Cause of death distribution with InterVA and physician coding in a rural area of Burkina Faso
2012 (English)In: Tropical medicine & international health, ISSN 1360-2276, E-ISSN 1365-3156, Vol. 17, no 7, 904-913 p.Article in journal (Refereed) Published
Objectives To compare the cause of death distribution using the Physician Coded Verbal Autopsy approach versus the Interpreting Verbal Autopsy model, based on information from a French verbal autopsy questionnaire, in rural north-western Burkina Faso. Methods Data from 5649 verbal autopsy questionnaires reviewed by local physicians at the Nouna Health and Demographic Surveillance Site between 1998 and 2007 were considered for analyses. Information from VA interviews was extracted to create a set of standard indicators needed to run the Interpreting Verbal Autopsy model. Cause-specific mortality fractions were used to compare Physician Coded Verbal Autopsy and Interpreting Verbal Autopsy results. Results At the population level, 62.5% of causes of death using the Interpreting Verbal Autopsy model corresponded with those determined by two or three physicians. Although seven of the 10 main causes of death were present in both approaches, the comparison of percentages of single causes of death shows discrepancies, dominated by higher malaria rates found in the Physician Coded Verbal Autopsy approach. Conclusion Our results confirm that national mortality statistics, which are partly based on verbal autopsies, must be carefully interpreted. Difficulties in determining malaria as cause of death in holoendemic malaria regions might result in higher discrepancies than those in non-endemic areas. As neither Physician Coded Verbal Autopsy nor Interpreting Verbal Autopsy results represent a gold standard, uncertainty levels with either procedure are high.
Place, publisher, year, edition, pages
2012. Vol. 17, no 7, 904-913 p.
verbal autopsy, cause of death, Burkina Faso, Bayesian InterVA model, autopsie verbale, cause de deces, Burkina-Faso, modele bayesien InterVA, Autopsia verbal, causa de muerte, modelo Bayesiano InterVA
Public Health, Global Health, Social Medicine and Epidemiology
IdentifiersURN: urn:nbn:se:umu:diva-57358DOI: 10.1111/j.1365-3156.2012.02998.xISI: 000305513700014OAI: oai:DiVA.org:umu-57358DiVA: diva2:541434