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Validating the InterVA Model to Estimate the Burden of Mortality from Verbal Autopsy Data: A Population-Based Cross-Sectional Study

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  • Sebsibe Tadesse

Abstract

Background: In countries with incomplete or no vital registration systems, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. But in addition to being time and energy consuming, the method is liable to produce inconsistent results. The aim of this study is to validate the InterVA model for estimating the burden of mortality from verbal autopsy data by using physician review as a reference standard. Methods and Findings: A population-based cross-sectional study was conducted from March to April, 2012. All adults aged ≥14 years and died between 01 January, 2010 and 15 February, 2012 were included in the study. The verbal autopsy interviews were reviewed by the InterVA model and physicians to estimate cause-specific mortality fractions. Cohen’s kappa statistic, sensitivity, specificity, positive predictive value, and negative predictive value were applied to compare the agreement between the InterVA model and the physician review. A total of 408 adult deaths were studied. There was a general similarity and just slight differences between the InterVA model and the physicians in assigning cause-specific mortality. Both approaches showed an overall agreement in 298 (73%) cases [kappa = 0.49, 95% CI: 0.37-0.60]. The observed sensitivities and specificities across causes of death categories varied from 13.3% to 81.9% and 77.7% to 99.5%, respectively. Conclusions: In understanding the burden of disease and setting health intervention priorities in areas that lack reliable vital registration systems, an accurate analysis of verbal autopsies is essential. Therefore, users should be aware of the suboptimal performance of the InterVA model. Similar validation studies need to be undertaken considering the limitation of the physician review as gold standard since physicians may misinterpret some of the verbal autopsy data and finally reach a wrong conclusion of the cause of death.

Suggested Citation

  • Sebsibe Tadesse, 2013. "Validating the InterVA Model to Estimate the Burden of Mortality from Verbal Autopsy Data: A Population-Based Cross-Sectional Study," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-1, September.
    • Handle: RePEc:plo:pone00:0073463
    DOI: 10.1371/journal.pone.0073463
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    References listed on IDEAS

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    1. Peter Byass, 2007. "Who Needs Cause-of-Death Data?," PLOS Medicine, Public Library of Science, vol. 4(11), pages 1-2, November.
    2. Dean T. Jamison & Richard G. Feacham & Malegapuru W. Makgoba & Eduard R. Bos & Florence K. Baingana & Karen J. Hofman & Khama O. Rogo, 2006. "Disease and Mortality in Sub-Saharan Africa, Second Edition," World Bank Publications - Books, The World Bank Group, number 7050, December.
    3. Christopher J L Murray & Alan D Lopez & Dennis M Feehan & Shanon T Peter & Gonghuan Yang, 2007. "Validation of the Symptom Pattern Method for Analyzing Verbal Autopsy Data," PLOS Medicine, Public Library of Science, vol. 4(11), pages 1-15, November.
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