English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In regions without complete-coverage civil registration and vital statisticssystems there is uncertainty about even the most basic demographic indicators.In such areas the majority of deaths occur outside hospitals and are notrecorded. Worldwide, fewer than one-third of deaths are assigned a cause, withthe least information available from the most impoverished nations. Inpopulations like this, verbal autopsy (VA) is a commonly used tool to assesscause of death and estimate cause-specific mortality rates and the distributionof deaths by cause. VA uses an interview with caregivers of the decedent toelicit data describing the signs and symptoms leading up to the death. Thispaper develops a new statistical tool known as InSilicoVA to classify cause ofdeath using information acquired through VA. InSilicoVA shares uncertaintybetween cause of death assignments for specific individuals and thedistribution of deaths by cause across the population. Using side-by-sidecomparisons with both observed and simulated data, we demonstrate thatInSilicoVA has distinct advantages compared to currently available methods.

Probabilistic Cause-of-death Assignment using Verbal Autopsies