Literature DB >> 19397583

Estimating HIV incidence based on combined prevalence testing.

Raji Balasubramanian1, Stephen W Lagakos.   

Abstract

Knowledge of incidence rates of HIV and other infectious diseases is important in evaluating the state of an epidemic as well as for designing interventional studies. Estimation of disease incidence from longitudinal studies can be expensive and time consuming. Alternatively, Janssen et al. (1998, Journal of the American Medical Association 280, 42-48) proposed the estimation of HIV incidence at a single point in time based on the combined use of a standard and "detuned" antibody assay. This article frames the problem from a longitudinal perspective, from which the maximum likelihood estimator of incidence is determined and compared with the Janssen estimator. The formulation also allows estimation for general situations, including different batteries of tests among subjects, inclusion of covariates, and a comparative evaluation of different test batteries to help guide study design. The methods are illustrated with data from an HIV interventional trial and a seroprevalence survey recently conducted in Botswana.

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Year:  2009        PMID: 19397583      PMCID: PMC3449098          DOI: 10.1111/j.1541-0420.2009.01242.x

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


  15 in total

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2.  Estimating HIV incidence rates from age prevalence data in epidemic situations.

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3.  Quantitative detection of increasing HIV type 1 antibodies after seroconversion: a simple assay for detecting recent HIV infection and estimating incidence.

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4.  Probability of viremia with HBV, HCV, HIV, and HTLV among tissue donors in the United States.

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5.  The AIDS epidemic in India: a new method for estimating current human immunodeficiency virus (HIV) incidence rates.

Authors:  R Brookmeyer; T Quinn; M Shepherd; S Mehendale; J Rodrigues; R Bollinger
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6.  Validation of a method to estimate age-specific human immunodeficiency virus (HIV) incidence rates in developing countries using population-based seroprevalence data.

Authors:  T Saidel; D Sokal; J Rice; T Buzingo; S Hassig
Journal:  Am J Epidemiol       Date:  1996-08-01       Impact factor: 4.897

7.  Estimation of current human immunodeficiency virus incidence rates from a cross-sectional survey using early diagnostic tests.

Authors:  R Brookmeyer; T C Quinn
Journal:  Am J Epidemiol       Date:  1995-01-15       Impact factor: 4.897

8.  Time course of detection of viral and serologic markers preceding human immunodeficiency virus type 1 seroconversion: implications for screening of blood and tissue donors.

Authors:  M P Busch; L L Lee; G A Satten; D R Henrard; H Farzadegan; K E Nelson; S Read; R Y Dodd; L R Petersen
Journal:  Transfusion       Date:  1995-02       Impact factor: 3.157

9.  Human immunodeficiency virus-1 and hepatitis C virus RNA among South African blood donors: estimation of residual transfusion risk and yield of nucleic acid testing.

Authors:  C T Fang; S P Field; M P Busch; A du P Heyns
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10.  HIV type 1 incidence estimates by detection of recent infection from a cross-sectional sampling of injection drug users in Bangkok: use of the IgG capture BED enzyme immunoassay.

Authors:  Dale J Hu; Suphak Vanichseni; Philip A Mock; Nancy L Young; Trudy Dobbs; Robert H Byers; Kachit Choopanya; Frits van Griensven; Dwip Kitayaporn; J Steven McDougal; Jordan W Tappero; Timothy D Mastro; Bharat S Parekh
Journal:  AIDS Res Hum Retroviruses       Date:  2003-09       Impact factor: 2.205

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  9 in total

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2.  Augmented cross-sectional studies with abbreviated follow-up for estimating HIV incidence.

Authors:  B Claggett; S W Lagakos; R Wang
Journal:  Biometrics       Date:  2011-06-13       Impact factor: 2.571

3.  On the use of adjusted cross-sectional estimators of HIV incidence.

Authors:  Rui Wang; Stephen W Lagakos
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4.  Augmented cross-sectional prevalence testing for estimating HIV incidence.

Authors:  Rui Wang; Stephen W Lagakos
Journal:  Biometrics       Date:  2010-09       Impact factor: 2.571

5.  A likelihood estimation of HIV incidence incorporating information on past prevalence.

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

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7.  Seroconverting blood donors as a resource for characterising and optimising recent infection testing algorithms for incidence estimation.

Authors:  Reshma Kassanjee; Alex Welte; Thomas A McWalter; Sheila M Keating; Marion Vermeulen; Susan L Stramer; Michael P Busch
Journal:  PLoS One       Date:  2011-06-09       Impact factor: 3.240

8.  A general HIV incidence inference scheme based on likelihood of individual level data and a population renewal equation.

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9.  Efficient estimation of human immunodeficiency virus incidence rate using a pooled cross-sectional cohort study design.

Authors:  Kesaobaka Molebatsi; Lesego Gabaitiri; Lucky Mokgatlhe; Sikhulile Moyo; Simani Gaseitsiwe; Kathleen E Wirth; Victor DeGruttola; Eric Tchetgen Tchetgen
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  9 in total

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