Understanding the fatal burden of COVID-19 in residential aged care homes in Australia: Using linked data to generate evidence

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Jennifer Welsh
Grace Joshy
Rachel Freeman-Robinson
Nicholas Biddle
Emily Banks
Clement Schlegel
Kayla Jordan
Phillip Gould
Paul Kelly
Rosemary Korda

Abstract

Aim
To quantify the impact of the pandemic on fatal burden of disease among those living in residential aged care homes (RACH) in Australia.


Methods
Using Residential Aged Care data linked to Death Registrations (Jan 2016 to 11 Aug 2022), we estimated years of life lost per person-year (YLL/py) among people living in RACH. Additional linkage of notifications data from the state of Victoria enabled comparisons of average survival times between notified COVID-19 cases and matched non-cases living in RACH using COVID-19.


Results
COVID-19 deaths were low in 2020 and 2021 (610 and 260 deaths, respectively) but increased in 2022 (3230 deaths). Years of life lost due to COVID-19 was low in 2020 and 2021 (1.2% and 0.5% of the total YLL/py, respectively) but increased substantially in 2022 (8.3% of the total YLL/py). However, there was little evidence that YLLs/py overall increased in the pandemic (range: 0.87 to 0.93 in 2016-2019 and 0.85 to 0.88 in 2020-2022). Results describing differences in survival between notified COVID-19 cases and non-cases are forthcoming.


Conclusion
We observed no substantial increase in overall fatal burden of disease among the RACH population during the pandemic period. While COVID-19 case numbers increased in 2022 relative to 2020-2021, this was offset with better survival among cases over time, reflecting, at least in part, decreasing disease severity, high uptake of COVID-19 vaccines and antiviral medications.

Article Details

How to Cite
Welsh, J., Joshy, G., Freeman-Robinson, R., Biddle, N., Banks, E., Schlegel, C., Jordan, K., Gould, P., Kelly, P. and Korda, R. (2024) “Understanding the fatal burden of COVID-19 in residential aged care homes in Australia: Using linked data to generate evidence”, International Journal of Population Data Science, 9(5). doi: 10.23889/ijpds.v9i5.2691.

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