Articoli scientifici - 10/07/2026
Redistribution of garbage codes to underlying causes of death: a systematic analysis on Italian data based on the global burden of disease study 2023
Ridistribuzione dei garbage codes a cause primarie di morte: un’analisi sistematica su dati italiani basata sul Global Burden of Disease Study 2023
[…] d redistribution algorithms can help reassign deaths originally coded as GCs to the most plausible underlying causes, thereby improving the reliability of mortality estimates.8 In line with this, the global Burden of Disease (GBD) Study applies evidence-based redistribution methods to produce cause-specific mortality estimates by systematically reallocating GCs.9 Specifically, redistribution draws […] […] tribution algorithms can help reassign deaths originally coded as GCs to the most plausible underlying causes, thereby improving the reliability of mortality estimates.8 In line with this, the Global burden of Disease (GBD) Study applies evidence-based redistribution methods to produce cause-specific mortality estimates by systematically reallocating GCs.9 Specifically, redistribution draws on mul […] […] Introduction
Accurate cause-of-death reporting is essential for monitoring population health, informing public health policies on disease prevention and control, and guiding the allocation of healthcare resources.1 However, it remains a significant challenge, as mortality data are often affected by misreporting in death certification, and a substantial proportion of deaths remains poorly defined.2 […] […] help reassign deaths originally coded as GCs to the most plausible underlying causes, thereby improving the reliability of mortality estimates.8 In line with this, the Global Burden of Disease (GBD) study applies evidence-based redistribution methods to produce cause-specific mortality estimates by systematically reallocating GCs.9 Specifically, redistribution draws on multiple approaches, includ […]


