tetano
Editor, Senior Moderator
Sci Rep
. 2024 Sep 30;14(1):22663.
doi: 10.1038/s41598-024-73160-x. Modeling the burden of long COVID in California with quality adjusted life-years (QALYS)
Sophie Zhu[SUP] 1 2 [/SUP], Kalyani McCullough[SUP] 3 [/SUP], Jake M Pry[SUP] 3 4 [/SUP], Seema Jain[SUP] 3 [/SUP], Lauren A White[SUP] 3 [/SUP], Tomás M León[SUP] 3 [/SUP]
Affiliations
Individuals infected with SARS-CoV-2 may develop post-acute sequelae of COVID-19 ("long COVID") even after asymptomatic or mild acute illness. Including time varying COVID symptom severity can provide more informative burden estimates for public health response. Using a compartmental model driven by confirmed cases, this study estimated long COVID burden by age group (0-4, 5-17, 18-49, 50-64, 65+) in California as measured by the cumulative and severity-specific proportion of quality-adjusted life years (QALYs) lost. Long COVID symptoms were grouped into severe, moderate, and mild categories based on estimates from the Global Burden of Disease study, and symptoms were assumed to decrease in severity in the model before full recovery. All 10,945,079 confirmed COVID-19 cases reported to the California Department of Public Health between March 1, 2020, and December 31, 2022, were included in the analysis. Most estimated long COVID-specific QALYs [59,514 (range: 10,372-180,257)] lost in California were concentrated in adults 18-49 (31,592; 53.1%). Relative to other age groups, older adults (65+) lost proportionally more QALYs from severe long COVID (1,366/6,984; 20%). Due to changing case ascertainment over time, this analysis might underestimate the actual total burden. In global sensitivity analysis, estimates of QALYs lost were most sensitive to the proportion of individuals that developed long COVID and proportion of cases with each initial level of long COVID symptom severity (mild/moderate/severe). Models like this analysis can help translate observable metrics such as cases and hospitalizations into quantitative estimates of long COVID burden that are currently difficult to directly measure. Unlike the observed relationship between age and incident severe outcomes for COVID-19, this study points to the potential cumulative impact of mild long COVID symptoms in younger individuals.
. 2024 Sep 30;14(1):22663.
doi: 10.1038/s41598-024-73160-x. Modeling the burden of long COVID in California with quality adjusted life-years (QALYS)
Sophie Zhu[SUP] 1 2 [/SUP], Kalyani McCullough[SUP] 3 [/SUP], Jake M Pry[SUP] 3 4 [/SUP], Seema Jain[SUP] 3 [/SUP], Lauren A White[SUP] 3 [/SUP], Tomás M León[SUP] 3 [/SUP]
Affiliations
- PMID: 39349557
- DOI: 10.1038/s41598-024-73160-x
Individuals infected with SARS-CoV-2 may develop post-acute sequelae of COVID-19 ("long COVID") even after asymptomatic or mild acute illness. Including time varying COVID symptom severity can provide more informative burden estimates for public health response. Using a compartmental model driven by confirmed cases, this study estimated long COVID burden by age group (0-4, 5-17, 18-49, 50-64, 65+) in California as measured by the cumulative and severity-specific proportion of quality-adjusted life years (QALYs) lost. Long COVID symptoms were grouped into severe, moderate, and mild categories based on estimates from the Global Burden of Disease study, and symptoms were assumed to decrease in severity in the model before full recovery. All 10,945,079 confirmed COVID-19 cases reported to the California Department of Public Health between March 1, 2020, and December 31, 2022, were included in the analysis. Most estimated long COVID-specific QALYs [59,514 (range: 10,372-180,257)] lost in California were concentrated in adults 18-49 (31,592; 53.1%). Relative to other age groups, older adults (65+) lost proportionally more QALYs from severe long COVID (1,366/6,984; 20%). Due to changing case ascertainment over time, this analysis might underestimate the actual total burden. In global sensitivity analysis, estimates of QALYs lost were most sensitive to the proportion of individuals that developed long COVID and proportion of cases with each initial level of long COVID symptom severity (mild/moderate/severe). Models like this analysis can help translate observable metrics such as cases and hospitalizations into quantitative estimates of long COVID burden that are currently difficult to directly measure. Unlike the observed relationship between age and incident severe outcomes for COVID-19, this study points to the potential cumulative impact of mild long COVID symptoms in younger individuals.