. 2025 Jul 18;80(6):1247-1261.

doi: 10.1093/cid/ciaf046.

Long COVID Incidence Proportion in Adults and Children Between 2020 and 2024: An Electronic Health Record-Based Study From the RECOVER Initiative

Hannah Mandel¹, Yun J Yoo², Andrea J Allen³, Sajjad Abedian⁴, Zoe Verzani⁵, Elizabeth W Karlson⁶, Lawrence C Kleinman⁷, Praveen C Mudumbi¹, Carlos R Oliveira^{8

9}, Jennifer A Muszynski¹⁰, Rachel S Gross¹¹, Thomas W Carton¹², C Kim¹³, Emily Taylor¹³, Heekyong Park¹⁴, Jasmin Divers¹⁵, J Daniel Kelly^{16

17}, Jonathan Arnold¹⁸, Carol Reynolds Geary¹⁹, Chengxi Zang⁵, Kelan G Tantisira^{20

21}, Kyung E Rhee^{21

22}, Michael Koropsak⁵, Sindhu Mohandas^{23

24}, Andrew Vasey¹⁹, Abu Saleh Mohammad Mosa²⁵, Melissa Haendel²⁶, Christopher G Chute²⁷, Shawn N Murphy²⁸, Lisa O'Brien¹³, Jacqueline Szmuszkovicz^{23

24}, Nicholas Guthe¹³, Jorge L Santana²⁹, Aliva De³⁰, Amanda L Bogie³¹, Katia C Halabi^{32

33}, Lathika Mohanraj³⁴, Patricia A Kinser³⁴, Samuel E Packard³⁵, Katherine R Tuttle^{36

37}, Kathryn Hirabayashi³, Rainu Kaushal⁵, Emily Pfaff³⁸, Mark G Weiner⁵, Lorna E Thorpe¹, Richard A Moffitt^{2

39}

Affiliations

¹ Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA.
² Department of Hematology and Medical Oncology, Emory University, Atlanta, Georgia, USA.
³ Applied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁴ Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, USA.
⁵ Department of Population Health Sciences, Weill Cornell Medical College, New York, New York, USA.
⁶ Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA.
⁷ Department of Pediatrics and Child Health Institute, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
⁸ Department of Pediatrics, Division of Infectious Diseases & Global Health, Yale University School of Medicine, New Haven, Connecticut, USA.
⁹ Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.
¹⁰ Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA.
¹¹ Department of Pediatrics, New York University Grossman School of Medicine, New York, New York, USA.
¹² Louisiana Public Health Institute, New Orleans, Louisiana, USA.
¹³ RECOVER Patient, Caregiver, or Community Advocate Representative, New York, New York, USA.
¹⁴ Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, USA.
¹⁵ Department of Biostatistics, NYU Long Island School of Medicine, Mineola, New York, USA.
¹⁶ Department of Medicine, University of California, San Francisco, California, USA.
¹⁷ San Francisco VA Medical Center, San Francisco, California, USA.
¹⁸ Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
¹⁹ Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.
²⁰ Division of Pediatric Respiratory Medicine, University of California San Diego, San Diego, California, USA.
²¹ Department of Pediatrics, Rady Children's Hospital, San Diego, California, USA.
²² Department of Pediatrics, University of California San Diego School of Medicine, San Diego, California, USA.
²³ Division of Infectious Diseases, Children's Hospital Los Angeles, Los Angeles, California, USA.
²⁴ Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
²⁵ Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, University of Missouri School of Medicine, Columbia, Missouri, USA.
²⁶ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
²⁷ Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
²⁸ Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
²⁹ School of Medicine, University of Puerto Rico, San Juan, Puerto Rico.
³⁰ Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA.
³¹ Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
³² Department of Infectious Disease, Nationwide Children's Hospital, Columbus, Ohio, USA.
³³ Infectious Diseases Division, Department of Pediatrics, Atlantic Health System, Goryeb Children's Hospital, Morristown, New Jersey, USA.
³⁴ Department of Adult Health and Nursing Systems, Virginia Commonwealth University School of Nursing, Richmond, Virginia, USA.
³⁵ Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.
³⁶ Providence Medical Research Center, Providence Inland Northwest Health, Spokane, Washington, USA.
³⁷ Division of Nephrology and Kidney Research Institute Seattle, University of Washington School of Medicine, Seattle, Washington, USA.
³⁸ Department of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina USA.
³⁹ Department of Biomedical Informatics, Emory University, Atlanta, Georgia, USA.

PMID: 39907495
PMCID: PMC12272849
DOI: 10.1093/cid/ciaf046

Long COVID Incidence Proportion in Adults and Children Between 2020 and 2024: An Electronic Health Record-Based Study From the RECOVER Initiative

Hannah Mandel et al. Clin Infect Dis. 2025.

. 2025 Jul 18;80(6):1247-1261.

doi: 10.1093/cid/ciaf046.

Authors

Affiliations

¹ Department of Population Health, New York University Grossman School of Medicine, New York, New York, USA.
² Department of Hematology and Medical Oncology, Emory University, Atlanta, Georgia, USA.
³ Applied Clinical Research Center, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
⁴ Information Technologies and Services Department, Weill Cornell Medicine, New York, New York, USA.
⁵ Department of Population Health Sciences, Weill Cornell Medical College, New York, New York, USA.
⁶ Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA.
⁷ Department of Pediatrics and Child Health Institute, Rutgers Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA.
⁸ Department of Pediatrics, Division of Infectious Diseases & Global Health, Yale University School of Medicine, New Haven, Connecticut, USA.
⁹ Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.
¹⁰ Division of Critical Care Medicine, Nationwide Children's Hospital, Columbus, Ohio, USA.
¹¹ Department of Pediatrics, New York University Grossman School of Medicine, New York, New York, USA.
¹² Louisiana Public Health Institute, New Orleans, Louisiana, USA.
¹³ RECOVER Patient, Caregiver, or Community Advocate Representative, New York, New York, USA.
¹⁴ Research Information Science and Computing, Mass General Brigham, Somerville, Massachusetts, USA.
¹⁵ Department of Biostatistics, NYU Long Island School of Medicine, Mineola, New York, USA.
¹⁶ Department of Medicine, University of California, San Francisco, California, USA.
¹⁷ San Francisco VA Medical Center, San Francisco, California, USA.
¹⁸ Division of General Internal Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
¹⁹ Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA.
²⁰ Division of Pediatric Respiratory Medicine, University of California San Diego, San Diego, California, USA.
²¹ Department of Pediatrics, Rady Children's Hospital, San Diego, California, USA.
²² Department of Pediatrics, University of California San Diego School of Medicine, San Diego, California, USA.
²³ Division of Infectious Diseases, Children's Hospital Los Angeles, Los Angeles, California, USA.
²⁴ Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
²⁵ Department of Biomedical Informatics, Biostatistics and Medical Epidemiology, University of Missouri School of Medicine, Columbia, Missouri, USA.
²⁶ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
²⁷ Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
²⁸ Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA.
²⁹ School of Medicine, University of Puerto Rico, San Juan, Puerto Rico.
³⁰ Department of Pediatrics, Columbia University Irving Medical Center, New York, New York, USA.
³¹ Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA.
³² Department of Infectious Disease, Nationwide Children's Hospital, Columbus, Ohio, USA.
³³ Infectious Diseases Division, Department of Pediatrics, Atlantic Health System, Goryeb Children's Hospital, Morristown, New Jersey, USA.
³⁴ Department of Adult Health and Nursing Systems, Virginia Commonwealth University School of Nursing, Richmond, Virginia, USA.
³⁵ Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York, USA.
³⁶ Providence Medical Research Center, Providence Inland Northwest Health, Spokane, Washington, USA.
³⁷ Division of Nephrology and Kidney Research Institute Seattle, University of Washington School of Medicine, Seattle, Washington, USA.
³⁸ Department of Medicine, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina USA.
³⁹ Department of Biomedical Informatics, Emory University, Atlanta, Georgia, USA.

PMID: 39907495
PMCID: PMC12272849
DOI: 10.1093/cid/ciaf046

Abstract

Background: Incidence estimates of post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, also known as long COVID, have varied across studies and changed over time. We estimated long COVID incidence among adult and pediatric populations in 3 nationwide research networks of electronic health records (EHRs) participating in the RECOVER (Researching COVID to Enhance Recovery) Initiative using different classification algorithms (computable phenotypes).

Methods: This EHR-based retrospective cohort study included adult and pediatric patients with documented acute SARS-CoV-2 infection and 2 control groups: contemporary coronavirus disease 2019 (COVID-19)-negative and historical patients (2019). We examined the proportion of individuals identified as having symptoms or conditions consistent with probable long COVID within 30-180 days after COVID-19 infection (incidence proportion). Each network (the National COVID Cohort Collaborative [N3C], National Patient-Centered Clinical Research Network [PCORnet], and PEDSnet) implemented its own long COVID definition. We introduced a harmonized definition for adults in a supplementary analysis.

Results: Overall, 4% of children and 10%-26% of adults developed long COVID, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 1.5% in children and ranged from 5% to 6% among adults, representing a lower-bound incidence estimation based on our control groups. Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants.

Conclusions: Our findings indicate that preventing and mitigating long COVID remains a public health priority. Examining temporal patterns and risk factors for long COVID incidence informs our understanding of etiology and can improve prevention and management.

Keywords: COVID; EHRs; electronic health records; long COVID; public health surveillance.

© The Author(s) 2025. Published by Oxford University Press on behalf of Infectious Diseases Society of America. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.

PubMed Disclaimer

Conflict of interest statement

Potential conflicts of interest . H. P., K. G. T., C. R. O., A. V., L. E. T., J. D., R. A. M., J. D. K., E. W. K., P. A. K., R. S. G., C. R. G., A. D., T. W. C., M. H., and K. R. T. all reports funding from the NIH. Additionally, J. A. reports grants or contracts from Pfizer and Amgen. C. G. C. reports a leadership role on the World Health Organization (WHO) Medical Scientific Advisory Committee. P. A. K. reports a leadership role with the Commonwealth of Virginia Board of Health. L. C. K. reports owning shares in Amgen, Regeneron, Sanofi, and GLAXF. K. E. R. reports funding from the NIH (National Institute on Minority Health and Health Disparities [NIMHD]) and the US Department of Agriculture (USDA). C. R. O. reports holding leadership positions with the American Academy of Pediatrics, Eastern Society of Pediatric Research, and Journal of Pediatric Infectious Diseases Society. S. E. P. received funding from the National Institute of Mental Health (NIMH) and travel support from Columbia University Mailman School of Public Health. J. L. S. reports funding from NYU Langone. K. R. T. reports funding from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIMHD, NIH Director's Office, Centers for Disease Control and Prevention (CDC), Travere, and Bayer; consulting fees and/or payments/honoraria from Eli Lilly, Boehringer Ingelheim, AstraZeneca, Bayer, Novo Nordisk, Pfizer, Travere, and ProKidney; participation in a data safety monitoring or advisory board for NIDDK/NIH and AstraZeneca; and leadership roles with the American Society of Nephrology and Clinical Journal of the American Society of Nephrology. L. E. T. reports a leadership position with the American Journal of Public Health. L. M. reports a leadership position with the International Society of Nurses in Genetics. C. K. reports receiving payments from the NIH. J. D. K. reports funding from the VA and CDC. K. C. H. reports owning stock in Pfizer. M. H. reports being a founder of Alamya Health. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.

Figures

**Graphical Abstract**
This graphical abstract is also available at Tidbit: https://tidbitapp.io/institutional-portal/clinical-infectious-diseases/tidbits/long-covid-incidence-proportion-in-adults-and-children-between-2020-and-2023/update

**Figure 1.**
Proportion of patients with long COVID and associated variables over time. Each patient was counted as having COVID-19 once, and COVID-19 index dates are graphed on the x-axis for panels B–F. The dotted red line shows a 20% benchmark across differently sized axes. All percentages were calculated using the monthly COVID-19 case count as the denominator. “NASEM” refers to the harmonized long COVID definition used in both N3C and PCORnet. A, Count of long COVID cases, with the x-axis representing the date of long COVID onset. B, Count of COVID-19 index cases each month. C, Percentage of patients developing long COVID within 180 days of their COVID-19 index date. D, Percentage of COVID-19 cases hospitalized (with or without ICU-level care) for index infection. E, Percentage of COVID-19 cases treated with Paxlovid. This excludes N3C sites not providing any data around Paxlovid orders. F, Percentage of COVID-19 cases with vaccination documented prior to the index event. Abbreviations: COVID-19, coronavirus disease 2019; ICU, intensive care unit; N3C, National COVID Cohort Collaborative; NASEM, National Academies of Sciences, Engineering, and Medicine; PCORnet, National Patient-Centered Clinical Research Network. Purple represents N3C, yellow represents PCORnet, and green represents PEDSnet.

**Figure 2.**
Long COVID incidence proportion by patient subpopulation and adjusted monthly relative hazards. A, Univariate analysis. Incidence of long COVID, calculated as the proportion of COVID-19 cases who developed long COVID within 180 days of the index infection. 95% CIs are provided. Patient characteristics align with categories described in Table 2. Vertical dotted lines represent overall long COVID incidence proportion for each network. B, Two-dimensional heatmap. Heatmaps represent the proportion of COVID-19–positive patients who developed long COVID. Percentages are stratified by COVID-19 severity and patient pre-existing conditions. “N” represents the number of patients within the group. “P” represents the number of long COVID patients within the group. Heatmap scales are based on the percentage of long COVID patients from each network, from 0% (blue) to 100% (red). The midpoint (white) of the scale represents the overall long COVID rate from each network. Values 3 or more times greater than the overall long COVID rate are colored red. C, Risk of long COVID over time compared to January 2021. Multivariable hazard ratios for incident long COVID per month are shown. Hazard ratios were generated by a multivariable Cox proportional hazards regression model, and are presented as unadjusted (black) and adjusted (orange) for age group, sex, race/ethnicity, pre-existing conditions, rurality, COVID-19 severity, vaccination status, and month of the index event. 95% CIs are provided. Abbreviations: COVID-19, coronavirus disease 2019; ED, emergency department; ICU, intensive care unit; N3C, National COVID Cohort Collaborative; PCORnet, National Patient-Centered Clinical Research Network. Purple represents N3C, yellow represents PCORnet, and green represents PEDSnet.

**Figure 3.**
Control group analysis. Long COVID incidence proportion, by COVID-19 (COVID-19–positive patients) or index event (control patients) severity and pre-existing condition burden, among (A) COVID-19–positive patients identified between 1 January 2021 and 30 May 2021; (B) contemporary COVID-19–negative patients identified between 1 January 2021 and 30 May 2021; and (C) historical control patients identified between 1 January 2019 and 30 May 2019. Heatmaps for each group are centered (white) on the global long COVID incidence estimated in that group. Lower values are shown in shades of blue, and values up to 2.5 times above the global incidence are shown in shades of red. “N” represents the number of patients within the group. “P” represents the number of long COVID patients within the group. Abbreviations: COVID-19, coronavirus disease 2019; ED, emergency department; ICU, intensive care unit; N3C, National COVID Cohort Collaborative; PCORnet, National Patient-Centered Clinical Research Network. Purple represents N3C, yellow represents PCORnet, and green represents PEDSnet.

**Figure 4.**
Harmonized long COVID incidence proportions by patient subpopulation. A, Description of logic for the NASEM-aligned definition applied to our adult populations. B, Univariate analysis applied to this additional long COVID definition. Incidence proportion was calculated as the percentage of COVID-19 cases who developed long COVID within 270 days of index infection. 95% CIs are provided. Vertical dotted lines represent overall long COVID incidence proportion for each network. C, Two-dimensional heatmap. Heatmaps represent the proportion of COVID-19–positive patients who developed long COVID. Percentages are stratified by COVID-19 severity and patient pre-existing conditions. “N” represents the number of patients within the group. “P” represents the number of long COVID patients within the group. Heatmap scales are based on the percentage of long COVID patients from each network, from 0% (blue) to 100% (red). The midpoint (white) of the scale represents the overall long COVID rate from each network. Values 3 or more times greater than the overall long COVID rate are colored red. Abbreviations: COVID-19, coronavirus disease 2019; ED, emergency department; ICU, intensive care unit; N3C, National COVID Cohort Collaborative; NASEM, National Academies of Sciences, Engineering, and Medicine; PCORnet, National Patient-Centered Clinical Research Network. Purple represents N3C, yellow represents PCORnet, and green represents PEDSnet.

See this image and copyright information in PMC

Update of

Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative.
Mandel H, Yoo Y, Allen A, Abedian S, Verzani Z, Karlson E, Kleinman L, Mudumbi P, Oliveira C, Muszynski J, Gross R, Carton T, Kim C, Taylor E, Park H, Divers J, Kelly J, Arnold J, Geary C, Zang C, Tantisira K, Rhee K, Koropsak M, Mohandas S, Vasey A, Weiner M, Mosa A, Haendel M, Chute C, Murphy S, O'Brien L, Szmuszkovicz J, Güthe N, Santana J, De A, Bogie A, Halabi K, Mohanraj L, Kinser P, Packard S, Tuttle K, Thorpe L, Moffitt R. Mandel H, et al. Res Sq [Preprint]. 2024 Apr 26:rs.3.rs-4124710. doi: 10.21203/rs.3.rs-4124710/v1. Res Sq. 2024. Update in: Clin Infect Dis. 2025 Jul 18;80(6):1247-1261. doi: 10.1093/cid/ciaf046. PMID: 38746290 Free PMC article. Updated. Preprint.

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Long COVID Incidence Proportion in Adults and Children Between 2020 and 2024: An Electronic Health Record-Based Study From the RECOVER Initiative

Affiliations

Long COVID Incidence Proportion in Adults and Children Between 2020 and 2024: An Electronic Health Record-Based Study From the RECOVER Initiative

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Update of

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Miscellaneous