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Applying the InterVA-4 model to determine causes of death in rural Ethiopia
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 b...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Co-Action Publishing
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220136/ https://www.ncbi.nlm.nih.gov/pubmed/25377338 http://dx.doi.org/10.3402/gha.v7.25550 |
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author | Weldearegawi, Berhe Melaku, Yohannes Adama Spigt, Mark Dinant, Geert Jan |
author_facet | Weldearegawi, Berhe Melaku, Yohannes Adama Spigt, Mark Dinant, Geert Jan |
author_sort | Weldearegawi, Berhe |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4220136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Co-Action Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-42201362014-12-02 Applying the InterVA-4 model to determine causes of death in rural Ethiopia Weldearegawi, Berhe Melaku, Yohannes Adama Spigt, Mark Dinant, Geert Jan Glob Health Action Indepth Network Cause-Specific Mortality 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. Co-Action Publishing 2014-10-29 /pmc/articles/PMC4220136/ /pubmed/25377338 http://dx.doi.org/10.3402/gha.v7.25550 Text en © 2014 Berhe Weldearegawi et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Indepth Network Cause-Specific Mortality Weldearegawi, Berhe Melaku, Yohannes Adama Spigt, Mark Dinant, Geert Jan Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title | Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title_full | Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title_fullStr | Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title_full_unstemmed | Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title_short | Applying the InterVA-4 model to determine causes of death in rural Ethiopia |
title_sort | applying the interva-4 model to determine causes of death in rural ethiopia |
topic | Indepth Network Cause-Specific Mortality |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4220136/ https://www.ncbi.nlm.nih.gov/pubmed/25377338 http://dx.doi.org/10.3402/gha.v7.25550 |
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