ArticleThe American journal of tropical medicine and hygiene2023
Multi-Cause Calibration of Verbal Autopsy-Based Cause-Specific Mortality Estimates of Children and Neonates in Mozambique.
Article in The American journal of tropical medicine and hygiene, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Validation of malaria-attributed deaths using verbal autopsy studies: a systematic review.Malaria journal · 2024Pooled it
- Introducing Minimally Invasive Tissue Sampling to Ascertain Cause of Death in Children and Stillbirths in Central Mozambique.The American journal of tropical medicine and hygiene · 2026Article
- Country-specific estimates of misclassification rates of computer-coded verbal autopsy algorithms.BMJ global health · 2026Article
- Comparison of verbal autopsy using a large language model to biologically confirmed causes of death for malaria and other communicable diseases among children in six sub-Saharan African countries.Malaria journal · 2026Article
- The contribution of minimally invasive tissue sampling compared to antemortem-derived cause of death determination among inpatient child deaths: the minimally invasive tissue sampling in Malawi study.Journal of global health · 2025Article
- Burden of child mortality from malaria in high endemic areas: Results from the CHAMPS network using minimally invasive tissue sampling.The Journal of infection · 2024Article
- Comparison of causes of stillbirth and child deaths as determined by verbal autopsy and minimally invasive tissue sampling.PLOS global public health · 2024Article
- Adapting the log quadratic model to estimate age- and cause-specific mortality among neonates.PloS one · 2024Article
- Addressing the Gaps in Mortality Data: A Case for National Mortality Surveillance.The American journal of tropical medicine and hygiene · 2023Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Countrywide Mortality Surveillance for Action platform is collecting verbal autopsy (VA) records from a nationally representative sample in Mozambique. These records are used to estimate the national and subnational cause-specific mortality fractions (CSMFs) for children (1-59 months) and neonates (1-28 days). Cross-tabulation of VA-based cause-of-death (COD) determination against that from the minimally invasive tissue sampling (MITS) from the Child Health and Mortality Prevention project revealed important misclassification errors for all the VA algorithms, which if not accounted for will lead to bias in the estimates of CSMF from VA. A recently proposed Bayesian VA-calibration method is used that accounts for this misclassification bias and produces calibrated estimates of CSMF. Both the VA-COD and the MITS-COD can be multi-cause (i.e., suggest more than one probable COD for some of the records). To fully use this probabilistic COD data, we use the multi-cause VA calibration. Two different computer-coded VA algorithms are considered-InSilicoVA and EAVA-and the final CSMF estimates are obtained using an ensemble calibration that uses data from both the algorithms. The calibrated estimates consistently offer a better fit to the data and reveal important changes in the CSMF for both children and neonates in Mozambique after accounting for VA misclassification bias.
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