The DOI matches its Crossref record; 44 of the 46 references it cites were found in a registry or an index.
Characterizing long COVID in an international cohort: 7 months of symptoms and their impact
Open accessPublished version of a preprint
Abstract
BACKGROUND: A significant number of patients with COVID-19 experience prolonged symptoms, known as Long COVID. Few systematic studies have investigated this population, particularly in outpatient settings. Hence, relatively little is known about symptom makeup and severity, expected clinical course, impact on daily functioning, and return to baseline health. METHODS: We conducted an online survey of people with suspected and confirmed COVID-19, distributed via COVID-19 support groups (e.g. Body Politic, Long COVID Support Group, Long Haul COVID Fighters) and social media (e.g. Twitter, Facebook). Data were collected from September 6, 2020 to November 25, 2020. We analyzed responses from 3762 participants with confirmed (diagnostic/antibody positive; 1020) or suspected (diagnostic/antibody negative or untested; 2742) COVID-19, from 56 countries, with illness lasting over 28 days and onset prior to June 2020. We estimated the prevalence of 203 symptoms in 10 organ systems and traced 66 symptoms over seven months. We measured the impact on life, work, and return to baseline health. FINDINGS: For the majority of respondents (>91%), the time to recovery exceeded 35 weeks. During their illness, participants experienced an average of 55.9+/- 25.5 (mean+/-STD) symptoms, across an average of 9.1 organ systems. The most frequent symptoms after month 6 were fatigue, post-exertional malaise, and cognitive dysfunction. Symptoms varied in their prevalence over time, and we identified three symptom clusters, each with a characteristic temporal profile. 85.9% of participants (95% CI, 84.8% to 87.0%) experienced relapses, primarily triggered by exercise, physical or mental activity, and stress. 86.7% (85.6% to 92.5%) of unrecovered respondents were experiencing fatigue at the time of survey, compared to 44.7% (38.5% to 50.5%) of recovered respondents. 1700 respondents (45.2%) required a reduced work schedule compared to pre-illness, and an additional 839 (22.3%) were not working at the time of survey due to illness. Cognitive dysfunction or memory issues were common across all age groups (~88%). Except for loss of smell and taste, the prevalence and trajectory of all symptoms were similar between groups with confirmed and suspected COVID-19. INTERPRETATION: Patients with Long COVID report prolonged, multisystem involvement and significant disability. By seven months, many patients have not yet recovered (mainly from systemic and neurological/cognitive symptoms), have not returned to previous levels of work, and continue to experience significant symptom burden. FUNDING: All authors contributed to this work in a voluntary capacity. The cost of survey hosting (on Qualtrics) and publication fee was covered by AA's research grant (Wellcome Trust/Gatsby Charity via Sainsbury Wellcome center, UCL).
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
![Fig. 12 Return to baseline and work impact. a) Distribution of Fatigue Assessment Scale scores for recovered (n = 257, blue) and unrecovered (n = 3505, yellow) population. The vertical dashed lines indicate the range for “No fatigue”[10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], “Fatigue”[22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], and “Extreme” (>=35). Mean values for each distribution are also marked. b) Percentage of participants in each of the three categories. c) Distribution of scores in response to “return to pre-COVID” health baseline, where 0 indicates worst (most different from baseline) and 100 indicates best (most similar to baseline). d) Working status due to COVID-19. Error bars show 95% simultaneous confidence interval.](/paper-figures/213b855e24a54c7194a392c254c6fa31/characterizing-long-covid-in-an-international-cohort-7-months-of-symptoms-and-figure-12.jpg)
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Identifying subjects who are at risk of higher perceived loneliness and related psychological factors is particularly important in the context of the so called “long COVID” syndrome [50]”
From Psychological correlates of perceived loneliness in college students before and during the COVID-19 stay-at-home period: a longitudinal study (2023) · cites this paper as [50]
Experimental — accuracy not yet measuredIn the citing paper
“These symptoms can endure up to 6–7 months and even longer [[1], [2], [3], [4], [5]].”
From Female gender is associated with long COVID syndrome: a prospective cohort study (2022) · cites this paper as [3]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Persistent Symptoms in Patients After Acute COVID-19
Carfì, A., Bernabei, R., Landi, F., & for the Gemelli Against COVID-19 Post-Acute Care Study Group (2020) · JAMA · doi:10.1001/jama.2020.12603 · Cited by 4,561
Natural language processing with Python
Bird, S., Klein, E., & Loper, E. (2009) · CERN Document Server (European Organization for Nuclear Research) · Cited by 3,472
Better Bootstrap Confidence Intervals
Efron, B. (1987) · Journal of the American Statistical Association · doi:10.1080/01621459.1987.10478410 · Cited by 3,462 · cited 2×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
MethodAttributes and predictors of long COVID
Sudre, C. H., Murray, B., Varsavsky, T., Graham, M. S., Penfold, R. S., Bowyer, R. C., Pujol, J. C., Klaser, K., Antonelli, M., Canas, L. S., et al. (2021) · Nature Medicine · doi:10.1038/s41591-021-01292-y · Cited by 2,707
Management of post-acute covid-19 in primary care
Greenhalgh, T., Knight, M., A’Court, C., Buxton, M., & Husain, L. (2020) · BMJ · doi:10.1136/bmj.m3026 · Cited by 1,771 · cited 1×
“While respiratory and some cardiovascular symptoms have been widely reported, neurological symptoms remain unclear [33].”
BackgroundEvolution of antibody immunity to SARS-CoV-2
Gaebler, C., Wang, Z., Lorenzi, J. C. C., Muecksch, F., Finkin, S., Tokuyama, M., Cho, A., Jankovic, M., Schaefer-Babajew, D., Oliveira, T. Y., et al. (2021) · Nature · doi:10.1038/s41586-021-03207-w · Cited by 1,674
High-dimensional characterization of post-acute sequelae of COVID-19
Al-Aly, Z., Xie, Y., & Bowe, B. (2021) · Nature · doi:10.1038/s41586-021-03553-9 · Cited by 1,518
Kucirka, L. M., Lauer, S. A., Laeyendecker, O. B., Boon, D., & Lessler, J. (2020) · Annals of Internal Medicine · doi:10.7326/m20-1495 · Cited by 1,414 · cited 1×
“Furthermore, the likelihood of false negatives increases after day 3 of symptom onset, when the false negative rate is 20%, reaching 66% by day 21[40].”
BackgroundTenforde, M. W., Kim, S. S., Lindsell, C. J., Billig Rose, E., Shapiro, N. I., Files, D. C., Gibbs, K. W., Erickson, H. L., Steingrub, J. S., Smithline, H. A., et al. (2020) · MMWR. Morbidity and Mortality Weekly Report · doi:10.15585/mmwr.mm6930e1 · Cited by 1,319 · cited 2×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
BackgroundConcept Decompositions for Large Sparse Text Data Using Clustering
Dhillon, I. S., & Modha, D. S. (2001) · Machine Learning · doi:10.1023/a:1007612920971 · Cited by 1,308 · cited 1×
“Symptom time course clustering Symptom time courses were clustered using spherical k-means, a variant of k-means based on cosine distances [12].”
Characterising long COVID: a living systematic review
Michelen, M., Cheng, V., Manoharan, L., Elkheir, N., Dagens, A., Hastie, C., O’Hara, M. E., Suett, J. C., Dahmash, D. T., Bugaeva, P., et al. (2021) · BMJ Global Health · doi:10.1136/bmjgh-2021-005427 · Cited by 1,004
How and why patients made Long Covid
Callard, F. J., & Perego, E. (2020) · Social Science & Medicine · doi:10.1016/j.socscimed.2020.113426 · Cited by 1,001 · cited 2×
“Early in the course of the pandemic, patients identified this trend, referring to themselves as “Long-Haulers” and the prolonged illness as “Long COVID” [7].”
BackgroundPersistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome?
Goërtz, Y. M. J., Herck, M. V., Delbressine, J. M., Vaes, A. W., Meys, R., Machado, F. V. C., Houben‐Wilke, S., Burtin, C., Posthuma, R., Franssen, F. M. E., et al. (2020) · ERJ Open Research · doi:10.1183/23120541.00542-2020 · Cited by 880
Evolution of Antibody Immunity to SARS-CoV-2Preprint
Gaebler, C., Wang, Z., Lorenzi, J. C. C., et al. (2020) · bioRxiv · doi:10.1101/2020.11.03.367391 · Cited by 810 · cited 1×
“Regarding antibody testing, it has been reported that antibody levels decrease with time [44,45], that males are likely to retain antibodies longer than females [46], and that antibody tests can be less accurate for females [47].”
BackgroundCognitive deficits in people who have recovered from COVID-19
Hampshire, A., Trender, W. R., Chamberlain, S. R., Jolly, A., Grant, J. E., Patrick, F., Mazibuko, N., Williams, S., Barnby, J. M., Hellyer, P. J., et al. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.101044 · Cited by 738
Interpreting a covid-19 test result
Watson, J., Whiting, P. F., & Brush, J. E. (2020) · BMJ · doi:10.1136/bmj.m1808 · Cited by 712
Ladds, E. C., Rushforth, A., Wieringa, S., Taylor, S., Rayner, C. R., Husain, L., & Greenhalgh, T. (2020) · BMC Health Services Research · doi:10.1186/s12913-020-06001-y · Cited by 687 · cited 2×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
MethodFalse-negative results of initial RT-PCR assays for COVID-19: A systematic review
Arévalo-Rodríguez, I., Buitrago‐García, D., Simancas‐Racines, D., Zambrano-Achig, P., del Campo, R., Ciapponi, A., Sued, O. G., Martínez-García, L., Rutjes, A. W., Low, N. N., et al. (2020) · PLoS ONE · doi:10.1371/journal.pone.0242958 · Cited by 666 · cited 1×
“This reinforces the need for early testing in patients with suspected SARS-CoV-2 infection, given that up to 54% of patients could have an initial RTPCR false-negative result [41].”
BackgroundArnold, D., Hamilton, F., Milne, A., Morley, A. J., Viner, J., Attwood, M., Noel, A. R., Gunning, S., Hatrick, J., Hamilton, S., et al. (2020) · Thorax · doi:10.1136/thoraxjnl-2020-216086 · Cited by 645 · cited 1×
“Survey response rate, calculated as the ratio of respondents who completed the survey [4] (918) to those who started the survey [7] (285), was 67.”
BackgroundDetection of Novel Coronavirus by RT-PCR in Stool Specimen from Asymptomatic Child, China
Tang, A., Tong, Z.-D., Wang, H.-L., Dai, Y.-X., Li, K.-F., Liu, J.-N., Wu, W.-J., Yuan, C., Yu, M.-L., Li, P., et al. (2020) · Emerging Infectious Diseases · doi:10.3201/eid2606.200301 · Cited by 516
Measuring fatigue in sarcoidosis: The Fatigue Assessment Scale (FAS)
Vries, J. D., Michielsen, H. J., Heck, G. L. V., & Drent, M. (2004) · British Journal of Health Psychology · doi:10.1348/1359107041557048 · Cited by 427
Long COVID in the Faroe Islands: A Longitudinal Study Among Nonhospitalized Patients
Petersen, M. S., Kristiansen, M. F., Hanusson, K. D., Danielsen, M. E., Steig, B. Á., Gaïni, S., Strøm, M., & Weihe, P. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa1792 · Cited by 357 · cited 2×
“growing number of patients with initially mild COVID-19 will experience prolonged symptoms [2,3], the profile and timeline of which remains uncertain [2,4 9].”
BackgroundCovid-19 hyperinflammation and post-Covid-19 illness may be rooted in mast cell activation syndrome
Afrin, L. B., Weinstock, L. B., & Molderings, G. J. (2020) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2020.09.016 · Cited by 319 · cited 2×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
COVID-19 cardiac injury: Implications for long-term surveillance and outcomes in survivors
Mitrani, R. D., Dabas, N., & Goldberger, J. J. (2020) · Heart Rhythm · doi:10.1016/j.hrthm.2020.06.026 · Cited by 303
Sudre, C. H., Murray, B. A. K., Varsavsky, T., et al. (2020) · medRxiv · doi:10.1101/2020.10.19.20214494 · Cited by 259 · cited 2×
“While several others have investigated Long COVID symptoms [10,23], our approach also allowed the first representation of individual symptom trajectory over time.”
BackgroundInfluentialDiagnostic Testing for the Novel Coronavirus
Sharfstein, J. M., Becker, S. J., & Mello, M. M. (2020) · JAMA · doi:10.1001/jama.2020.3864 · Cited by 232 · cited 1×
“Access to adequate diagnostic tests in the early stages of the pandemic was notably limited, which likely contributed to respondents in this cohort being unable to be tested and/or being tested later in their illness [42].”
BackgroundStussman, B. J., Williams, A., Snow, J., Gavin, A., Scott, R., Nath, A., & Walitt, B. T. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.01025 · Cited by 165 · cited 9×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
MethodInfluentialAnalytical comparisons of SARS-COV-2 detection by qRT-PCR and ddPCR with multiple primer/probe sets
Liu, X., Feng, J., Zhang, Q., Guo, D., Zhang, L., Suo, T., Hu, W., Guo, M. S., Wang, X., Huang, Z., et al. (2020) · Emerging Microbes & Infections · doi:10.1080/22221751.2020.1772679 · Cited by 159 · cited 1×
“The sensitivity of diagnostic tests may depend on the primer/probe sets [38,39].”
BackgroundPostural orthostatic tachycardia syndrome
Agarwal, A., Garg, R., Ritch, A., & Sarkar, P. (2007) · Postgraduate Medical Journal · doi:10.1136/pgmj.2006.055046 · Cited by 127 · cited 14×
“By the time respondents took the survey, 155 had received a diagnosis of POTS, and 118 had received a diagnosis of ME/ CFS. 33.9% of respondents who reported tachycardia measured an increase of at least 30 BPM when standing, suggesting a possible POTS diagnosis [33].”
BackgroundInfluentialArnold, D., Hamilton, F., Milne, A., et al. (2020) · medRxiv · doi:10.1101/2020.08.12.20173526 · Cited by 110
Survival Analysis - A Self-Learning Text Third Edition
Puyneers, P. (2012) · Cited by 96
Surveillance is underestimating the burden of the COVID-19 pandemic
Alwan, N. A. (2020) · The Lancet · doi:10.1016/s0140-6736(20)31823-7 · Cited by 92 · cited 1×
“Public discourse on COVID-19 has largely centered around those with severe or fatal illness [1].”
BackgroundPatient-Led Research Collaborative: embedding patients in the Long COVID narrative
McCorkell, L., Assaf, G., Davis, H., Wei, H., & Akrami, A. (2021) · PAIN Reports · doi:10.1097/pr9.0000000000000913 · Cited by 92 · cited 2×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
MethodSelf-citationSalmon, D., Slama, D., de Broucker, T., Karmochkine, M., Pavie, J., Sorbets, E., Etienne, N., Batisse, D., Spiridon, G., Baut, V. L., et al. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.12.002 · Cited by 91 · cited 10×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
BackgroundInfluentialCare Dependency in Non-Hospitalized Patients with COVID-19
Vaes, A. W., Machado, F. V. C., Meys, R., Delbressine, J. M., Goërtz, Y. M. J., Herck, M. V., Houben‐Wilke, S., Franssen, F. M. E., Vijlbrief, H., Spies, Y., et al. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9092946 · Cited by 88
Disability Accommodation in Nonstandard and Precarious Employment Arrangements
Shuey, K. M., & Jovic, E. (2013) · Work and Occupations · doi:10.1177/0730888413481030 · Cited by 71 · cited 1×
“Lower wage earners may find it especially challenging to access accommodations and benefits, yet they are in need of protections the most to ensure financial stability [36].”
BackgroundCharacterising long term Covid-19: a living systematic review
(2020) · doi:10.1101/2020.12.08.20246025 · Cited by 61 · cited 2×
“While as of yet there is no agreed upon case definition of Long COVID [8,12], we define the illness as a collection of symptoms that develop during or following a confirmed or suspected case of COVID19, and which continue for more than 28 days.”
Neurologic manifestations of nonhospitalized patients with COVID‐19 in Wuhan, China
Ding, H., Yin, S., Cheng, Y., Cai, Y., Huang, W., & Deng, W. (2020) · MedComm · doi:10.1002/mco2.13 · Cited by 44 · cited 1×
“Prior studies have identified evidence of cognitive dysfunction induced by COVID-19 illness, with few studies in the non-hospitalized population [32,35].”
BackgroundTABACOF, L. R., Tosto-Mancuso, J., Wood, J., Cortes, M., Kontorovich, A., McCarthy, D., Rizk, D., Mohammadi, N., Breyman, E., Nasr, L., et al. (2020) · medRxiv · doi:10.1101/2020.11.04.20226126 · Cited by 38 · cited 1×
“Our analysis confirms prior findings that, with the exception of change to smell and taste, symptoms are not significantly different between those who test positive for SARS-CoV-2 and those who test negative (or have not been tested), but who otherwise show strongly suggestive symptoms [7,37].”
Fatigue Assessment Scale (FAS)
Shahid, A., Wilkinson, K., Marcu, S., & Shapiro, C. M. (2011) · Springer eBooks · doi:10.1007/978-1-4419-9893-4_33 · Cited by 28 · cited 7×
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
BackgroundMethodInfluentialAnjum, I., Sohail, W., Hatipoğlu, B., & Wilson, R. (2018) · Cureus · doi:10.7759/cureus.2435 · Cited by 13 · cited 8×
“Participants answered the Fatigue Assessment Scale (FAS) questionnaire [21,22], which includes10 questions that assess both physical and mental fatigue.”
BackgroundInfluentialVashisht, R., Patel, A. R., Crews, B. O., Garner, O. B., Dahm, L., Wilson, C. S., & Butte, A. J. (2021) · JAMA Network Open · doi:10.1001/jamanetworkopen.2021.0337 · Cited by 13
Health Workers’ Antibody Levels Wane After SARS-CoV-2 Infection
Kuehn, B. M. (2021) · JAMA · doi:10.1001/jama.2020.25457 · Cited by 8 · cited 2×
“respiratory specimens [44] can also play an important role in testing accuracy [43].”
BackgroundCOVID-19 Precautions Hamper Breastfeeding Support
Kuehn, B. M. (2021) · JAMA · doi:10.1001/jama.2020.25241 · Cited by 6
Research works printed but not linked: 3
- NIH workshop on post-acute sequelae of COVID-19 (Day 2) [Internet]. Available from: https://videocast.nih.gov/watch=38879
- Tang, 2020, 26, 1337
- Williams, 2021, A two-phase, single cohort study of COVID-19, Antibody Sera-Surveillance, 6
Cited by
Sorted by citations
Long COVID: major findings, mechanisms and recommendations
Davis, H. E., McCorkell, L., Vogel, J. M., & Topol, E. J. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-022-00846-2 · Cited by 4,153
Self-citationLong-term cardiovascular outcomes of COVID-19
Xie, Y., Xu, E., Bowe, B. C., & Al‐Aly, Z. (2022) · Nature Medicine · doi:10.1038/s41591-022-01689-3 · Cited by 2,125
Fatigue and cognitive impairment in Post-COVID-19 Syndrome: a systematic review and meta-analysis
Ceban, F., Ling, S., Lui, L. M. W., Lee, Y., Gill, H., Teopiz, K. M., Rodrigues, N. B., Subramaniapillai, M., Di Vincenzo, J. D., Cao, B., et al. (2022) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2021.12.020 · Cited by 1,554
Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments
Yong, S. J. (2021) · Infectious Diseases · doi:10.1080/23744235.2021.1924397 · Cited by 1,339
Symptoms and risk factors for long COVID in non-hospitalized adults
Subramanian, A., Nirantharakumar, K., Hughes, S., Myles, P. R., Williams, T., Gokhale, K. M., Taverner, T., Chandan, J. S., Brown, K. R., Simms-Williams, N., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01909-w · Cited by 1,108
Metadata
- Authors
- Davis, H. E., Assaf, G. S., McCorkell, L., Wei, H., Low, R. J., Re'em, Y., Redfield, S., Austin, J. P., & Akrami, A.
- Affiliations
- Patient-Led Research Collaborative (US)
- Oregon Health & Science University (US)
- Corresponding author
- Akrami, Athena
- ORCID
- Venue
- eClinicalMedicine
- Publisher
- Elsevier BV
- Published
- 2021-08
- Volume
- 38
- Pages
- 101019
- ISSN
- 2589-5370 (ISSN-L)
- PMC
- PMC8280690
- OpenAlex
- W3184339862
- Cited by
- 2,881
- References
- 46
- Citations by year
- 2026: 299 · 2025: 492 · 2024: 594 · 2023: 692 · 2022: 617 · 2021: 186
- FWCI
- 249.99
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- EClinicalMedicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Wellcome Trust
- Topics
- Health Sciences › Medicine › Clinical Neurology › Long-Term Effects of COVID-19
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Social Sciences › Psychology › Clinical Psychology › COVID-19 and Mental Health
- Keywords
- long COVID, symptom clusters, fatigue, post-exertional malaise, cognitive impairment, symptom recurrence, work disability, loss of taste and smell, outpatients
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
