BMC Infectious Diseases (Mar 2022)

Validity of InterVA model versus physician review of verbal autopsy for tracking tuberculosis-related mortality in Ethiopia

  • Haileleuel Bisrat,
  • Tsegahun Manyazewal,
  • Hussen Mohammed,
  • Bilal Shikur,
  • Getnet Yimer

DOI
https://doi.org/10.1186/s12879-022-07193-w
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 9

Abstract

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Abstract Background In most African countries where a legitimate vital registration system is lacking, physicians often review verbal autopsy (VA) data to determine the cause of death, while there are concerns about the routine practicality, accuracy, and reliability of this procedure. In Ethiopia where the burden of tuberculosis (TB) remains unacceptably high, reliable VA data are needed to guide intervention strategies. This study aimed to validate the InterVA model against the physician VA in tracking TB-related mortality in Ethiopia. Methods From a sample of deaths in Addis Ababa, Ethiopia, VAs were conducted on TB-related mortality, physician-certified verbal autopsy (PCVA) through multiple steps to ascertain the causes of death. InterVA model was used to interpret the causes of death. Estimates of TB-related deaths between physician reviews and the InterVA model were compared using Cohen’s Kappa (k), Receiver-operator characteristic (ROC) curve analysis, sensitivity, and specificity to compare agreement between PCVA and InterVA. Results A total of 8952 completed PCVA were used. The InterVA model had an optimal likelihood cut-off point sensitivity of 0.64 (95% CI: 59.0–69.0) and specificity of 0.95 (95% CI: 94.9–95.8). The area under the ROC curve was 0.79 (95% CI: 0.78–0.81). The level of agreement between physician reviews and the InterVA model to identifying TB-related mortality was moderate (k = 0.59, 95% CI: 0.57–0.61). Conclusion The InterVA model is a viable alternative to physician review for tracking TB-related causes of death in Ethiopia. From a public health perspective, InterVA helps to analyze the underlying causes of TB-related deaths cost-effectively using routine survey data and translate to policies and strategies in resource-constrained countries.

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