Modeling the burden of long COVID in California with quality adjusted life-years (QALYS).

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

COVID-19*/epidemiology ; Quality-Adjusted Life Years* ; SARS-CoV-2*/isolation & purification; Humans ; California/epidemiology ; Adolescent ; Adult ; Middle Aged ; Aged ; Child ; Child, Preschool ; Young Adult ; Infant ; Male ; Female ; Severity of Illness Index ; Infant, Newborn ; Cost of Illness ; Post-Acute COVID-19 Syndrome ; Aged, 80 and over

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. The Author(s).)

CDC. Post-COVID Conditions. Centers for Disease Control and Prevention. Published September 1, 2022. Accessed December 12, 2022. https://www.cdc.gov/coronavirus/2019-ncov/long-term-effects/index.html.
Coronavirus disease (COVID-19): Post COVID-19 condition. Accessed December 12, 2022. https://www.who.int/news-room/questions-and-answers/item/coronavirus-disease-(covid-19)-post-covid-19-condition.
Tenforde, M. W. Symptom duration and risk factors for delayed return to usual health among outpatients with COVID-19 in a multistate health care systems network—United States, March–June 2020. MMWR Morb Mortal Wkly Rep. 2020;69. https://doi.org/10.15585/mmwr.mm6930e1.
Seeßle, J. et al. Persistent symptoms in adult patients 1 year after coronavirus disease 2019 (COVID-19): A prospective cohort study. Clin. Infect. Dis.74(7), 1191–1198. https://doi.org/10.1093/cid/ciab611 (2022). (PMID: 10.1093/cid/ciab61134223884)
Yong, S. J. Long COVID or post-COVID-19 syndrome: Putative pathophysiology, risk factors, and treatments. Infect. Dis.53(10), 737–754. https://doi.org/10.1080/23744235.2021.1924397 (2021). (PMID: 10.1080/23744235.2021.1924397)
Chen, C., Haupert, S. R., Zimmermann, L., Shi, X., Fritsche, L. G. & Mukherjee, B. Global prevalence of post COVID-19 condition or long COVID: A meta-analysis and systematic review. J. Infect. Dis. Published online April 16, 2022:jiac136. https://doi.org/10.1093/infdis/jiac136.
Davis, H. E., Assaf, G. S., McCorkell, L., et al. Characterizing long COVID in an international cohort: 7 months of symptoms and their impact. eClinicalMedicine. 38. https://doi.org/10.1016/j.eclinm.2021.101019 (2021).
Prieto, L. & Sacristán, J. A. Problems and solutions in calculating quality-adjusted life years (QALYs). Health Qual Life Outcomes1, 80. https://doi.org/10.1186/1477-7525-1-80 (2003). (PMID: 10.1186/1477-7525-1-8031737014687421)
Global Burden of Disease Long COVID Collaborators. Estimated global proportions of individuals with persistent fatigue, cognitive, and respiratory symptom clusters following symptomatic COVID-19 in 2020 and 2021. JAMA328(16), 1604–1615. https://doi.org/10.1001/jama.2022.18931 (2022). (PMID: 10.1001/jama.2022.189319552043)
Adjei, S. et al. Mortality risk among patients hospitalized primarily for COVID-19 during the omicron and delta variant pandemic periods—United States, April 2020-June 2022. MMWR Morb. Mortal. Wkly. Rep.71(37), 1182–1189. https://doi.org/10.15585/mmwr.mm7137a4 (2022). (PMID: 10.15585/mmwr.mm7137a4948480836107788)
Martin, C., Luteijn, M., Letton, W., Robertson, J. & McDonald, S. A model framework for projecting the prevalence and impact of Long-COVID in the UK. PLOS ONE16(12), e0260843. https://doi.org/10.1371/journal.pone.0260843 (2021). (PMID: 10.1371/journal.pone.0260843863906534855874)
Padmanabhan, R. et al. A review of mathematical model-based scenario analysis and interventions for COVID-19. Comput. Methods Programs Biomed.209, 106301. https://doi.org/10.1016/j.cmpb.2021.106301 (2021). (PMID: 10.1016/j.cmpb.2021.106301831487134392001)
Azar, K. M. J. et al. Disparities in outcomes among COVID-19 patients in a large health care system in California. Health Aff. (Millwood).39(7), 1253–1262. https://doi.org/10.1377/hlthaff.2020.00598 (2020). (PMID: 10.1377/hlthaff.2020.0059832437224)
Reitsma, M. B. et al. Racial/ethnic disparities in COVID-19 exposure risk, testing, and cases at the subcounty level in California. Health Aff. (Millwood).40(6), 870–878. https://doi.org/10.1377/hlthaff.2021.00098 (2021). (PMID: 10.1377/hlthaff.2021.00098845802833979192)
Huang, Y. et al. COVID symptoms, symptom clusters, and predictors for becoming a long-hauler looking for clarity in the haze of the pandemic. Clin. Nurs. Res.31(8), 1390–1398. https://doi.org/10.1177/10547738221125632 (2022). (PMID: 10.1177/10547738221125632951095436154716)
Yomogida, K. et al. Post-acute sequelae of SARS-CoV-2 infection among adults aged ≥18 Years—Long Beach, California, April 1–December 10, 2020. Morb. Mortal. Wkly. Rep.70(37), 1274–1277. https://doi.org/10.15585/mmwr.mm7037a2 (2021). (PMID: 10.15585/mmwr.mm7037a2)
O’Laughlin, K. N. et al. Study protocol for the innovative support for patients with SARS-COV-2 infections registry (INSPIRE): A longitudinal study of the medium and long-term sequelae of SARS-CoV-2 infection. PLOS ONE17(3), e0264260. https://doi.org/10.1371/journal.pone.0264260 (2022). (PMID: 10.1371/journal.pone.0264260889362235239680)
California Department of Public Health. CalScope. Accessed March 1, 2023. https://www.cdph.ca.gov/Programs/OPA/Pages/Communications-Toolkits/Calscope.aspx.
Menni, C. et al. Symptom prevalence, duration, and risk of hospital admission in individuals infected with SARS-CoV-2 during periods of omicron and delta variant dominance: A prospective observational study from the ZOE COVID Study. Lancet399(10335), 1618–1624. https://doi.org/10.1016/S0140-6736(22)00327-0 (2022). (PMID: 10.1016/S0140-6736(22)00327-0898939635397851)
Augustin, M. et al. Post-COVID syndrome in non-hospitalised patients with COVID-19: A longitudinal prospective cohort study. Lancet Reg. Health Eur.6, 100122. https://doi.org/10.1016/j.lanepe.2021.100122 (2021). (PMID: 10.1016/j.lanepe.2021.100122812961334027514)
Malkova, A., Kudryavtsev, I., Starshinova, A, et al. Post COVID-19 syndrome in patients with asymptomatic/mild form. Pathogens. 10(11). https://doi.org/10.3390/pathogens10111408 (2021).
California Department of Finance. California 2020 Population by Age. Accessed November 16, 2023. https://dof.ca.gov/forecasting/demographics/.
California Department of Public Health. COVID-19 cases dashboard v2.0. Tableau Software. Accessed March 28, 2023. https://public.tableau.com/views/COVID-19CasesDashboardv2_0/CaseStatistics ?.
Perlis, R. H. et al. Prevalence and correlates of long COVID symptoms among US adults. JAMA Netw. Open5(10), e2238804. https://doi.org/10.1001/jamanetworkopen.2022.38804 (2022). (PMID: 10.1001/jamanetworkopen.2022.38804961458136301542)
Haendel, M. A. et al. The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment. J. Am. Med. Inform. Assoc.28(3), 427–443. https://doi.org/10.1093/jamia/ocaa196 (2021). (PMID: 10.1093/jamia/ocaa19632805036)
Wu, J., Dhingra, R., Gambhir, M. & Remais, J. V. Sensitivity analysis of infectious disease models: methods, advances and their application. J. R. Soc. Interface10(86), 20121018. https://doi.org/10.1098/rsif.2012.1018 (2013). (PMID: 10.1098/rsif.2012.1018373067723864497)
Blower, S. M. & Dowlatabadi, H. Sensitivity and uncertainty analysis of complex models of disease transmission: An HIV model, as an example. Int. Stat. Rev. Rev. Int. Stat.62(2), 229–243. https://doi.org/10.2307/1403510 (1994). (PMID: 10.2307/1403510)
Marino, S., Hogue, I. B., Ray, C. J. & Kirschner, D. E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol.254(1), 178–196. https://doi.org/10.1016/j.jtbi.2008.04.011 (2008). (PMID: 10.1016/j.jtbi.2008.04.011257019118572196)
Mckay, M. D., Beckman, R. J. & Conover, W. J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics42(1), 55–61. https://doi.org/10.1080/00401706.2000.10485979 (2000). (PMID: 10.1080/00401706.2000.10485979)
Carnell, R. lhs: Latin Hypercube Samples. Published online March 22, 2022. Accessed December 12, 2022. https://CRAN.R-project.org/package=lhs.
Bartsch, S. M. et al. The potential health care costs and resource use associated with COVID-19 in the United States. Health Aff. (Millwood)39(6), 927–935. https://doi.org/10.1377/hlthaff.2020.00426 (2020). (PMID: 10.1377/hlthaff.2020.0042632324428)
Di Fusco, M. et al. Health outcomes and economic burden of hospitalized COVID-19 patients in the United States. J. Med. Econ.24(1), 308–317. https://doi.org/10.1080/13696998.2021.1886109 (2021). (PMID: 10.1080/13696998.2021.188610933555956)
Mizrahi, B. et al. Long covid outcomes at one year after mild SARS-CoV-2 infection: Nationwide cohort study. BMJ380, e072529. https://doi.org/10.1136/bmj-2022-072529 (2023). (PMID: 10.1136/bmj-2022-07252936631153)
Bach, K. New data shows long Covid is keeping as many as 4 million people out of work. Brookings. Published August 24, 2022. Accessed January 23, 2023. https://www.brookings.edu/research/new-data-shows-long-covid-is-keeping-as-many-as-4-million-people-out-of-work/.
Tsuzuki, S. & Beutels, P. The estimated disease burden of COVID-19 in Japan from 2020 to 2021. Published online December 15, 2022:2022.12.14.22283492. https://doi.org/10.1101/2022.12.14.22283492.
Cuschieri, S., Calleja, N., Devleesschauwer, B. & Wyper, G. M. A. Estimating the direct Covid-19 disability-adjusted life years impact on the Malta population for the first full year. BMC Public Health21(1), 1827. https://doi.org/10.1186/s12889-021-11893-4 (2021). (PMID: 10.1186/s12889-021-11893-4850191334627228)
Wyper, G. M. A. et al. Measuring disability-adjusted life years (DALYs) due to COVID-19 in Scotland, 2020. Arch. Public Health80(1), 105. https://doi.org/10.1186/s13690-022-00862-x (2022). (PMID: 10.1186/s13690-022-00862-x897268735365228)
Fernández-de-las-Peñas, C. et al. Post–COVID-19 symptoms 2 years after SARS-CoV-2 infection among hospitalized vs nonhospitalized patients. JAMA Netw. Open5(11), e2242106. https://doi.org/10.1001/jamanetworkopen.2022.42106 (2022). (PMID: 10.1001/jamanetworkopen.2022.42106966733036378309)
Ayoubkhani, D. et al. Trajectory of long covid symptoms after covid-19 vaccination: Community based cohort study. BMJ377, e069676. https://doi.org/10.1136/bmj-2021-069676 (2022). (PMID: 10.1136/bmj-2021-06967635584816)
Carlile, O. et al. Impact of long COVID on health-related quality-of-life: An OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT). Lancet Region. Health-Europe1, 40 (2024).
Rafferty, E., Unsal, A., Kirwin, E., of Alberta U, of Manchester U, Kingdom U. Influenza and Other Respiratory Infections: Healthcare costs and effects of post-COVID-19 condition in Canada. Canada Communicable Disease Report.49(10), 425 (2023).
Yoo, S. M. et al. Factors associated with post-acute sequelae of SARS-CoV-2 (PASC) after diagnosis of symptomatic COVID-19 in the inpatient and outpatient setting in a diverse cohort. J. Gen. Intern. Med.37(8), 1988–1995 (2022). (PMID: 10.1007/s11606-022-07523-3898925635391623)
Pfaff, E. R. et al. Coding long COVID: Characterizing a new disease through an ICD-10 lens. BMC Med.21(1), 58. https://doi.org/10.1186/s12916-023-02737-6 (2023). (PMID: 10.1186/s12916-023-02737-6993156636793086)
CDC. Long COVID—Household Pulse Survey – COVID-19. Published February 21, 2023. Accessed March 1, 2023. https://www.cdc.gov/nchs/covid19/pulse/long-covid.htm.
Tanne, J. H. Covid-19: US studies show racial and ethnic disparities in long covid. BMJ.380, p535. https://doi.org/10.1136/bmj.p535 (2023). (PMID: 10.1136/bmj.p535)
Khullar, D., Zhang, Y., Zang, C., et al. Racial/ethnic disparities in post-acute sequelae of SARS-CoV-2 Infection in New York: an ©-Based Cohort Study from the RECOVER Program. J Gen Intern Med. Published online February 16, 2023. https://doi.org/10.1007/s11606-022-07997-1.
Colman, E., Puspitarani, G. A., Enright, J. & Kao, R. R. Ascertainment rate of SARS-CoV-2 infections from healthcare and community testing in the UK. J. Theor. Biol.558, 111333. https://doi.org/10.1016/j.jtbi.2022.111333 (2023). (PMID: 10.1016/j.jtbi.2022.11133336347306)
Mehrotra, M. L., Lim, E., Lamba, K., Kamali, A., Lai, K. W., Meza, E., Szeto, I., Robinson, P., Tsai, C. T., Gebhart, D. & Fonseca, N. CalScope: monitoring severe acute respiratory syndrome coronavirus 2 seroprevalence from vaccination and prior infection in adults and children in California May 2021–July 2021. InOpen Forum Infectious Diseases 2022 Jul 1 (Vol. 9, No. 7, p. ofac246). Oxford University Press.
California Department of Public Health. Assessing the impact of COVID-19 in California. Published March 9, 2022. Accessed July 9, 2024. https://www.cdph.ca.gov/Programs/CID/DCDC/Pages/COVID-19/Assessing-Impact-COVID-19-California.aspx.

U01 CK000539 United States CK NCEZID CDC HHS

Date Created: 20240930 Date Completed: 20240930 Latest Revision: 20241003

20241004

PMC11443048

10.1038/s41598-024-73160-x

39349557