Literature DB >> 11315072

Validating marker-based incidence estimates in repeatedly screened populations.

G A Satten1, R Janssen, M P Busch, S Datta.   

Abstract

Disease incidence (new cases of disease per person per year) is usually measured by using longitudinal data. However, several recent proposals for measuring the incidence of human immunodeficiency virus (HIV) rely on cross-sectional data only. These methods assume each person is only sampled once; however, in some instances, it is necessary to consider these cross-sectional methods when individuals are represented more than once in the survey sample. We derive an extension of the cross-sectional incidence estimator that is valid for data from repeatedly screened populations and show under what conditions our new estimator reduces to the old estimator. An example involving estimation of HIV incidence among repeat blood donors is presented.

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Year:  1999        PMID: 11315072     DOI: 10.1111/j.0006-341x.1999.01224.x

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


  3 in total

1.  Interpopulation variation in HIV testing promptness may introduce bias in HIV incidence estimates using the serologic testing algorithm for recent HIV seroconversion.

Authors:  Edward White; Gary Goldbaum; Steven Goodreau; Thomas Lumley; Stephen E Hawes
Journal:  Sex Transm Infect       Date:  2010-06-24       Impact factor: 3.519

2.  Stochastic models to demonstrate the effect of motivated testing on HIV incidence estimates using the serological testing algorithm for recent HIV seroconversion (STARHS).

Authors:  Edward W White; Thomas Lumley; Steven M Goodreau; Gary Goldbaum; Stephen E Hawes
Journal:  Sex Transm Infect       Date:  2010-11-08       Impact factor: 3.519

3.  Assessment of BED HIV-1 incidence assay in seroconverter cohorts: effect of individuals with long-term infection and importance of stable incidence.

Authors:  Janet M McNicholl; J Steven McDougal; Punneeporn Wasinrapee; Bernard M Branson; Michael Martin; Jordan W Tappero; Philip A Mock; Timothy A Green; Dale J Hu; Bharat Parekh
Journal:  PLoS One       Date:  2011-03-04       Impact factor: 3.240

  3 in total

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