Differences in fertility by HIV serostatus and adjusted HIV prevalence data from an antenatal clinic in northern Uganda

2006 ◽  
Vol 11 (2) ◽  
pp. 182-187 ◽  
Author(s):  
Massimo Fabiani ◽  
Barbara Nattabi ◽  
Emingtone O. Ayella ◽  
Martin Ogwang ◽  
Silvia Declich
Keyword(s):  
Antenatal Clinic ◽  
Hiv Prevalence ◽  
Northern Uganda ◽  
Prevalence Data ◽  
Hiv Serostatus

scholarly journals Use of Antenatal Clinic Surveillance to Assess the Effect of Sexual Behavior on HIV Prevalence in Young Women in Karonga District, Malawi

2008 ◽  
Vol 48 (2) ◽  
pp. 196-202 ◽  
Author(s):  
Amelia Catharine Crampin ◽  
Andreas Jahn ◽  
Masiya Kondowe ◽  
Bagrey M Ngwira ◽  
Joanne Hemmings ◽  
...  
Keyword(s):  
Sexual Behavior ◽  
Young Women ◽  
Antenatal Clinic ◽  
Hiv Prevalence

Proximity to sex work sites is not associated with higher HIV prevalence in the general population in Zimbabwe

2021 ◽  
Author(s):  
Mariëlle Kloek ◽  
Caroline Bulstra ◽  
Sungai Chabata ◽  
Elizabeth Fearon ◽  
Isaac Taramusi ◽  
...  
Keyword(s):  
General Population ◽  
Sex Work ◽  
Sex Workers ◽  
Hiv Prevalence ◽  
Demographic And Health Surveys ◽  
African Countries ◽  
Prevalence Data ◽  
Individual Level ◽  
Shortest Distance ◽  
Survey Sample

Abstract In Zimbabwe, as in other East and Southern African countries, HIV prevalence is largely geographically heterogeneous. We determined if, and to what extent, this heterogeneity is associated with proximity to sex work sites by type of site (city, economic growth point, international, seasonal, or transport), using Demographic and Health Surveys location-specific HIV prevalence data—including 16,121 individuals (aged 15-49 years) from 400 sample locations—and Centre for Sexual Health and HIV/AIDS Research data on locations of 56 sex work sites throughout Zimbabwe. We conducted univariate and multivariate multilevel logistic regression to determine the association between sex work proximity—calculated as the shortest distance by road from each survey sample location to the nearest sex work site—and HIV seropositivity. We found no association between locations of sex work and heterogeneity in HIV prevalence in the general population, possibly explained by the mobile nature of both female sex workers and their clients as individual-level indicators of sex work were still significantly associated with HIV.

HIV prevalence data mount, patterns seen emerging by end of this year

JAMA ◽  
1988 ◽  
Vol 260 (13) ◽  
pp. 1829-1830 ◽  
Author(s):  
M. F. Goldsmith
Keyword(s):  
Hiv Prevalence ◽  
Prevalence Data

Adjusting HIV Prevalence Data From a Program for the Prevention of Mother-to-Child Transmission for Surveillance Purposes in Uganda

2007 ◽  
Vol 46 (3) ◽  
pp. 328-331 ◽  
Author(s):  
Massimo Fabiani ◽  
Zabulon Yoti ◽  
Barbara Nattabi ◽  
Emintone O Ayella ◽  
Alex A Opio ◽  
...  
Keyword(s):  
Hiv Prevalence ◽  
Mother To Child Transmission ◽  
Child Transmission ◽  
Prevalence Data ◽  
Mother To Child

scholarly journals Antenatal clinic-based HIV prevalence in Zambia: Declining trends but sharp local contrasts in young women

2006 ◽  
Vol 11 (6) ◽  
pp. 917-928 ◽  
Author(s):  
Ingvild F. Sandoy ◽  
Gunnar Kvale ◽  
Charles Michelo ◽  
Knut Fylkesnes
Keyword(s):  
Young Women ◽  
Antenatal Clinic ◽  
Hiv Prevalence

Predictors of HIV Serostatus among HIV Discordant Couples in Lusaka, Zambia and Female Antenatal Clinic Attendants in Kigali, Rwanda

2005 ◽  
Vol 21 (1) ◽  
pp. 5-12 ◽  
Author(s):  
Kayvon Modjarrad ◽  
Isaac Zulu ◽  
Etienne Karita ◽  
Nzali Kancheya ◽  
Ellen Funkhouser ◽  
...  
Keyword(s):  
Antenatal Clinic ◽  
Discordant Couples ◽  
Hiv Serostatus

scholarly journals The implementation of EPP software using HIV prevalence data from studies conducted in Greece

Retrovirology ◽  
2010 ◽  
Vol 7 (S1) ◽  
Author(s):  
Georgios Nikolopoulos ◽  
Chryssa Tsiara ◽  
Chryssoula Botsi
Keyword(s):  
Hiv Prevalence ◽  
Prevalence Data

scholarly journals Challenges in estimating HIV prevalence trends and geographical variation in HIV prevalence using antenatal data: Insights from mathematical modelling

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242595
Author(s):  
Leigh F. Johnson ◽  
Mmamapudi Kubjane ◽  
Jeffrey W. Eaton
Keyword(s):  
South Africa ◽  
Pregnant Women ◽  
Rural Areas ◽  
Urban Areas ◽  
Geographical Variation ◽  
Sexual Experience ◽  
Hiv Prevalence ◽  
Hiv Incidence ◽  
African Countries ◽  
Prevalence Data

Background HIV prevalence data among pregnant women have been critical to estimating HIV trends and geographical patterns of HIV in many African countries. Although antenatal HIV prevalence data are known to be biased representations of HIV prevalence in the general population, mathematical models have made various adjustments to control for known sources of bias, including the effect of HIV on fertility, the age profile of pregnant women and sexual experience. Methods and findings We assessed whether assumptions about antenatal bias affect conclusions about trends and geographical variation in HIV prevalence, using simulated datasets generated by an agent-based model of HIV and fertility in South Africa. Results suggest that even when controlling for age and other previously-considered sources of bias, antenatal bias in South Africa has not been constant over time, and trends in bias differ substantially by age. Differences in the average duration of infection explain much of this variation. We propose an HIV duration-adjusted measure of antenatal bias that is more stable, which yields higher estimates of HIV incidence in recent years and at older ages. Simpler measures of antenatal bias, which are not age-adjusted, yield estimates of HIV prevalence and incidence that are too high in the early stages of the HIV epidemic, and that are less precise. Antenatal bias in South Africa is substantially greater in urban areas than in rural areas. Conclusions Age-standardized approaches to defining antenatal bias are likely to improve precision in model-based estimates, and further recency adjustments increase estimates of HIV incidence in recent years and at older ages. Incompletely adjusting for changing antenatal bias may explain why previous model estimates overstated the early HIV burden in South Africa. New assays to estimate the fraction of HIV-positive pregnant women who are recently infected could play an important role in better estimating antenatal bias.

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