Epidemiologic Features of Recovery From SARS-CoV-2 Infection

Author:

Oelsner Elizabeth C.1,Sun Yifei2,Balte Pallavi P.1,Allen Norrina B.3,Andrews Howard2,Carson April4,Cole Shelley A.5,Coresh Josef6,Couper David7,Cushman Mary8,Daviglus Martha9,Demmer Ryan T.10,Elkind Mitchell S. V.1112,Gallo Linda C.13,Gutierrez Jose D.11,Howard Virginia J.4,Isasi Carmen R.14,Judd Suzanne E.4,Kanaya Alka M.15,Kandula Namratha R.316,Kaplan Robert C.14,Kinney Gregory L.17,Kucharska-Newton Anna M.18,Lackland Daniel T.19,Lee Joyce S.20,Make Barry J.21,Min Yuan-I.22,Murabito Joanne M.23,Norwood Arnita F.22,Ortega Victor E.24,Pettee Gabriel Kelley4,Psaty Bruce M.25,Regan Elizabeth A.26,Sotres-Alvarez Daniela7,Schwartz David20,Shikany James M.27,Thyagarajan Bharat28,Tracy Russell P.29,Umans Jason G.30,Vasan Ramachandran S.31,Wenzel Sally E.32,Woodruff Prescott G.33,Xanthakis Vanessa3435,Zhang Ying36,Post Wendy S.37

Affiliation:

1. Division of General Medicine, Department of Medicine, Columbia University Irving Medical Center, New York, New York

2. Department of Biostatistics, Mailman School of Public Health, Columbia University Irving Medical Center, New York, New York

3. Center for Epidemiology and Population Health, Northwestern Feinberg School of Medicine, Chicago, Illinois

4. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham

5. Texas Biomed, San Antonio, Texas

6. Departments of Medicine and Public Health, NYU Grossman School of Medicine, New York, New York

7. Collaborative Studies Coordinating Center, Department of Biostatistics, University of North Carolina, Chapel Hill

8. Division of Hematology/Oncology, Department of Medicine, Larner School of Medicine, University of Vermont, Burlington

9. Institute for Minority Health Research, University of Illinois College of Medicine, Chicago

10. Division of Epidemiology, Department of Quantitative Health Sciences, College of Medicine and Science, Mayo Clinic, Rochester, Minnesota

11. Department of Neurology, Columbia University Irving Medical Center, New York, New York

12. American Heart Association, Dallas, Texas

13. Department of Psychology, San Diego State University, California

14. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York

15. Departments of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco

16. Department of Medicine, Northwestern Feinberg School of Medicine, Chicago, Illinois

17. Department of Epidemiology, University of Colorado Denver

18. Department of Epidemiology and Environmental Health, University of Kentucky, Lexington

19. Department of Neurology, Medical University of South Carolina, Charleston

20. Division of Pulmonary and Critical Care, Department of Medicine, University of Colorado, Aurora

21. Division of Pulmonary, Critical Care and Sleep, Department of Medicine, National Jewish Health, Denver, Colorado

22. Department of Medicine, University of Mississippi Medical Center, Jackson

23. Department of Medicine, Boston University, Boston, Massachusetts

24. Division of Pulmonary Medicine, Department of Medicine, Mayo Clinic, Phoenix, Arizona

25. Departments of Epidemiology and Medicine, University of Washington, Seattle

26. Division of Rheumatology, Department of Medicine, National Jewish Health, Denver, Colorado

27. Division of Preventive Medicine, Heersink School of Medicine, University of Alabama at Birmingham

28. Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis

29. Department of Pathology and Laboratory Medicine, University of Vermont, Burlington

30. MedStar Health Research Institute, School of Medicine, Georgetown University, Washington, District of Columbia

31. School of Public Health, University of Texas School of Public Health San Antonio

32. Department of Pulmonary, Allergy and Critical Care, Department of Medicine, University of Pittsburgh, Pennsylvania

33. Divison of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California, San Francisco

34. Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts

35. Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts

36. Departments of Biostatistics and Epidemiology, Hudson College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City

37. Division of Cardiology, Departments of Medicine and Epidemiology, Johns Hopkins University, Baltimore, Maryland

Abstract

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Publisher

American Medical Association (AMA)

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