OBJECTIVE: To compare HIV prevalence in antenatal clinics (ANC) and the general population, and to identify factors determining the differences that were found. DESIGN: Cross-sectional surveys in the general population and in ANC in three cities. METHODS: HIV prevalence measured in adults in the community was compared with that measured by sentinel surveillance in ANC in Yaoundé, Cameroon, Kisumu, Kenya, and Ndola, Zambia. RESULTS: In Yaoundé and Ndola, the HIV prevalence in ANC attenders was lower than that in women in the population overall, and for age groups over 20 years. In Kisumu, the HIV prevalence in ANC attenders was similar to that in women in the population at all ages. The only factors identified that influenced the results were age, marital status, parity, schooling, and contraceptive use. The HIV prevalence in women in ANC was similar to that in the combined male and female population aged 15-40 years in Yaoundé and Ndola, but overestimated it in Kisumu. In Yaoundé and Ndola, the overall HIV prevalence in men was approximated by using the age of the father of the child reported by ANC attenders, but this method overestimated the HIV prevalence in Kisumu, and did not give good age-specific estimates. CONCLUSION: Few factors influenced the difference in HIV prevalence between ANC and the population, which could aid the development of adjustment procedures to estimate population HIV prevalence. However, the differences between cities were considerable, making standard adjustments difficult. The method of estimating male HIV prevalence should be tested in other sites.
OBJECTIVE: To compare HIV prevalence in antenatal clinics (ANC) and the general population, and to identify factors determining the differences that were found. DESIGN: Cross-sectional surveys in the general population and in ANC in three cities. METHODS: HIV prevalence measured in adults in the community was compared with that measured by sentinel surveillance in ANC in Yaoundé, Cameroon, Kisumu, Kenya, and Ndola, Zambia. RESULTS: In Yaoundé and Ndola, the HIV prevalence in ANC attenders was lower than that in women in the population overall, and for age groups over 20 years. In Kisumu, the HIV prevalence in ANC attenders was similar to that in women in the population at all ages. The only factors identified that influenced the results were age, marital status, parity, schooling, and contraceptive use. The HIV prevalence in women in ANC was similar to that in the combined male and female population aged 15-40 years in Yaoundé and Ndola, but overestimated it in Kisumu. In Yaoundé and Ndola, the overall HIV prevalence in men was approximated by using the age of the father of the child reported by ANC attenders, but this method overestimated the HIV prevalence in Kisumu, and did not give good age-specific estimates. CONCLUSION: Few factors influenced the difference in HIV prevalence between ANC and the population, which could aid the development of adjustment procedures to estimate population HIV prevalence. However, the differences between cities were considerable, making standard adjustments difficult. The method of estimating male HIV prevalence should be tested in other sites.
Authors: Jorge O Alarcón; Heidi B Friedman; Silvia M Montano; Joseph R Zunt; King K Holmes; Gerald V Quinnan Journal: J Acquir Immune Defic Syndr Date: 2006-08-15 Impact factor: 3.731
Authors: Kimberly A Marsh; Constance A Nyamukapa; Christl A Donnelly; Jesus M Garcia-Calleja; Phillis Mushati; Geoffrey P Garnett; Edith Mpandaguta; Nicholas C Grassly; Simon Gregson Journal: J Int AIDS Soc Date: 2011-05-24 Impact factor: 5.396
Authors: Jeanne Françoise Kayibanda; Michel Alary; Raphaël Bitera; Adeline Kabeja; Ruton Hinda; Louis Munyakazi; Bassirou Chitou; Jean Philippe Gatarayiha Journal: Open AIDS J Date: 2011-03-30