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Verfasst von:Nyirenda, Makandwe [VerfasserIn]   i
 Zaba, Basia [VerfasserIn]   i
 Bärnighausen, Till [VerfasserIn]   i
 Hosegood, Victoria [VerfasserIn]   i
 Newell, Marie-Louise [VerfasserIn]   i
Titel:Adjusting HIV prevalence for survey non-response using mortality rates
Titelzusatz:an application of the method using surveillance data from rural South Africa
Verf.angabe:Makandwe Nyirenda, Basia Zaba, Till Bärnighausen, Victoria Hosegood, Marie-Louise Newell
E-Jahr:2010
Jahr:August 25, 2010
Umfang:8 S.
Fussnoten:Gesehen am 24.08.2017
Titel Quelle:Enthalten in: PLOS ONE
Ort Quelle:San Francisco, California, US : PLOS, 2006
Jahr Quelle:2010
Band/Heft Quelle:5(2010,8) Artikel-Nummer e12370, 8 Seiten
ISSN Quelle:1932-6203
Abstract:Background The main source of HIV prevalence estimates are household and population-based surveys; however, high refusal rates may hinder the interpretation of such estimates. The study objective was to evaluate whether population HIV prevalence estimates can be adjusted for survey non-response using mortality rates. Methodology/Principal Findings Data come from the longitudinal Africa Centre Demographic Information System (ACDIS), in rural South Africa. Mortality rates for persons tested and not tested in the 2005 HIV surveillance were available from routine household surveillance. Assuming HIV status among individuals contacted but who refused to test (non-response) is missing at random and mortality among non-testers can be related to mortality of those tested a mathematical model was developed. Non-parametric bootstrapping was used to estimate the 95% confidence intervals around the estimates. Mortality rates were higher among untested (16.9 per thousand person-years) than tested population (11.6 per thousand person-years), suggesting higher HIV prevalence in the former. Adjusted HIV prevalence for females (15-49 years) was 31.6% (95% CI 26.1-37.1) compared to observed 25.2% (95% CI 24.0-26.4). For males (15-49 years) adjusted HIV prevalence was 19.8% (95% CI 14.8-24.8), compared to observed 13.2% (95% CI 12.1-14.3). For both sexes (15-49 years) combined, adjusted prevalence was 27.5% (95% CI 23.6-31.3), and observed prevalence was 19.7% (95% CI 19.6-21.3). Overall, observed prevalence underestimates the adjusted prevalence by around 7 percentage points (37% relative difference). Conclusions/Significance We developed a simple approach to adjust HIV prevalence estimates for survey non-response. The approach has three features that make it easy to implement and effective in adjusting for selection bias than other approaches. Further research is needed to assess this approach in populations with widely available HIV treatment (ART).
DOI:doi:10.1371/journal.pone.0012370
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

kostenfrei: Volltext: http://dx.doi.org/10.1371/journal.pone.0012370
 kostenfrei: Volltext: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0012370
 DOI: https://doi.org/10.1371/journal.pone.0012370
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Adults
 Age groups
 Confidence intervals
 Death rates
 Demography
 HIV
 HIV infections
 South Africa
K10plus-PPN:1562712721
Verknüpfungen:→ Zeitschrift

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