Abstract:
Background: Verbal autopsy methods are critically important for evaluating the leading causes of death in
populations without adequate vital registration systems. With a myriad of analytical and data collection approaches,
it is essential to create a high quality validation dataset from different populations to evaluate comparative method
performance and make recommendations for future verbal autopsy implementation. This study was undertaken to
compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the
accuracy of different methods of verbal autopsy cause of death assignment.
Methods: Data collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines;
Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population
Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory,
pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an
enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was
constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to
identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold
standard cases. Blinded verbal autopsies were collected on all gold standard deaths.
Results: Over 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075
children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria
as well as problems with misclassification for certain causes meant that the target list of causes for analysis was
reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence
for the validation of methods and assessment of comparative performance, 500 test-train datasets were created
from the universe of cases, covering a range of cause-specific compositions.
Conclusions: This unique, robust validation dataset will allow scholars to evaluate the performance of different
verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform theimplementation of verbal autopsies to more reliably ascertain cause of death in national health information
systems.
