OBJECTIVES: To find a simple and robust method for adjusting ante-natal clinic data on HIV prevalence to represent prevalence in the general female population in the same age range, allowing for fertility differences by HIV status. BACKGROUND: HIV prevalence comparisons for pregnant women and women in the general community show that prevalence in the latter is significantly higher than in the former. An adjustment procedure is needed that is specific for the demographic and epidemiological circumstances of a particular population, making maximum use of data that can easily be collected in ante-natal clinics or are widely available from secondary sources. METHODS: Birth interval length data are used to allow for subfertility among HIV-positive women. To allow for infertility, relative HIV prevalence ratios for fertile and infertile women obtained in community surveys in populations with similar levels of contraception use are applied to demographic survey data that describe the structure of the population not at risk of child-bearing. RESULTS: For populations with low contraception use, the procedure yields estimates of general female HIV prevalence of 35-65% higher than the observed ante-natal prevalence, depending on population structure. Results were verified using general population prevalence data collected in Kisesa (Tanzania) and Masaka (Uganda). For high contraception use populations, adjusted values range from 15% higher to 5% lower, but only limited verification has been possible so far. CONCLUSIONS: The procedure is suitable for estimating general female HIV prevalence in low contraception use populations, but the high contraception variant needs further testing before it can be applied widely.
OBJECTIVES: To find a simple and robust method for adjusting ante-natal clinic data on HIV prevalence to represent prevalence in the general female population in the same age range, allowing for fertility differences by HIV status. BACKGROUND: HIV prevalence comparisons for pregnant women and women in the general community show that prevalence in the latter is significantly higher than in the former. An adjustment procedure is needed that is specific for the demographic and epidemiological circumstances of a particular population, making maximum use of data that can easily be collected in ante-natal clinics or are widely available from secondary sources. METHODS: Birth interval length data are used to allow for subfertility among HIV-positive women. To allow for infertility, relative HIV prevalence ratios for fertile and infertile women obtained in community surveys in populations with similar levels of contraception use are applied to demographic survey data that describe the structure of the population not at risk of child-bearing. RESULTS: For populations with low contraception use, the procedure yields estimates of general female HIV prevalence of 35-65% higher than the observed ante-natal prevalence, depending on population structure. Results were verified using general population prevalence data collected in Kisesa (Tanzania) and Masaka (Uganda). For high contraception use populations, adjusted values range from 15% higher to 5% lower, but only limited verification has been possible so far. CONCLUSIONS: The procedure is suitable for estimating general female HIV prevalence in low contraception use populations, but the high contraception variant needs further testing before it can be applied widely.
Authors: R G White; E Vynnycky; J R Glynn; A C Crampin; A Jahn; F Mwaungulu; O Mwanyongo; H Jabu; H Phiri; N McGrath; B Zaba; P E M Fine Journal: Epidemiol Infect Date: 2007-01-12 Impact factor: 2.451
Authors: M Urassa; Y Kumogola; R Isingo; G Mwaluko; B Makelemo; K Mugeye; T Boerma; T Calleja; E Slaymaker; B Zaba Journal: Sex Transm Infect Date: 2006-08 Impact factor: 3.519
Authors: Yusufu Kumogola; Emma Slaymaker; Basia Zaba; Julius Mngara; Raphael Isingo; John Changalucha; Patrick Mwidunda; Daniel Kimaro; Mark Urassa Journal: BMC Public Health Date: 2010-09-13 Impact factor: 3.295
Authors: R Kinoshita-Moleka; J S Smith; J Atibu; A Tshefu; J Hemingway-Foday; M Hobbs; J Bartz; M A Koch; A W Rimoin; R W Ryder Journal: Epidemiol Infect Date: 2007-11-21 Impact factor: 2.451
Authors: Munyaradzi P Mapingure; Sia Msuya; Nyaradzai E Kurewa; Marshal W Munjoma; Noel Sam; Mike Z Chirenje; Simbarashe Rusakaniko; Letten F Saugstad; Sake J de Vlas; Babill Stray-Pedersen Journal: J Int AIDS Soc Date: 2010-11-16 Impact factor: 5.396