Evaluating the InterVA model for determining AIDS mortality from verbal autopsies in the adult population of Addis Ababa.


Tensou, B; Araya, T; Telake, DS; Byass, P; Berhane, Y; Kebebew, T; Sanders, EJ; Reniers, G; (2010) Evaluating the InterVA model for determining AIDS mortality from verbal autopsies in the adult population of Addis Ababa. Tropical medicine & international health, 15 (5). pp. 547-53. ISSN 1360-2276 DOI: https://doi.org/10.1111/j.1365-3156.2010.02484.x

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Abstract

OBJECTIVE: To evaluate the performance of a verbal autopsy (VA) expert algorithm (the InterVA model) for diagnosing AIDS mortality against a reference standard from hospital records that include HIV serostatus information in Addis Ababa, Ethiopia. METHODS: Verbal autopsies were conducted for 193 individuals who visited a hospital under surveillance during terminal illness. Decedent admission diagnosis and HIV serostatus information are used to construct two reference standards (AIDS vs. other causes of death and TB/AIDS vs. other causes). The InterVA model is used to interpret the VA interviews; and the sensitivity, specificity and cause-specific mortality fractions are calculated as indicators of the diagnostic accuracy of the InterVA model. RESULTS: The sensitivity and specificity of the InterVA model for diagnosing AIDS are 0.82 (95% CI: 0.74-0.89) and 0.76 (95% CI: 0.64-0.86), respectively. The sensitivity and specificity for TB/AIDS are 0.91 (95% CI: 0.85-0.96) and 0.78 (95% CI: 0.63-0.89), respectively. The AIDS-specific mortality fraction estimated by the model is 61.7% (95% CI: 54-69%), which is close to 64.7% (95% CI: 57-72%) in the reference standard. The TB/AIDS mortality fraction estimated by the model is 73.6% (95% CI: 67-80%), compared to 74.1% (95% CI: 68-81%) in the reference standard. CONCLUSION: The InterVA model is an easy to use and cheap alternative to physician review for assessing AIDS mortality in populations without vital registration and medical certification of causes of death. The model seems to perform better when TB and AIDS are combined, but the sample is too small to statistically confirm that.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Population Health (2012- ) > Dept of Population Studies (1974-2012)
Faculty of Epidemiology and Population Health > Dept of Population Health (2012- )
Research Centre: Population Studies Group
PubMed ID: 20214760
Web of Science ID: 276496100008
URI: http://researchonline.lshtm.ac.uk/id/eprint/449575

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