Applying the InterVA-4 model to determine causes of death in rural Ethiopia

B. Weldearegawi, Y.A. Melaku, M. Spigt, G.J. Dinant

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

Background: In Ethiopia, most deaths take place at home and routine certification of cause of death by physicians is lacking. As a result, reliable cause of death (CoD) data are often not available. Recently, a computerized method for interpretation of verbal autopsy (VA) data, called InterVA, has been developed and used. It calculates the probability of a set of CoD given the presence of circumstances, signs, and symptoms reported during VA interviews. We applied the InterVA model to describe CoD in a rural population of Ethiopia. Objective: VA data for 436/599 (72.7%) deaths that occurred during 2010-2011 were included. InterVA-4 was used to interpret the VA data into probable cause of death. Cause-specific mortality fraction was used to describe frequency of occurrence of death from specific causes. Results: InterVA-4 was able to give likely cause(s) of death for 401/436 of the cases (92.0%). Overall, 35.0% of the total deaths were attributed to communicable diseases, and 30.7% to chronic non-communicable diseases. Tuberculosis (12.5%) and acute respiratory tract infections (10.4%) were the most frequent causes followed by neoplasms (9.6%) and diseases of circulatory system (7.2%). Conclusion: InterVA-4 can produce plausible estimates of the major public health problems that can guide public health interventions. We encourage further validation studies, in local settings, so that InterVA can be integrated into national health surveys.
Original languageEnglish
Article number25550
JournalGlobal Health Action
Volume7
DOIs
Publication statusPublished - 1 Jan 2014

Cite this

@article{4004449e3dc34d03814eace44d363d6c,
title = "Applying the InterVA-4 model to determine causes of death in rural Ethiopia",
abstract = "Background: In Ethiopia, most deaths take place at home and routine certification of cause of death by physicians is lacking. As a result, reliable cause of death (CoD) data are often not available. Recently, a computerized method for interpretation of verbal autopsy (VA) data, called InterVA, has been developed and used. It calculates the probability of a set of CoD given the presence of circumstances, signs, and symptoms reported during VA interviews. We applied the InterVA model to describe CoD in a rural population of Ethiopia. Objective: VA data for 436/599 (72.7{\%}) deaths that occurred during 2010-2011 were included. InterVA-4 was used to interpret the VA data into probable cause of death. Cause-specific mortality fraction was used to describe frequency of occurrence of death from specific causes. Results: InterVA-4 was able to give likely cause(s) of death for 401/436 of the cases (92.0{\%}). Overall, 35.0{\%} of the total deaths were attributed to communicable diseases, and 30.7{\%} to chronic non-communicable diseases. Tuberculosis (12.5{\%}) and acute respiratory tract infections (10.4{\%}) were the most frequent causes followed by neoplasms (9.6{\%}) and diseases of circulatory system (7.2{\%}). Conclusion: InterVA-4 can produce plausible estimates of the major public health problems that can guide public health interventions. We encourage further validation studies, in local settings, so that InterVA can be integrated into national health surveys.",
author = "B. Weldearegawi and Y.A. Melaku and M. Spigt and G.J. Dinant",
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Applying the InterVA-4 model to determine causes of death in rural Ethiopia. / Weldearegawi, B.; Melaku, Y.A.; Spigt, M.; Dinant, G.J.

In: Global Health Action, Vol. 7, 25550, 01.01.2014.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

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N2 - Background: In Ethiopia, most deaths take place at home and routine certification of cause of death by physicians is lacking. As a result, reliable cause of death (CoD) data are often not available. Recently, a computerized method for interpretation of verbal autopsy (VA) data, called InterVA, has been developed and used. It calculates the probability of a set of CoD given the presence of circumstances, signs, and symptoms reported during VA interviews. We applied the InterVA model to describe CoD in a rural population of Ethiopia. Objective: VA data for 436/599 (72.7%) deaths that occurred during 2010-2011 were included. InterVA-4 was used to interpret the VA data into probable cause of death. Cause-specific mortality fraction was used to describe frequency of occurrence of death from specific causes. Results: InterVA-4 was able to give likely cause(s) of death for 401/436 of the cases (92.0%). Overall, 35.0% of the total deaths were attributed to communicable diseases, and 30.7% to chronic non-communicable diseases. Tuberculosis (12.5%) and acute respiratory tract infections (10.4%) were the most frequent causes followed by neoplasms (9.6%) and diseases of circulatory system (7.2%). Conclusion: InterVA-4 can produce plausible estimates of the major public health problems that can guide public health interventions. We encourage further validation studies, in local settings, so that InterVA can be integrated into national health surveys.

AB - Background: In Ethiopia, most deaths take place at home and routine certification of cause of death by physicians is lacking. As a result, reliable cause of death (CoD) data are often not available. Recently, a computerized method for interpretation of verbal autopsy (VA) data, called InterVA, has been developed and used. It calculates the probability of a set of CoD given the presence of circumstances, signs, and symptoms reported during VA interviews. We applied the InterVA model to describe CoD in a rural population of Ethiopia. Objective: VA data for 436/599 (72.7%) deaths that occurred during 2010-2011 were included. InterVA-4 was used to interpret the VA data into probable cause of death. Cause-specific mortality fraction was used to describe frequency of occurrence of death from specific causes. Results: InterVA-4 was able to give likely cause(s) of death for 401/436 of the cases (92.0%). Overall, 35.0% of the total deaths were attributed to communicable diseases, and 30.7% to chronic non-communicable diseases. Tuberculosis (12.5%) and acute respiratory tract infections (10.4%) were the most frequent causes followed by neoplasms (9.6%) and diseases of circulatory system (7.2%). Conclusion: InterVA-4 can produce plausible estimates of the major public health problems that can guide public health interventions. We encourage further validation studies, in local settings, so that InterVA can be integrated into national health surveys.

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