Correcting for Verbal Autopsy Misclassification Bias in Cause-Specific Mortality Estimates.

ABSTRACT: Verbal autopsies (VAs) are extensively used to determine cause of death (COD) in many low- and middle-income countries. However, COD determination from VA can be inaccurate. Computer coded verbal autopsy (CCVA) algorithms used for this task are imperfect and misclassify COD for a large proportion of deaths. If not accounted for, this misclassification leads to biased estimates of cause-specific mortality fractions (CSMFs), a critical piece in health-policy making. Recent work has demonstrated that the knowledge of the CCVA misclassification rates can be used to calibrate raw VA-based CSMF estimates to account for the misclassification bias. In this manuscript, we review the current practices and issues with raw COD predictions from CCVA algorithms and provide a complete primer on how to us

SUBMITTER: Fiksel J 

PROVIDER: S-EPMC10160858 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature