ArticleJournal of global health2015
Direct estimates of national neonatal and child cause-specific mortality proportions in Niger by expert algorithm and physician-coded analysis of verbal autopsy interviews.
Article in Journal of global health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Secondary Effects from Mass Azithromycin Administration: A Systematic Review and Meta-analysis.The American journal of tropical medicine and hygiene · 2022Pooled it
- Causes of death after biannual azithromycin treatment: A community-level randomized clinical trial.PloS one · 2021Trial
- Cause-specific mortality of children younger than 5 years in communities receiving biannual mass azithromycin treatment in Niger: verbal autopsy results from a cluster-randomised controlled trial.The Lancet. Global health · 2020Trial
- Azithromycin to Reduce Childhood Mortality in Sub-Saharan Africa.The New England journal of medicine · 2018Trial
- A verbal and social autopsy study to improve estimates of mortality determinants in Pakistan: study design and methods.Journal of global health · 2026Article
- Exploring mortality patterns in Pakistani children and adolescents aged 5-19: evidence from a national verbal and social autopsy study.Journal of global health · 2026Article
- Determining causes of death through an abridged verbal autopsy tool: a pilot test conducted among vulnerable communities in Kolkata, India.BMJ global health · 2026Article
- Country-specific estimates of misclassification rates of computer-coded verbal autopsy algorithms.BMJ global health · 2026Article
- Prescribing practices in the treatment of wasting: secondary analysis from a randomised trial.BMJ nutrition, prevention & health · 2024Article
- Article
- Causes of deaths in neonates and children aged 1-59 months in Nigeria: verbal autopsy findings of 2019 Verbal and Social Autopsy study.BMC public health · 2022Article
- Regularized Bayesian transfer learning for population-level etiological distributions.Biostatistics (Oxford, England) · 2021Article
- Verbal/social autopsy analysis of causes and determinants of under-5 mortality in Tanzania from 2010 to 2016.Journal of global health · 2020Article
- Using health facility deaths to estimate population causes of neonatal and child mortality in four African countries.BMC medicine · 2020Article
- Validation of verbal autopsy methods for assessment of child mortality in sub-Saharan Africa and the policy implication: a rapid review.The Pan African medical journal · 2019Review
- Article
- Burden, timing and causes of maternal and neonatal deaths and stillbirths in sub-Saharan Africa and South Asia: protocol for a prospective cohort study.Journal of global health · 2016Article
- Validating hierarchical verbal autopsy expert algorithms in a large data set with known causes of death.Journal of global health · 2016Article
- Verbal/Social Autopsy in Niger 2012-2013: A new tool for a better understanding of the neonatal and child mortality situation.Journal of global health · 2016Article
- Social determinants of child mortality in Niger: Results from the 2012 National Verbal and Social Autopsy Study.Journal of global health · 2016Article
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study was one of a set of verbal autopsy investigations undertaken by the WHO/UNCEF-supported Child Health Epidemiology Reference Group (CHERG) to derive direct estimates of the causes of neonatal and child deaths in high priority countries of sub-Saharan Africa. The objective of the study was to determine the cause distributions of neonatal (0-27 days) and child (1-59 months) mortality in Niger.
methodsVerbal autopsy interviews were conducted of random samples of 453 neonatal deaths and 620 child deaths from 2007 to 2010 identified by the 2011 Niger National Mortality Survey. The cause of each death was assigned using two methods: computerized expert algorithms arranged in a hierarchy and physician completion of a death certificate for each child. The findings of the two methods were compared to each other, and plausibility checks were conducted to assess which is the preferred method. Comparison of some direct measures from this study with CHERG modeled cause of death estimates are discussed.
findingsThe cause distributions of neonatal deaths as determined by expert algorithms and the physician were similar, with the same top three causes by both methods and all but two other causes within one rank of each other. Although child causes of death differed more, the reasons often could be discerned by analyzing algorithmic criteria alongside the physician's application of required minimal diagnostic criteria. Including all algorithmic (primary and co-morbid) and physician (direct, underlying and contributing) diagnoses in the comparison minimized the differences, with kappa coefficients greater than 0.40 for five of 11 neonatal diagnoses and nine of 13 child diagnoses. By algorithmic diagnosis, early onset neonatal infection was significantly associated (χ(2) = 13.2, P < 0.001) with maternal infection, and the geographic distribution of child meningitis deaths closely corresponded with that for meningitis surveillance cases and deaths.
conclusionsVerbal autopsy conducted in the context of a national mortality survey can provide useful estimates of the cause distributions of neonatal and child deaths. While the current study found reasonable agreement between the expert algorithm and physician analyses, it also demonstrated greater plausibility for two algorithmic diagnoses and validation work is needed to ascertain the findings. Direct, large-scale measurement of causes of death complement, can strengthen, and in some settings may be preferred over modeled estimates.
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