Affiliation:
1. Population Interventions Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne , Carlton, VIC, Australia
Abstract
Abstract
Background
Long COVID symptoms occur for a proportion of acute COVID-19 survivors, with reduced risk among the vaccinated and for Omicron compared with Delta variant infections. The health loss attributed to pre-Omicron long COVID has previously been estimated using only a few major symptoms.
Methods
The years lived with disability (YLDs) due to long COVID in Australia during the 2021–22 Omicron BA.1/BA.2 wave were calculated using inputs from previously published case-control, cross-sectional or cohort studies examining the prevalence and duration of individual long COVID symptoms. This estimated health loss was compared with acute SARS-CoV-2 infection YLDs and years of life lost (YLLs) from SARS-CoV-2. The sum of these three components equals COVID-19 disability-adjusted life years (DALYs); this was compared with DALYs from other diseases.
Results
A total of 5200 [95% uncertainty interval (UI) 2200–8300] YLDs were attributable to long COVID and 1800 (95% UI 1100-2600) to acute SARS-CoV-2 infection, suggesting long COVID caused 74% of the overall YLDs from SARS-CoV-2 infections in the BA.1/BA.2 wave. Total DALYs attributable to SARS-CoV-2 were 50 900 (95% UI 21 000-80 900), 2.4% of expected DALYs for all diseases in the same period.
Conclusion
This study provides a comprehensive approach to estimating the morbidity due to long COVID. Improved data on long COVID symptoms will improve the accuracy of these estimates. As data accumulate on SARS-CoV-2 infection sequelae (e.g. increased cardiovascular disease rates), total health loss is likely to be higher than estimated in this study. Nevertheless, this study demonstrates that long COVID requires consideration in pandemic policy planning, given it is responsible for the majority of direct SARS-CoV-2 morbidity, including during an Omicron wave in a highly vaccinated population.
Publisher
Oxford University Press (OUP)
Subject
General Medicine,Epidemiology
Cited by
4 articles.
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