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

Autor: Fiksel J; Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania., Gilbert B; Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland., Wilson E; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Kalter H; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Kante A; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Akum A; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Blau D; Center for Global Health, Centers for Disease Control and Prevention, Atlanta, Georgia., Bassat Q; ISGlobal, Hospital Clínic - Universitat de Barcelona, Barcelona, Spain.; Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique.; ICREA, Barcelona, Spain.; Pediatrics Department, Hospital Sant Joan de Déu, Universitat de Barcelona, Barcelona, Spain.; Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain., Macicame I; Instituto Nacional de Saúde (INS), Maputo, Mozambique., Samo Gudo E; Instituto Nacional de Saúde (INS), Maputo, Mozambique., Black R; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Zeger S; Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland., Amouzou A; Department of International Health, Johns Hopkins University, Baltimore, Maryland., Datta A; Department of Biostatistics, Johns Hopkins University, Baltimore, Maryland.
Jazyk: angličtina
Zdroj: The American journal of tropical medicine and hygiene [Am J Trop Med Hyg] 2023 Apr 10; Vol. 108 (5_Suppl), pp. 66-77. Date of Electronic Publication: 2023 Apr 10 (Print Publication: 2023).
DOI: 10.4269/ajtmh.22-0318
Abstrakt: 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 use the VA calibration approach with the calibratedVA software to correct for verbal autopsy misclassification bias in cause-specific mortality estimates. We use calibratedVA to obtain CSMFs for child (1-59 months) and neonatal deaths using VA data from the Countrywide Mortality Surveillance for Action project in Mozambique.
Databáze: MEDLINE