Rise in people discovered dead and decomposed raises concerns

An exploratory study has raised concerns about the increasing number of people in England and Wales whose bodies are discovered so late that they have decomposed.

The study, published in the Journal of the Royal Society of Medicine, has highlighted potential links between growing isolation and such deaths, even before the COVID-19 pandemic.

The study was authored by a team led by Dr Lucinda Hiam of the University of Oxford and including histopathology registrar Dr Theodore Estrin-Serlui of Imperial College NHS Healthcare Trust.

The researchers analysed data from the Office for National Statistics (ONS), identifying deaths where bodies were found in a state of decomposition. They used a novel proxy: deaths coded as R98 ("unattended death") and R99 ("other ill-defined and unknown causes of mortality") according to the International Classification of Diseases (ICD-10) and previous versions, referred to as “undefined deaths”.

The study revealed a steady increase in “undefined deaths”, i.e., deaths of people found decomposed, between 1979 and 2020 for both sexes. The proportion of total male deaths exceeded female deaths, with these deaths increasing significantly among males during the 1990 and 2000s, when overall mortality was rapidly improving. This acceleration in deaths where people are found decomposed, particularly for men, is a concerning trend, the authors said.

“Many people would be shocked that someone can lie dead at home for days, weeks or even longer, without anyone raising an alarm among the community they live in,” said Dr Estrin-Serlui. “The increase in people found dead and decomposed suggests wider societal breakdowns of both formal and informal social support networks even before the pandemic. They are concerning and warrant urgent further investigation.”

The authors of the study are calling on national and international authorities to consider measures that would make it possible to identify deaths where people are found decomposed more easily in routine data.

ENDS