as such data become available.

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Year:  1994        PMID: 7846403     DOI: 10.1002/sim.4780131908

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  6 in total

1.  HIV/AIDS surveillance in Italy: the potential misinterpretation of time trends.

Authors:  P Pezzotti; C Piovesan; G Rezza; P Ferraro
Journal:  Am J Public Health       Date:  1997-03       Impact factor: 9.308

2.  The status of national HIV case surveillance, United States 2006.

Authors:  M Kathleen Glynn; Lisa M Lee; Matthew T McKenna
Journal:  Public Health Rep       Date:  2007       Impact factor: 2.792

3.  Estimation of HIV incidence in the United States.

Authors:  H Irene Hall; Ruiguang Song; Philip Rhodes; Joseph Prejean; Qian An; Lisa M Lee; John Karon; Ron Brookmeyer; Edward H Kaplan; Matthew T McKenna; Robert S Janssen
Journal:  JAMA       Date:  2008-08-06       Impact factor: 56.272

4.  A Bayesian hierarchical model with novel prior specifications for estimating HIV testing rates.

Authors:  Qian An; Jian Kang; Ruiguang Song; H Irene Hall
Journal:  Stat Med       Date:  2015-11-15       Impact factor: 2.373

5.  Estimating the incidence and diagnosed proportion of HIV infections in Japan: a statistical modeling study.

Authors:  Hiroshi Nishiura
Journal:  PeerJ       Date:  2019-01-15       Impact factor: 2.984

Review 6.  Modeling methods for estimating HIV incidence: a mathematical review.

Authors:  Xiaodan Sun; Hiroshi Nishiura; Yanni Xiao
Journal:  Theor Biol Med Model       Date:  2020-01-22       Impact factor: 2.432

  6 in total

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