Literature DB >> 21505383

Estimating the HIV incidence rate: recent and future developments.

Timothy B Hallett1.   

Abstract

PURPOSE OF REVIEW: To describe the needs for information on the rate of new HIV infections (incidence) in epidemics and review developments in various methods for its estimation. RECENT
FINDINGS: Epidemiological methods for estimating incidence with models using prevalence data have been useful, but the expansion of antiretroviral treatment programmes could now challenge their reliability. Laboratory-based HIV incidence assays that can be used to measure HIV incidence using a cross-sectional survey, provide a promising concept, but current technologies have not been sufficiently accurate. New statistical methods have been developed that show that if the properties of the assay are properly measured then unbiased estimates of incidence can be derived, and that assays meeting certain criteria can produce estimates of acceptable accuracy and precision. Encouragingly, some new assays and algorithms show signs of potentially meeting those criteria. Among the next challenges will be the systematic evaluation of assay performance in many different types of specimen and the validation of those methods through comparison with other measurements of incidence.
SUMMARY: Recent developments in epidemiological and incidence assay-based methods of measuring incidence have been substantial and are likely to eventually lead to a revolution in the way that worldwide HIV epidemics are routinely tracked.

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Year:  2011        PMID: 21505383      PMCID: PMC3083833          DOI: 10.1097/COH.0b013e328343bfdb

Source DB:  PubMed          Journal:  Curr Opin HIV AIDS        ISSN: 1746-630X            Impact factor:   4.283


  56 in total

1.  Time from HIV-1 seroconversion to AIDS and death before widespread use of highly-active antiretroviral therapy: a collaborative re-analysis. Collaborative Group on AIDS Incubation and HIV Survival including the CASCADE EU Concerted Action. Concerted Action on SeroConversion to AIDS and Death in Europe.

Authors: 
Journal:  Lancet       Date:  2000-04-01       Impact factor: 79.321

Review 2.  Measuring trends in prevalence and incidence of HIV infection in countries with generalised epidemics.

Authors:  P D Ghys; E Kufa; M V George
Journal:  Sex Transm Infect       Date:  2006-04       Impact factor: 3.519

3.  Estimating incidence of HIV infection in Uganda.

Authors:  Jim Todd; Tom Lutalo; Pontiano Kaleebu
Journal:  JAMA       Date:  2009-01-14       Impact factor: 56.272

4.  Estimating incidence of HIV infection in Uganda.

Authors:  Timothy Hallett; Geoff Garnett
Journal:  JAMA       Date:  2009-01-14       Impact factor: 56.272

Review 5.  Accuracy of serological assays for detection of recent infection with HIV and estimation of population incidence: a systematic review.

Authors:  Rebecca Guy; Judy Gold; Jesus M García Calleja; Andrea A Kim; Bharat Parekh; Michael Busch; Thomas Rehle; John Hargrove; Robert S Remis; John M Kaldor
Journal:  Lancet Infect Dis       Date:  2009-12       Impact factor: 25.071

6.  Estimating incidence from age-specific prevalence for irreversible diseases with differential mortality.

Authors:  M J Podgor; M C Leske
Journal:  Stat Med       Date:  1986 Nov-Dec       Impact factor: 2.373

7.  Monitoring of HIV-1 infection prevalence and trends in the general population using pregnant women as a sentinel population: 9 years experience from the Kagera region of Tanzania.

Authors:  G Kwesigabo; J Z Killewo; W Urassa; E Mbena; F Mhalu; J L Lugalla; C Godoy; G Biberfeld; M Emmelin; S Wall; A Sandstrom
Journal:  J Acquir Immune Defic Syndr       Date:  2000-04-15       Impact factor: 3.731

8.  Antenatal clinic HIV data found to underestimate actual prevalence declines: evidence from Zambia.

Authors:  Charles Michelo; Ingvild Sandøy; Knut Fylkesnes
Journal:  Trop Med Int Health       Date:  2008-02       Impact factor: 2.622

9.  Investigating the utility of the HIV-1 BED capture enzyme immunoassay using cross-sectional and longitudinal seroconverter specimens from Africa.

Authors:  Etienne Karita; Matt Price; Eric Hunter; Elwyn Chomba; Susan Allen; Lin Fei; Anatoli Kamali; Eduard J Sanders; Omu Anzala; Michael Katende; Nzeera Ketter
Journal:  AIDS       Date:  2007-02-19       Impact factor: 4.177

10.  Flexible epidemiological model for estimates and short-term projections in generalised HIV/AIDS epidemics.

Authors:  Daniel R Hogan; Alan M Zaslavsky; James K Hammitt; Joshua A Salomon
Journal:  Sex Transm Infect       Date:  2010-12       Impact factor: 3.519

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  27 in total

1.  Short Communication: Defining optimality of a test for recent infection for HIV incidence surveillance.

Authors:  Reshma Kassanjee; Thomas A McWalter; Alex Welte
Journal:  AIDS Res Hum Retroviruses       Date:  2013-10-26       Impact factor: 2.205

2.  Estimating False-Recent Classification for the Limiting-Antigen Avidity EIA and BED-Capture Enzyme Immunoassay in Vietnam: Implications for HIV-1 Incidence Estimates.

Authors:  Neha S Shah; Yen T Duong; Linh-Vi Le; Nguyen Anh Tuan; Bharat S Parekh; Hoang Thi Thanh Ha; Quang Duy Pham; Cao Thi Thu Cuc; Trudy Dobbs; Tran Hong Tram; Truong Thi Xuan Lien; Nick Wagar; Chunfu Yang; Amy Martin; Mitchell Wolfe; Nguyen Tran Hien; Andrea A Kim
Journal:  AIDS Res Hum Retroviruses       Date:  2017-03-13       Impact factor: 2.205

3.  A new general biomarker-based incidence estimator.

Authors:  Reshma Kassanjee; Thomas A McWalter; Till Bärnighausen; Alex Welte
Journal:  Epidemiology       Date:  2012-09       Impact factor: 4.822

4.  Workshop summary: Novel biomarkers for HIV incidence assay development.

Authors:  Usha K Sharma; Marco Schito; Alex Welte; Christine Rousseau; Joseph Fitzgibbon; Brandon Keele; Stuart Shapiro; Andrew McMichael; David N Burns
Journal:  AIDS Res Hum Retroviruses       Date:  2012-02-24       Impact factor: 2.205

5.  Evaluation of the false recent classification rates of multiassay algorithms in estimating HIV type 1 subtype C incidence.

Authors:  Sikhulile Moyo; Tessa LeCuyer; Rui Wang; Simani Gaseitsiwe; Jia Weng; Rosemary Musonda; Hermann Bussmann; Madisa Mine; Susan Engelbrecht; Joseph Makhema; Richard Marlink; Marianna K Baum; Vladimir Novitsky; M Essex
Journal:  AIDS Res Hum Retroviruses       Date:  2013-09-06       Impact factor: 2.205

6.  More and better information to tackle HIV epidemics: towards improved HIV incidence assays.

Authors: 
Journal:  PLoS Med       Date:  2011-06-14       Impact factor: 11.069

7.  Is back-projection methodology still relevant for estimating HIV incidence from national surveillance data?

Authors:  Kylie-Ann Mallitt; David P Wilson; Ann McDonald; Handan Wand
Journal:  Open AIDS J       Date:  2012-09-07

8.  Towards estimation of HIV-1 date of infection: a time-continuous IgG-model shows that seroconversion does not occur at the midpoint between negative and positive tests.

Authors:  Helena Skar; Jan Albert; Thomas Leitner
Journal:  PLoS One       Date:  2013-04-16       Impact factor: 3.240

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

Authors:  Guy Severin Mahiane; Rachid Ouifki; Hilmarie Brand; Wim Delva; Alex Welte
Journal:  PLoS One       Date:  2012-09-12       Impact factor: 3.240

10.  Trends in HIV prevalence among young people in generalised epidemics: implications for monitoring the HIV epidemic.

Authors:  Mary Mahy; Jesus Maria Garcia-Calleja; Kimberly Anne Marsh
Journal:  Sex Transm Infect       Date:  2012-12       Impact factor: 3.519

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