In regions without complete-coverage civil registration and vital statistics
systems there is uncertainty about even the most basic demographic indicators.
In such areas the majority of deaths occur outside hospitals and are not
recorded. Worldwide, fewer than one-third of deaths are assigned a cause, with
the least information available from the most impoverished nations. In
populations like this, verbal autopsy (VA) is a commonly used tool to assess
cause of death and estimate cause-specific mortality rates and the distribution
of deaths by cause. VA uses an interview with caregivers of the decedent to
elicit data describing the signs and symptoms leading up to the death. This
paper develops a new statistical tool known as InSilicoVA to classify cause of
death using information acquired through VA. InSilicoVA shares uncertainty
between cause of death assignments for specific individuals and the
distribution of deaths by cause across the population. Using side-by-side
comparisons with both observed and simulated data, we demonstrate that
InSilicoVA has distinct advantages compared to currently available methods.

通过使用口头尸检工具，本文开发了一种名为 InSilicoVA 的新的统计工具来确定死因，并展示了它相对于目前可用方法的明显优势，能够在未完成民事登记和关键统计系统的地区帮助评估死亡率和死因分布。