ArticleTropical medicine & international health : TM & IH2014
Adjusting the HIV prevalence for non-respondents using mortality rates in an open cohort in northwest Tanzania.
Article in Tropical medicine & international health : TM & IH, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Cohort profile: internal migration in sub-Saharan Africa-The Migration and Health in Malawi (MHM) study.BMJ open · 2017Article
- How have ART treatment programmes changed the patterns of excess mortality in people living with HIV? Estimates from four countries in East and Southern Africa.Global health action · 2014Article
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5 authors.
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Abstract
objectiveTo estimate HIV prevalence in adults who have not tested for HIV using age-specific mortality rates and to adjust the overall population HIV prevalence to include both tested and untested adults.
methodsAn open cohort study was established since 1994 with demographic surveillance system (DSS) and five serological surveys conducted. Deaths from Kisesa DSS were used to estimate mortality rates and 95% confidence intervals by HIV status for 3- 5-year periods (1995-1999, 2000-2004, and 2005-2009). Assuming that mortality rates in individuals who did not test for HIV are similar to those in tested individuals, and dependent on age, sex and HIV status and HIV, prevalence was estimated.
resultsIn 1995-1999, mortality rates (per 1000 person years) were 43.7 (95% CI 35.7-53.4) for HIV positive, 2.6 (95% CI 2.1-3.2) in HIV negative and 16.4 (95% CI 14.4-18.7) in untested. In 2000-2004, mortality rates were 43.3 (95% CI 36.2-51.9) in HIV positive, 3.3 (95% CI 2.8-4.0) in HIV negative and 11.9 (95% CI 10.5-13.6) in untested. In 2005-2009, mortality rates were 30.7 (95% CI 24.8-38.0) in HIV positive, 4.1 (95% CI 3.5-4.9) in HIV negative and 5.7 (95% CI 5.0-6.6) in untested residents. In the three survey periods (1995-1999, 2000-2004, 2005-2009), the adjusted period prevalences of HIV, including the untested, were 13.5%, 11.6% and 7.1%, compared with the observed prevalence in the tested of 6.0%, 6.8 and 8.0%. The estimated prevalence in the untested was 33.4%, 21.6% and 6.1% in the three survey periods.
conclusionThe simple model was able to estimate HIV prevalence where a DSS provided mortality data for untested residents.
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