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Childhood cause-specific mortality in rural Western Kenya

Application of the InterVA-4 model

Bibliographic Data

ID19529511
AuthorsAmek Nyaguara (0000-0002-7865-8756, Kenya Medical Research Institute, corresponding author), Nyaguara O Amek, Frank Odhiambo (0000-0003-3056-8425, Kenya Medical Research Institute), Frank O Odhiambo, Sammy Khagayi (0000-0002-2470-1851, Kenya Medical Research Institute), Hellen Moige (Kenya Medical Research Institute), Gordon Orwa (Kenya Medical Research Institute), Mary J Hamel (Centers for Disease Control and Prevention), Annemieke van Eijk (Kenya Medical Research Institute), John Vulule (0000-0001-7710-0390, Kenya Medical Research Institute), Laurence Slutsker (Centers for Disease Control and Prevention), Kayla F Laserson (Centers for Disease Control and Prevention)
Year2014
Volume7
Issue1
Pages25581-25581
Publication date2014-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueGlobal Health Action (JOURNAL)
Journal identifiersISSN: 1654-9716 • E-ISSN: 1654-9880
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.3402/gha.v7.25581
PMID25377340
OpenAlexW1974093960
LanguageEN
Citations received5
References cited25

BACKGROUND: Assessing the progress in achieving the United Nation's Millennium Development Goals in terms of population health requires consistent and reliable information on cause-specific mortality, which is often rare in resource-constrained countries. Health and demographic surveillance systems (HDSS) have largely used medical personnel to review and assign likely causes of death based on the information gathered from standardized verbal autopsy (VA) forms. However, this approach is expensive and time consuming, and it may lead to biased results based on the knowledge and experience of individual clinicians. We assessed the cause-specific mortality for children under 5 years old (under-5 deaths) in Siaya County, obtained from a computer-based probabilistic model (InterVA-4). DESIGN: Successfully completed VA interviews for under-5 deaths conducted between January 2003 and December 2010 in the Kenya Medical Research Institute/US Centers for Disease Control and Prevention HDSS were extracted from the VA database and processed using the InterVA-4 (version 4.02) model for interpretation. Cause-specific mortality fractions were then generated from the causes of death produced by the model. RESULTS: A total of 84.33% (6,621) childhood deaths had completed VA data during the study period. Children aged 1-4 years constituted 48.53% of all cases, and 42.50% were from infants. A single cause of death was assigned to 89.18% (5,940) of cases, 8.35% (556) of cases were assigned two causes, and 2.10% (140) were assigned 'indeterminate' as cause of death by the InterVA-4 model. Overall, malaria (28.20%) was the leading cause of death, followed by acute respiratory infection including pneumonia (25.10%), in under-5 children over the study period. But in the first 5 years of the study period, acute respiratory infection including pneumonia was the main cause of death, followed by malaria. Similar trends were also reported in infants (29 days-11 months) and children aged 1-4 years. CONCLUSIONS: Under-5 cause-specific mortality obtained using the InterVA-4 model is consistent with existing knowledge on the burden of childhood diseases in rural western Kenya

Cause of death · Disease · Environmental health · Geography · Socioeconomics · Sociology · Verbal autopsy · Data-Driven Disease Surveillance · Demography · Global Maternal and Child Health · Maternal and Neonatal Healthcare · Medicine

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Unique citing works5
Citations per year0.42
Citation span2014 - 2025 (12)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 5

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