This cohort study investigates the incidence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)–like symptoms in individuals tested for SARS-CoV-2 infection and whether ME/CFS symptom prevalence is associated with positive or negative COVID-19 test results.
Key Points
Question
Does prevalence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)–like illness differ between individuals with an acute infection–like index illness who are COVID-19 positive or negative?
Findings
In this cohort study of 4378 participants, the weighted prevalence of ME/CFS-like illness was 4.5% or less at 3 to 12 months after the index illness in the COVID-19–positive and COVID-19–negative groups, with no significant differences in odds of ME/CFS-like illness.
Meaning
The findings suggest that ME/CFS-like illness following an acute infection–like index illness does not vary by COVID-19 test result.
Abstract
Importance
Chronic symptoms reported following an infection with SARS-CoV-2, such as cognitive problems, overlap with symptoms included in the definition of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS).
Objective
To evaluate the prevalence of ME/CFS-like illness subsequent to acute SARS-CoV-2 infection, changes in ME/CFS symptoms through 12 months of follow-up, and the association of ME/CFS symptoms with SARS-CoV-2 test results at the acute infection–like index illness.
Design, Setting, and Participants
This prospective, multisite, longitudinal cohort study (Innovative Support for Patients with SARS-CoV-2 Infections Registry [INSPIRE]) enrolled participants from December 11, 2020, to August 29, 2022. Participants were adults aged 18 to 64 years with acute symptoms suggestive of SARS-CoV-2 infection who received a US Food and Drug Administration–approved SARS-CoV-2 test at the time of illness and did not die or withdraw from the study by 3 months. Follow-up surveys were collected through February 28, 2023.
Exposure
COVID-19 status (positive vs negative) at enrollment.
Main Outcome and Measures
The main outcome was the weighted proportion of participants with ME/CFS-like illness based on the 2015 Institute of Medicine clinical case definition using self-reported symptoms.
Results
A total of 4378 participants were included in the study. Most were female (3226 [68.1%]). Mean (SD) age was 37.8 (11.8) years. The survey completion rates ranged from 38.7% (3613 of 4738 participants) to 76.3% (1835 of 4738) and decreased over time. The weighted proportion of participants identified with ME/CFS-like illness did not change significantly at 3 through 12 months of follow-up and was similar in the COVID-19–positive (range, 2.8%-3.7%) and COVID-19–negative (range, 3.1%-4.5%) groups. Adjusted analyses revealed no significant difference in the odds of ME/CFS-like illness at any time point between COVID-19–positive and COVID-19–negative individuals (marginal odds ratio range, 0.84 [95% CI, 0.42-1.67] to 1.18 [95% CI, 0.55-2.51]).
Conclusions and Relevance
In this prospective cohort study, there was no evidence that the proportion of participants with ME/CFS-like illness differed between those infected with SARS-CoV-2 vs those without SARS-CoV-2 infection up to 12 months after infection. A 3% to 4% prevalence of ME/CFS-like illness after an acute infection–like index illness would impose a high societal burden given the millions of persons infected with SARS-CoV-2.
Introduction
Chronic medical syndromes can occur after a variety of acute infections (eg, postpolio syndrome, post–Epstein Barr virus syndrome).1,2 These postacute infection syndromes (PAISs) share similar symptoms, including functional impairment associated with fatigue, exertion intolerance, and cognitive problems. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), a complex, chronic, debilitating condition with systemic manifestations often linked to a prior acute influenza-like illness,3,4 is emblematic of the largely enigmatic group of PAISs. Fatigue is the most common symptom among patients with post-COVID condition or long COVID,5,6,7 and the symptom profile of postacute sequelae of COVID-19 and of other PAISs overlaps with characteristic symptoms of ME/CFS. The prevalence of long COVID symptoms in the US,8 including those overlapping with ME/CFS symptoms, suggests that millions of individuals will be impacted, with medical costs in the billions,9 emphasizing the need to understand PAISs.
The COVID-19 pandemic raised awareness of PAISs and provides a unique opportunity to examine the occurrence of ME/CFS following a specific infection. Through the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) study, we collected thousands of self-reported outcome data points, allowing the identification and evaluation of patients with ME/CFS-like illness. The objective of this analysis was to evaluate the occurrence of ME/CFS among INSPIRE participants following symptomatic acute illness that prompted their COVID-19 test and to compare the odds of ME/CFS in the COVID-19–positive cohort and the COVID-19–negative cohort.
Methods
Study Design and Data Source
INSPIRE was a multicenter, prospective, longitudinal registry cohort study that enrolled individuals who experienced an acute index illness suggestive of COVID-19 between December 11, 2020, and August 29, 2022. Eight geographically diverse study sites across the US recruited and enrolled participants with a protocol and methods previously described.10 Recruitment occurred in person, by email or telephone, and through electronic advertisement. A secure online platform (Hugo; Hugo Health LLC) facilitated collection of consent and survey distribution. Participants self-enrolled by first completing an online eligibility screener, during which they were asked to self-report COVID-19–like symptoms that they experienced within the past 42 days and provide documentation of their valid COVID-19 test and test result. If respondents were deemed eligible for participation, they were provided a consent form on the online platform. Follow-up surveys were collected through February 28, 2023. The institutional review board at each of the study sites reviewed and approved this study. The Centers for Disease Control and Prevention (CDC) reviewed the project and determined the study was nonengaged human participants research. The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.11
Cohort Definition
The INSPIRE study included adult participants (aged ≥18 years) who were fluent in English or Spanish, had access to an internet-enabled device to allow for participation, and had self-reported symptoms suggestive of acute SARS-CoV-2 infection at the time of their SARS-CoV-2 test. Participants had to have been tested for SARS-CoV-2 with a US Food and Drug Administration–approved or authorized molecular or antigen-based assay within 42 days before their study enrollment. For this analysis, we excluded participants aged 65 years or older to minimize the confounding impact of age-associated illnesses that could explain ME/CFS symptoms.12,13,14 We excluded participants who did not link their electronic health portal connection with the online platform, did not complete the baseline survey, died or withdrew from the study before 3 months, or did not have valid COVID-19 test results. The flowchart (eFigure 1 in Supplement 1) has detailed information on recruitment and follow-up completion.
Participants were grouped as either COVID-19 positive or COVID-19 negative based on their index SARS-CoV-2 test result. If they had more than 1 test within 7 days of enrollment and results were discordant, we considered the positive test result to be the true result. If a participant’s test result changed more than 7 days after enrollment, we kept the participant in their initial group and adjusted for subsequent positive test results as a covariate.
Variables
Participants completed surveys at baseline and at 4 quarterly follow-up times. Participants self-reported sociodemographic data, including age, gender (female, male, or transgender, nonbinary, or other gender), race (Asian, Native Hawaiian, or Other Pacific Islander; Black or African American; White; or other [groups are listed in eAppendix 3 in Supplement 1] or multiracial), ethnicity (Hispanic, Latino, or of Spanish origin or not Hispanic, Latino, or of Spanish origin), educational level, income, employment status, health insurance status, and marital status. Self-reported race and ethnicity items on the baseline survey were included because patient outcomes have been reported to vary across racial and ethnic groups. Standardized questions assessing physical and mental health, symptoms, access to care, and work-related outcomes were included in the baseline and follow-up surveys.15 Participants listed other conditions that could contribute to ME/CFS symptoms in free-text responses (a list of the free-text entries is included in eAppendix 2 in Supplement 1). The Patient-Reported Outcomes Measurement Information System–29 (PROMIS-29) profile, version 2.1 was administered at baseline and at all follow-up times.16,17 It contains 7 domains, including symptom-oriented (sleep, pain, anxiety, depression, and energy or fatigue) and function-oriented (physical function and social role or activity limitation) measures. We assessed cognitive function via the PROMIS Short Form–Cognitive Function 8a measure. The PROMIS measures use T-score metrics with a mean of 50 and SD of 10 in a reference population (ie, the US general population). Higher scores indicate a greater degree of the concept being measured (eg, better functioning for the physical function subscale, more depressed for the depression subscale).
ME/CFS Outcomes of Interest
We used the 2015 Institute of Medicine (IOM) criteria15 for binary classification of the primary ME/CFS outcome, operationalized using participants’ responses to symptoms from the CDC ME/CFS Symptom Screener–Short Form, version 1.2 (eAppendix 1 in Supplement 1) and the Physical Function subscale of the PROMIS-29, version 2.118 profile (algorithm in eTable 1 in Supplement 1). In brief, the criteria include activity limitations associated with fatigue, postexertional malaise, and sleep problems as well as either cognitive impairment or orthostatic intolerance. Because ME/CFS diagnosis requires a full clinical evaluation to identify treatable conditions contributing to symptoms used in diagnosis, the self-reported information in this study only allowed determination of ME/CFS-like illness, hereafter referred to as ME/CFS. Additionally, the survey questions did not allow clear detection of the presence of chronic symptoms before participants’ acute index illness. The count of ME/CFS diagnostic criteria met (0-5) was also used as an outcome for this study.
For simplicity of monitoring ME/CFS-related symptoms, we grouped participants as ever having ME/CFS symptoms if they met criteria at any time point (acute index illness through 12 months) or never having ME/CFS symptoms if they did not meet criteria at any time point. We focused regression analysis results comparing ME/CFS classification at 3 months and beyond but, for parsimony, included those who ever met the ME/CFS definition at any time point to summarize participant characteristics descriptively.
Statistical Analysis
Statistical analyses were conducted using SAS, version 9.4 (SAS Institute Inc). All tests were 2-sided with a significance threshold of P = .05. Bivariate analyses were performed to examine the association between participant characteristics and ME/CFS status at any time point and whether characteristics were balanced between COVID-19–positive and COVID-19–negative participants. This identified significant differences between the COVID-19–positive and COVID-19–negative groups in baseline characteristics that were associated with ME/CFS outcomes. To address the imbalanced distribution of these confounders, we used the inverse propensity score weighting (IPW) technique. We assessed (Table 1 and eTable 2 and eFigure 2 in Supplement 1) how well the distribution of confounders and covariates were balanced between the COVID-19–positive and COVID-19–negative groups through IPW. Because of the need for balancing groups by COVID-19 status using IPW, all results in the main text are weighted, and observed (unweighted) results are included in eTable2 in Supplement 1.
Table 1. Weighted Distribution of Confounders and Covariates Between COVID-19 Groupsa.
| Characteristic | Participants, No. (%) | |||
|---|---|---|---|---|
| Overall (N = 4738) | COVID-19 positive (n = 2418) | COVID-19 negative (n = 2320) | P value | |
| Age at enrollment, y | ||||
| 18-34 | 2080 (43.9) | 1088 (45.0) | 992 (42.8) | .27 |
| 35-49 | 1703 (36.0) | 846 (35.0) | 858 (37.0) | |
| 50-64 | 955 (20.2) | 485 (20.1) | 470 (20.2) | |
| Gender | ||||
| Female | 3236 (68.3) | 1654 (68.4) | 1582 (68.2) | .99 |
| Male | 1435 (30.3) | 730 (30.2) | 705 (30.4) | |
| Transgender, nonbinary, or otherb | 67 (1.4) | 34 (1.4) | 33 (1.4) | |
| Ethnicity | ||||
| Hispanic, Latino, or of Spanish origin | 690 (14.6) | 353 (14.6) | 337 (14.5) | .97 |
| Not Hispanic, Latino, or of Spanish origin | 4048 (85.4) | 2065 (85.4) | 1983 (85.5) | |
| Race | ||||
| Asian, Native Hawaiian, or Other Pacific Islander | 607 (12.8) | 310 (12.8) | 297 (12.8) | .04 |
| Black or African American | 571 (12.1) | 271 (11.2) | 301 (13.0) | |
| White | 3125 (66.0) | 1592 (65.9) | 1533 (66.1) | |
| Other race or multiracialc | 435 (9.2) | 245 (10.1) | 190 (8.2) | |
| Educational attainment | ||||
| Less than high school diploma | 72 (1.5) | 35 (1.4) | 38 (1.6) | .71 |
| High school graduate or GED | 411 (8.7) | 213 (8.8) | 198 (8.5) | |
| Some college but did not complete degree | 710 (15.0) | 356 (14.7) | 354 (15.3) | |
| 2-y College degree | 353 (7.5) | 174 (7.2) | 179 (7.7) | |
| 4-y College degree | 1485 (31.3) | 781 (32.3) | 703 (30.3) | |
| More than 4-y college degree | 1707 (36.0) | 859 (35.5) | 848 (36.5) | |
| Marital status | ||||
| Never married | 1832 (38.7) | 938 (38.8) | 894 (38.5) | .94 |
| Married or living with a partner | 2427 (51.2) | 1233 (51.0) | 1194 (51.5) | |
| Divorced, widowed, or separated | 479 (10.1) | 247 (10.2) | 232 (10.0) | |
| Prepandemic family income, $ | ||||
| <10 000 | 378 (8.0) | 185 (7.7) | 193 (8.3) | .42 |
| 10 000 to <35 000 | 580 (12.2) | 294 (12.2) | 286 (12.3) | |
| 35 000 to <50 000 | 562 (11.9) | 283 (11.7) | 280 (12.0) | |
| 50 000 to <75 000 | 701 (14.8) | 341 (14.1) | 360 (15.5) | |
| ≥75 000 | 2516 (53.1) | 1315 (54.4) | 1201 (51.8) | |
| Location of COVID-19 test | ||||
| At-home testing kit | 633 (13.4) | 325 (13.4) | 308 (13.3) | .85 |
| Tent or drive-up testing site | 2349 (49.6) | 1204 (49.8) | 1145 (49.3) | |
| Clinic, including an urgent care clinic | 706 (14.9) | 345 (14.3) | 361 (15.6) | |
| Hospital | 385 (8.1) | 199 (8.2) | 186 (8.0) | |
| Emergency department | 288 (6.1) | 153 (6.3) | 135 (5.8) | |
| Other | 378 (8.0) | 193 (8.0) | 185 (8.0) | |
| Tobacco use in past 12 mo | ||||
| Daily or near daily | 347 (7.3) | 173 (7.1) | 174 (7.5) | .92 |
| Weekly | 96 (2.0) | 47 (1.9) | 49 (2.1) | |
| Monthly | 251 (5.3) | 128 (5.3) | 123 (5.3) | |
| Less than monthly | 94 (2.0) | 45 (1.8) | 49 (2.1) | |
| Not at all | 3950 (83.4) | 2026 (83.8) | 1924 (82.9) | |
| Binge drinking in past 12 mo | ||||
| Daily or near daily | 54 (1.1) | 32 (1.3) | 22 (0.9) | .23 |
| Weekly | 459 (9.7) | 243 (10.1) | 216 (9.3) | |
| Monthly | 1112 (23.5) | 569 (23.5) | 542 (23.4) | |
| Less than monthly | 619 (13.1) | 332 (13.7) | 286 (12.3) | |
| Not at all | 2495 (52.7) | 1241 (51.3) | 1254 (54.0) | |
| Health insurance | ||||
| Private and public | 83 (1.8) | 38 (1.6) | 45 (2.0) | .74 |
| Private only | 3603 (76.1) | 1840 (76.1) | 1763 (76.0) | |
| Public only | 862 (18.2) | 445 (18.4) | 417 (18.0) | |
| None | 190 (4.0) | 95 (3.9) | 95 (4.1) | |
| Hospitalized for index illnessd | ||||
| No | 3468 (73.2) | 1772 (73.3) | 1696 (73.1) | <.001 |
| Yes | 91 (1.9) | 64 (2.6) | 27 (1.1) | |
| Missing | 1180 (24.9) | 582 (24.1) | 598 (25.8) | |
| Variant period at index test datee | ||||
| Pre-Delta | 827 (17.4) | 430 (17.8) | 396 (17.1) | .57 |
| Delta | 1577 (33.3) | 814 (33.7) | 762 (32.9) | |
| Omicron | 2335 (49.3) | 1173 (48.5) | 1161 (50.1) | |
| Self-reported comorbidities | ||||
| Overweight or obesity | 1003 (21.2) | 498 (20.6) | 505 (21.8) | .33 |
| Asthma, moderate or severe | 447 (9.4) | 234 (9.7) | 213 (9.2) | .55 |
| Hypertension or high blood pressure | 443 (9.3) | 215 (8.9) | 228 (9.8) | .26 |
| Current tobacco usef | 187 (4.0) | 91 (3.8) | 96 (4.2) | .48 |
| Diabetes | 183 (3.9) | 83 (3.4) | 100 (4.3) | .13 |
| Heart conditionsg | 65 (1.4) | 34 (1.4) | 31 (1.3) | .90 |
| Kidney disease | 47 (1.0) | 24 (1.0) | 24 (1.0) | .90 |
| Liver disease | 25 (0.5) | 11 (0.5) | 13 (0.6) | .60 |
| Emphysema or COPD | 23 (0.5) | 12 (0.5) | 11 (0.5) | .87 |
| Other conditionsh | 361 (7.6) | 174 (7.2) | 187 (8.0) | .28 |
| Symptoms before index illness | ||||
| Fatigue, tiredness, or exhaustion | 1115 (23.5) | 561 (23.2) | 554 (23.9) | .58 |
| Problems getting to sleep | 1050 (22.2) | 556 (23.0) | 494 (21.3) | .16 |
| Unrefreshing sleep | 740 (15.6) | 383 (15.8) | 357 (15.4) | .68 |
| Muscle aches or muscle pains | 545 (11.5) | 272 (11.2) | 273 (11.8) | .58 |
| Pain in joints | 361 (7.6) | 178 (7.4) | 183 (7.9) | .49 |
| Difficulty thinking or concentrating | 308 (6.5) | 150 (6.2) | 158 (6.8) | .41 |
| Forgetfulness or memory problems | 246 (5.2) | 125 (5.2) | 121 (5.2) | .94 |
| Dizziness or fainting | 244 (5.1) | 121 (5.0) | 123 (5.3) | .68 |
Abbreviations: COPD, chronic obstructive pulmonary disease; GED, General Educational Development.
Weighted by inverse propensity scores calculated by accounting for the confounders and covariates in the table. Variables correlated with COVID-19 status but not with the myalgic encephalomyelitis/chronic fatigue syndrome outcomes were excluded from propensity score calculation to avoid introducing noise into estimating the impact of COVID-19 infection and therefore are not included in this table. Hospitalization for the index illness was not well balanced by inverse propensity score weighting and was therefore included in the generalized estimating equation modeling.
Other gender included gender nonconforming, not listed, or preferred not to answer.
Other races listed in free-text responses entered by participants are included in eAppendix 3 in Supplement 1.
Hospitalization for the index illness was a new question added to the 3-month survey after April 14, 2021. There were 1134 participants missing a response to this question that were included as a separate category in the analysis.
Viral prevalence greater than 50% was used to determine the dominant variant.
Any type of tobacco, including smokeless tobacco.
Included coronary artery disease, heart failure, and cardiomyopathy.
Other conditions listed in free-text responses entered by participants that could contribute to myalgic encephalomyelitis/chronic fatigue syndrome symptoms. A list of the free-text entries is included in eAppendix 2 in Supplement 1.
Incorporating IPW, we used generalized estimating equation (GEE) models to examine the association between initial SARS-CoV-2 infection and ME/CFS outcomes across time and how the risk of ME/CFS outcomes changed over time in each COVID-19 group after the index illness. Specifically, we used a GEE with a binomial distribution and logit link function for the binary outcome of ME/CFS and a GEE negative binomial model with the log link function for the counts of ME/CFS diagnostic criteria met (0-5). Both models included the initial SARS-CoV-2 infection status at enrollment, time points (baseline and 4 quarterly follow-up times), any postbaseline SARS-CoV-2 infection as a time-varying covariate, and hospitalization status for the index illness, which was not fully balanced by IPW (eFigure 2 in Supplement 1). Additionally, we included adjustment for the SARS-CoV-2 variant period at enrollment using previously published methods.19 We also allowed initial COVID-19 status to interact with time points, subsequent SARS-CoV-2 infection, and the variant period. Marginal differences between the COVID-19–positive and COVID-19–negative groups were estimated at each time point. Simultaneously, changes over time from 3 through 12 months in each COVID-19 group were estimated for all possible paired time comparisons. To examine symptom and function measures between participants with and without ME/CFS, effect sizes (ie, Cohen d) were calculated for group mean differences.
Results
There were 4738 participants included in the study, of whom 3226 (68.1%) identified as female, 1437 (30.3%) as male, and 75 (1.6%) as transgender, nonbinary, or other gender. A total of 691 (14.6%) identified as Hispanic, Latino, or of Spanish origin and 4047 (85.4%) as not Hispanic, Latino, or of Spanish origin; 631 (13.3%) were Asian, Native Hawaiian, or Other Pacific Islander; 513 (10.8%), Black or African American; 3133 (66.1%), White; and 461 (9.7%), other race or multiracial. Mean (SD) age was 37.8 (11.8) years. A total of 2440 (51.5%) were married or living with a partner, and 3636 (76.7%) were privately insured (Table 2). Table 2 shows the participants’ observed baseline characteristics by ME/CFS status (ever, 322 [6.8%]; never, 4416 [93.2%]), most of which were significantly different. After IPW, the frequency of symptoms of ME/CFS reported by participants ranged from 5.1% for dizziness or fainting and 5.2% for forgetfulness or memory problems to 23.5% for fatigue (Table 1). Among all 4738 participants, the survey completion rates ranged from 38.7% (3613) to 76.3% (1835) and decreased over time. Less than one-third (1357 [28.6%]) provided data at all follow-up time points
Table 2. Observed Characteristics by Ever or Never Meeting Criteria for ME/CFS.
| Characteristic | Participants, No. (%) | P value | ||
|---|---|---|---|---|
| Overall (N = 4738) | ME/CFS classificationa | |||
| Ever (n = 322) | Never (n = 4416) | |||
| Age at enrollment, y | ||||
| 18-34 | 2161 (45.6) | 110 (34.2) | 2051 (46.4) | <.001 |
| 35-49 | 1647 (34.8) | 124 (38.5) | 1523 (34.5) | |
| 50-64 | 930 (19.6) | 88 (27.3) | 842 (19.1) | |
| Gender | ||||
| Female | 3226 (68.1) | 266 (82.6) | 2960 (67.0) | <.001 |
| Male | 1437 (30.3) | 49 (15.2) | 1388 (31.4) | |
| Transgender, nonbinary, or otherb | 75 (1.6) | 7 (2.2) | 68 (1.5) | |
| Ethnicity | ||||
| Hispanic, Latino, or of Spanish origin | 691 (14.6) | 66 (20.5) | 625 (14.2) | .002 |
| Not Hispanic, Latino, or of Spanish origin | 4047 (85.4) | 256 (79.5) | 3791 (85.8) | |
| Race | ||||
| Asian, Native Hawaiian, or Other Pacific Islander | 631 (13.3) | 18 (5.6) | 613 (13.9) | <.001 |
| Black or African American | 513 (10.8) | 36 (11.2) | 477 (10.8) | |
| White | 3133 (66.1) | 222 (68.9) | 2911 (65.9) | |
| Other race or multiracialc | 461 (9.7) | 46 (14.3) | 415 (9.4) | |
| Educational attainment | ||||
| Less than high school diploma | 65 (1.4) | 6 (1.9) | 59 (1.3) | <.001 |
| High school graduate or GED | 404 (8.5) | 37 (11.5) | 367 (8.3) | |
| Some college but did not complete degree | 663 (14.0) | 73 (22.7) | 590 (13.4) | |
| 2-y College degree | 350 (7.4) | 45 (14.0) | 305 (6.9) | |
| 4-y College degree | 1553 (32.8) | 77 (23.9) | 1476 (33.4) | |
| More than 4-y college degree | 1703 (35.9) | 84 (26.1) | 1619 (36.7) | |
| Marital status | ||||
| Never married | 1858 (39.2) | 110 (34.2) | 1748 (39.6) | <.001 |
| Married or living with a partner | 2440 (51.5) | 154 (47.8) | 2286 (51.8) | |
| Divorced, widowed, or separated | 440 (9.3) | 58 (18.0) | 382 (8.7) | |
| Prepandemic family income, $ | ||||
| <10 000 | 348 (7.3) | 31 (9.6) | 317 (7.2) | <.001 |
| 10 000 to <35 000 | 580 (12.2) | 72 (22.4) | 508 (11.5) | |
| 35 000 to <50 000 | 540 (11.4) | 52 (16.1) | 488 (11.1) | |
| 50 000 to <75 000 | 658 (13.9) | 46 (14.3) | 612 (13.9) | |
| ≥75 000 | 2612 (55.1) | 121 (37.6) | 2491 (56.4) | |
| Location of COVID-19 test | ||||
| At-home testing kit | 638 (13.5) | 29 (9.0) | 609 (13.8) | <.001 |
| Tent or drive-up testing site | 2380 (50.2) | 132 (41.0) | 2248 (50.9) | |
| Clinic, including an urgent care clinic | 656 (13.8) | 59 (18.3) | 597 (13.5) | |
| Hospital | 402 (8.5) | 33 (10.2) | 369 (8.4) | |
| Emergency department | 267 (5.6) | 45 (14.0) | 222 (5.0) | |
| Other | 395 (8.3) | 24 (7.5) | 371 (8.4) | |
| Tobacco use in past 12 mo | ||||
| Daily or near daily | 321 (6.8) | 45 (14.0) | 276 (6.3) | <.001 |
| Weekly | 94 (2.0) | 10 (3.1) | 84 (1.9) | |
| Monthly | 253 (5.3) | 15 (4.7) | 238 (5.4) | |
| Less than monthly | 81 (1.7) | 9 (2.8) | 72 (1.6) | |
| Not at all | 3989 (84.2) | 243 (75.5) | 3746 (84.8) | |
| Binge drinking in past 12 mo | ||||
| Daily or near daily | 65 (1.4) | 4 (1.2) | 61 (1.4) | <.001 |
| Weekly | 487 (10.3) | 27 (8.4) | 460 (10.4) | |
| Monthly | 1109 (23.4) | 52 (16.1) | 1057 (23.9) | |
| Less than monthly | 666 (14.1) | 24 (7.5) | 642 (14.5) | |
| Not at all | 2411 (50.9) | 215 (66.8) | 2196 (49.7) | |
| Health insurance | ||||
| Private and public | 74 (1.6) | 13 (4.0) | 61 (1.4) | <.001 |
| Private only | 3636 (76.7) | 165 (51.2) | 3471 (78.6) | |
| Public only | 835 (17.6) | 123 (38.2) | 712 (16.1) | |
| None | 193 (4.1) | 21 (6.5) | 172 (3.9) | |
| Hospitalized during index illnessd | ||||
| No | 3478 (73.4) | 226 (70.2) | 3252 (73.6) | <.001 |
| Yes | 126 (2.7) | 29 (9.0) | 97 (2.2) | |
| Missing | 1134 (23.9) | 67 (20.8) | 1067 (24.2) | |
| Variant period at index test datee | ||||
| Pre-Delta | 818 (17.3) | 76 (23.6) | 742 (16.8) | .005 |
| Delta | 1613 (34.0) | 109 (33.9) | 1504 (34.1) | |
| Omicron | 2307 (48.7) | 137 (42.5) | 2170 (49.1) | |
| Self-reported comorbidities | ||||
| Overweight or obesity | 967 (20.4) | 112 (34.8) | 855 (19.4) | <.001 |
| Asthma, moderate or severe | 466 (9.8) | 74 (23.0) | 392 (8.9) | <.001 |
| Hypertension or high blood pressure | 421 (8.9) | 50 (15.5) | 371 (8.4) | <.001 |
| Current tobacco usef | 169 (3.6) | 29 (9.0) | 140 (3.2) | <.001 |
| Diabetes | 168 (3.5) | 21 (6.5) | 147 (3.3) | .003 |
| Heart conditionsg | 69 (1.5) | 10 (3.1) | 59 (1.3) | .01 |
| Kidney disease | 40 (0.8) | 5 (1.6) | 35 (0.8) | .15 |
| Liver disease | 30 (0.6) | 4 (1.2) | 26 (0.6) | .15 |
| Emphysema or COPD | 18 (0.4) | 7 (2.2) | 11 (0.2) | <.001 |
| Other conditions in free texth | 336 (7.1) | 44 (13.7) | 292 (6.6) | <.001 |
| Symptoms before index COVID-19 test | ||||
| Fatigue, tiredness, or exhaustion | 1079 (22.8) | 151 (46.9) | 928 (21.0) | <.001 |
| Problems getting to sleep | 1078 (22.8) | 135 (41.9) | 943 (21.4) | <.001 |
| Unrefreshing sleep | 770 (16.3) | 115 (35.7) | 655 (14.8) | <.001 |
| Muscle aches or muscle pains | 515 (10.9) | 95 (29.5) | 420 (9.5) | <.001 |
| Pain in joints | 351 (7.4) | 84 (26.1) | 267 (6.0) | <.001 |
| Difficulty thinking or concentrating | 293 (6.2) | 97 (30.1) | 196 (4.4) | <.001 |
| Forgetfulness or memory problems | 227 (4.8) | 77 (23.9) | 150 (3.4) | <.001 |
| Dizziness or fainting | 209 (4.4) | 53 (16.5) | 156 (3.5) | <.001 |
Abbreviations: COPD, chronic obstructive pulmonary disease; GED, General Educational Development; ME/CFS, myalgic encephalomyelitis/chronic fatigue syndrome–like illness.
Myalgic encephalomyelitis/chronic fatigue syndrome would not be identified during acute illness, but the index time was included along with all other time points for the dichotomous classification of ever vs never having ME/CFS.
Other gender included gender nonconforming, not listed, or preferred not to answer.
Other races listed in free-text responses entered by participants are included in eAppendix 3 in Supplement 1.
Hospitalization for the index illness was a new question added to the 3-month survey after April 14, 2021. There were 1134 participants missing a response to this question that were included as a separate category in the analysis.
Viral prevalence greater than 50% was used to determine the dominant variant.
Any type of tobacco, including smokeless tobacco.
Included coronary artery disease, heart failure, and cardiomyopathy.
Other conditions listed in free-text responses entered by participants that could contribute to ME/CFS symptoms. A list of the free-text entries is included in eAppendix 2 in Supplement 1.
The weighted percentage of participants meeting the ME/CFS criteria at 3 months was 3.4% in the COVID-19–positive group and 3.7% in the COVID-19–negative group, and there was no statistically significant difference between the COVID-19–positive and COVID-19–negative groups in the prevalence of ME/CFS at any time point through 12 months of follow-up (range, 2.8%-3.7% in the COVID-19–positive group and 3.1%-4.5% in the COVID-19–negative group) (Table 3). At each follow-up survey, approximately one-third of the COVID-19–positive group and one-third of the COVID-19–negative group (range, 31.0%-37.6%) reported 1 or more of the 5 ME/CFS symptoms assessed. In both the COVID-19–positive group and the COVID-19–negative group, unrefreshing sleep was the most frequently reported ME/CFS symptom (range, 20.2%-26.3%), followed by postexertional malaise (range, 16.9%-22.4%) and orthostatic intolerance (range, 9.0%-13.1%).
Table 3. Observed and Weighted ME/CFS Outcomes Across Time by COVID-19 Groupsa.
| ME/CFS criterion | Participants, % | |||||||
|---|---|---|---|---|---|---|---|---|
| COVID-19 positive | COVID-19 negative | |||||||
| 3 mo | 6 mo | 9 mo | 12 mo | 3 mo | 6 mo | 9 mo | 12 mo | |
| Observed results | ||||||||
| ME/CFS-like illnessb | 2.7 | 1.9 | 2.6 | 2.6 | 3.8 | 3.2 | 3.7 | 3.6 |
| Reported individual criteria | ||||||||
| Postexertional malaise | 17.2 | 15.4 | 16.0 | 16.3 | 20.1 | 19.2 | 21.5 | 24.4 |
| Unrefreshing sleep | 20.9 | 21.4 | 20.6 | 22.2 | 22.8 | 23.2 | 25.0 | 25.2 |
| Fatigue | 9.2 | 8.0 | 9.3 | 9.4 | 10.1 | 9.8 | 12.0 | 12.7 |
| Orthostatic intolerance | 5.4 | 4.8 | 5.7 | 5.9 | 8.8 | 8.6 | 9.2 | 9.6 |
| Cognitive impairment | 1.3 | 1.1 | 1.5 | 1.4 | 3.5 | 2.2 | 2.1 | 2.5 |
| Criteria met, No. | ||||||||
| 0 | 69.6 | 70.0 | 70.6 | 69.5 | 65.4 | 66.6 | 64.2 | 59.1 |
| 1 | 15.9 | 17.0 | 15.3 | 15.5 | 17.6 | 16.4 | 17.2 | 22.0 |
| 2 | 8.4 | 7.5 | 7.7 | 8.3 | 8.6 | 8.8 | 8.9 | 9.1 |
| 3 | 3.2 | 3.4 | 3.7 | 4.1 | 4.4 | 4.6 | 5.8 | 5.7 |
| 4 | 2.5 | 1.8 | 2.3 | 2.1 | 2.6 | 3.0 | 3.4 | 3.2 |
| 5 | 0.4 | 0.2 | 0.4 | 0.4 | 1.3 | 0.7 | 0.8 | 0.9 |
| Weighted resultsa | ||||||||
| ME/CFS-like illnessb | 3.4 | 2.8 | 3.6 | 2.8 | 3.7 | 3.1 | 4.4 | 4.5 |
| Reported individual criteria | ||||||||
| Postexertional malaise | 18.5 | 16.9 | 17.9 | 17.3 | 18.9 | 18.6 | 20.8 | 22.4 |
| Unrefreshing sleep | 22.4 | 22.9 | 22.8 | 23.4 | 20.2 | 24.3 | 26.3 | 22.6 |
| Fatigue | 6.5 | 6.1 | 7.3 | 6.2 | 8.2 | 8.3 | 9.2 | 8.7 |
| Orthostatic intolerance | 10.3 | 9.0 | 10.6 | 10.4 | 9.6 | 9.4 | 13.1 | 12.9 |
| Cognitive impairment | 1.4 | 1.2 | 1.8 | 1.6 | 3.3 | 2.4 | 2.2 | 2.0 |
| Criteria met, No. | ||||||||
| 0 | 67.9 | 68.3 | 68.5 | 68.1 | 69.0 | 65.9 | 63.7 | 62.4 |
| 1 | 16.1 | 17.2 | 15.0 | 15.9 | 15.5 | 17.8 | 17.2 | 20.8 |
| 2 | 8.9 | 7.8 | 8.4 | 8.7 | 7.6 | 8.9 | 8.9 | 8.2 |
| 3 | 3.5 | 3.8 | 4.3 | 4.5 | 4.2 | 3.9 | 5.1 | 4.0 |
| 4 | 3.2 | 2.7 | 3.1 | s | 2.1 | 2.3 | 4.1 | 3.8 |
| 5 | 0.4 | 0.3 | 0.6 | 0.6 | 1.7 | 1.3 | 0.9 | 0.9 |
Abbreviation: ME/CFS, myalgic encephalomyelitis/chronic fatigue syndrome–like illness.
Weighted by inverse propensity scores.
Defined as meeting criteria for postexertional malaise, unrefreshing sleep, and fatigue and for either orthostatic intolerance or cognitive impairment.
Table 4 summarizes the time course of symptoms in the groups that ever or never had ME/CFS symptoms stratified by COVID-19 status. The group that ever had ME/CFS symptoms consistently rated their symptoms as more severe (ie, higher scores) compared with the group that never had ME/CFS symptoms regardless of COVID-19 status. The effect size for the difference in scores between participants who ever and never had ME/CFS symptoms for both the COVID-19–positive group and the COVID-19–negative group was moderate to very large for nearly all symptoms at all time points, suggesting greater symptom prevalence and severity among the group that ever had ME/CFS symptoms. The effect sizes tended to be larger for the COVID-19–positive group (Cohen d range, 2.72 [95% CI, 2.72-8.05] to 0.10 [95% CI, 0.06-0.22]) compared with the COVID-19–negative group (Cohen d range, 1.46 [95% CI, 1.45-4.30] to 0.25 [95% CI, 0.05-0.34]).
Table 4. Post–Acute Illness Health Status by COVID-19 Group and Ever Having ME/CFS-Like Illness, Weighted by Inverse Propensity Scores.
| Health status | COVID-19 status, ME/CFS-like illness status | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 3 mo | 6 mo | 9 mo | 12 mo | |||||||||||||
| Positive | Negative | Positive | Negative | Positive | Negative | Positive | Negative | |||||||||
| Ever | Never | Ever | Never | Ever | Never | Ever | Never | Ever | Never | Ever | Never | Ever | Never | Ever | Never | |
| Weighted total participants, No.a | 100 | 1740 | 96 | 1633 | 88 | 1582 | 104 | 1537 | 80 | 1178 | 90 | 1251 | 58 | 855 | 77 | 927 |
| Symptom severity score, mean (SD)b | ||||||||||||||||
| Difficulty thinking or concentrating that caused you to substantially cut back on your activities | 9.6 (3.5) | 6.3 (3.3) | 11.3 (6.1) | 5.8 (5.5) | 10.4 (4.0) | 5.9 (3.2) | 9.9 (7.6) | 5.7 (5.9) | 5.1 (3.8) | 3.5 (2.8) | 4.5 (5.0) | 3.2 (5.2) | 10.3 (3.7) | 6.0 (3.3) | 11.4 (7.0) | 5.7 (4.8) |
| Forgetfulness or memory problems that caused you to substantially cut back on your activities | 9.1 (3.7) | 5.9 (3.3) | 11.2 (6.2) | 6.6 (6.7) | 10.6 (4.0) | 5.3 (3.1) | 10.3 (8.2) | 6.5 (5.6) | 11.3 (3.5) | 6.4 (3.4) | 11.2 (6.2) | 7.0 (6.8) | 9.8 (3.5) | 5.8 (3.3) | 11.0 (7.5) | 6.4 (5.2) |
| Dizziness or fainting | 3.8 (3.5) | 3.5 (2.9) | 8.4 (7.1) | 4.2 (4.3) | 4.8 (3.6) | 2.8 (2.2) | 8.6 (8.5) | 3.3 (3.4) | 9.4 (3.6) | 5.9 (3.3) | 8.0 (5.6) | 6.4 (6.2) | 5.1 (3.8) | 3.5 (2.8) | 4.5 (5.0) | 3.2 (5.2) |
| Fatigue, tiredness, or exhaustion | 10.1 (3.4) | 5.5 (3.0) | 10.8 (5.5) | 5.8 (5.3) | 10.5 (3.6) | 5.6 (3.0) | 11.8 (5.2) | 5.4 (5.6) | 11.1 (3.9) | 5.7 (3.0) | 11.4 (6.7) | 6.4 (5.8) | 10.6 (3.4) | 5.8 (3.1) | 11.3 (4.9) | 5.5 (5.1) |
| Muscle aches or muscle pains | 8.8 (4.0) | 5.0 (3.0) | 9.1 (6.4) | 5.3 (6.0) | 9.6 (4.1) | 5.3 (2.9) | 10.4 (6.7) | 4.0 (5.2) | 10.1 (3.5) | 5.9 (3.0) | 11.3 (5.3) | 5.7 (5.8) | 9.6 (3.5) | 4.9 (3.1) | 7.7 (8.0) | 5.7 (5.3) |
| Pain in joints | 10.3 (4.4) | 5.5 (3.3) | 9.3 (7.6) | 6.6 (6.7) | 10.1 (3.6) | 5.7 (3.1) | 8.5 (7.7) | 5.2 (5.5) | 10.1 (3.4) | 5.7 (3.1) | 10.9 (5.9) | 6.8 (6.1) | 9.1 (4.0) | 6.1 (3.4) | 8.4 (4.5) | 6.0 (4.9) |
| Problems getting to sleep, sleeping through the night, or waking up on time | 9.9 (3.6) | 6.6 (3.4) | 10.8 (5.5) | 6.3 (6.0) | 9.6 (3.3) | 6.5 (3.5) | 10.6 (7.1) | 6.7 (5.7) | 9.6 (3.5) | 4.9 (3.1) | 7.7 (8.0) | 5.7 (5.3) | 11.2 (3.2) | 6.5 (3.2) | 10.6 (6.1) | 6.5 (5.8) |
| Unrefreshing sleep | 10.0 (3.5) | 5.8 (3.2) | 9.9 (5.9) | 5.8 (5.9) | 9.7 (3.5) | 5.9 (3.3) | 11.9 (6.6) | 5.7 (5.5) | 11.5 (4.1) | 6.1 (3.0) | 10.0 (9.3) | 7.1 (5.7) | 10.1 (3.1) | 5.8 (3.1) | 9.0 (6.7) | 6.0 (5.5) |
| ME/CFS-like illness diagnostic criteria, No. (%)c | ||||||||||||||||
| Postexertional malaise | 87 (85.0) | 267 (14.8) | 79 (81.1) | 260 (15.1) | 67 (72.6) | 218 (13.5) | 84 (79.6) | 231 (14.6) | 66 (82.6) | 162 (13.5) | 75 (84.3) | 207 (16.1) | 43 (73.7) | 118 (13.5) | 66 (84.7) | 161 (16.8) |
| Unrefreshing sleep | 83 (81.0) | 343 (18.9) | 76 (77.3) | 300 (17.3) | 76 (81.9) | 312 (19.2) | 74 (70.1) | 340 (21.5) | 66 (81.7) | 225 (18.7) | 79 (87.8) | 283 (22.0) | 49 (83.9) | 172 (19.7) | 55 (70.4) | 173 (18.1) |
| Fatigue | 74 (73.0) | 47 (2.6) | 71 (73.0) | 71 (4.1) | 56 (60.8) | 48 (2.9) | 85 (80.1) | 52 (3.3) | 56 (69.5) | 37 (3.1) | 70 (77.8) | 53 (4.1) | 31 (54.1) | 26 (2.9) | 51 (66.3) | 39 (4.1) |
| Orthostatic intolerance | 10 (9.6) | 20 (1.1) | 36 (37.1) | 21 (1.2) | 12 (13.0) | 8 (0.5) | 28 (26.6) | 13 (0.8) | 10 (12.7) | 13 (1.1) | 18 (20.3) | 12 (0.9) | 7 (11.3) | 8 (0.9) | 12 (15.5) | 8 (0.8) |
| Cognitive impairment | 75 (73.7) | 123 (6.8) | 75 (77.4) | 96 (5.5) | 66 (70.6) | 88 (5.4) | 67 (62.9) | 91 (5.7) | 55 (68.2) | 78 (6.5) | 67 (75.3) | 109 (8.4) | 36 (62.0) | 60 (6.8) | 51 (66.0) | 78 (8.2) |
| PROMIS-29 domain T scores, mean (SD) | ||||||||||||||||
| Higher score is better | ||||||||||||||||
| Cognitive function | 33.6 (6.3) | 48.9 (8.7) | 32.5 (13.6) | 47.5 (15.2) | 33.3 (7.3) | 49.5 (8.7) | 34.1 (12.7) | 48.7 (15.3) | 32.9 (6.6) | 49.2 (8.9) | 29.9 (11.2) | 48.6 (15.3) | 33.0 (6.4) | 49.5 (9.1) | 31.3 (12.2) | 48.4 (16.4) |
| Physical function | 36.7 (5.8) | 52.3 (5.7) | 36.7 (8.2) | 51.4 (11.5) | 37.1 (6.3) | 52.4 (5.7) | 36.4 (10.5) | 51.4 (11.6) | 37.9 (5.7) | 52.2 (5.8) | 34.9 (8.4) | 51.2 (11.3) | 38.6 (5.3) | 52.1 (6.0) | 36.2 (9.8) | 50.6 (11.8) |
| Social participation | 38.7 (8.1) | 55.9 (7.5) | 38.5 (10.5) | 54.4 (14.0) | 39.1 (8.4) | 56.6 (7.2) | 38.3 (14.1) | 55.0 (13.9) | 41.2 (6.6) | 56.6 (7.2) | 36.1 (13.0) | 55.0 (12.9) | 42.8 (6.5) | 57.0 (6.9) | 36.2 (14.0) | 54.7 (13.6) |
| Lower score is better | ||||||||||||||||
| Anxiety | 62.4 (8.1) | 51.3 (7.7) | 61.5 (14.0) | 53.1 (13.5) | 62.5 (8.4) | 50.9 (7.6) | 59.8 (15.0) | 52.3 (13.3) | 61.1 (8.0) | 50.6 (7.8) | 59.5 (14.4) | 51.8 (14.0) | 62.2 (8.5) | 50.2 (7.9) | 60.3 (10.5) | 51.5 (14.0) |
| Depression | 59.0 (8.2) | 49.0 (7.0) | 57.4 (15.1) | 49.9 (12.4) | 59.0 (8.7) | 48.7 (7.0) | 61.0 (13.1) | 49.5 (12.7) | 58.9 (7.9) | 48.7 (7.0) | 60.1 (13.7) | 49.4 (12.7) | 59.8 (9.0) | 48.4 (7.0) | 57.4 (16.2) | 49.4 (13.1) |
| Fatigue | 64.9 (6.7) | 50.3 (8.1) | 66.3 (11.7) | 51.8 (14.2) | 65.5 (6.9) | 49.9 (8.2) | 66.7 (14.5) | 51.3 (14.5) | 64.5 (6.5) | 49.8 (8.5) | 68.9 (9.4) | 51.4 (14.1) | 64.8 (6.4) | 49.4 (8.6) | 67.4 (12.2) | 50.8 (14.6) |
| Pain interference | 62.4 (8.0) | 46.4 (6.2) | 62.6 (12.3) | 48.4 (12.7) | 62.7 (7.9) | 46.5 (6.3) | 63.3 (12.8) | 48.2 (12.2) | 61.4 (7.9) | 46.9 (6.6) | 64.5 (13.1) | 48.4 (12.5) | 61.8 (7.2) | 46.7 (6.5) | 62.6 (11.9) | 48.9 (13.1) |
| Sleep disturbance | 56.1 (3.8) | 50.8 (3.6) | 55.7 (5.7) | 51.2 (6.7) | 55.2 (4.2) | 50.7 (3.6) | 56.4 (5.8) | 51.0 (7.0) | 55.9 (4.0) | 50.5 (3.7) | 57.1 (4.6) | 51.2 (6.7) | 55.7 (3.7) | 50.6 (3.9) | 55.7 (6.4) | 50.9 (6.3) |
Abbreviations: ME/CFS, myalgic encephalomyelitis/chronic fatigue syndrome–like illness; PROMIS-29, Patient-Reported Outcomes Measurement Information System–29.
Nonmissing weighted total. The number of missing cases was 3 or fewer across all groups and time points.
Symptoms were assessed using the Centers for Disease Control and Prevention (CDC) ME/CFS Symptom Screener.
Percentages were calculated among nonmissing cases. The number of missing cases was less than 10 across all groups and time points.
In weighted and adjusted results, there were no statistically significant differences in the odds of ME/CFS between COVID-19–positive and COVID-19–negative participants at any time point (marginal odds ratio range, 0.84 [95% CI, 0.42-1.67] to 1.18 [95% CI, 0.55-2.51]) (Figure). The odds of ME/CFS also did not significantly differ across time points in either the COVID-19–positive group or the COVID-19–negative group (Figure). The marginal incidence rate ratio (MIRR) of ME/CFS symptom count was not significantly different between the COVID-19–positive and COVID-19–negative groups at any time point (eg, 12-month MIRR: 0.96; 95% CI. 0.74-1.24) (Figure) and was not significantly different over time in the COVID-19–positive or COVID-19–negative group. Results were consistent when using a propensity score–matched sample (eFigure 3 in Supplement 1) compared with the full sample with IPW.
Figure. Weighted Marginal Effect Estimates for the Association Between Index COVID-19 Status and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Outcomes.
MIRR indicates marginal incidence rate ratio; MOR, marginal odds ratio.
Discussion
Our findings suggest that COVID-19 is no more likely than other acute infections to be associated with ME/CFS and that acute illnesses more broadly may be associated with chronic symptom burden from ME/CFS. The odds of meeting ME/CFS criteria at quarterly follow-up time points through 12 months did not differ between the COVID-19–positive and COVID-19–negative groups, and prevalence was relatively stable over this time in both groups (range, 2.8%-4.5%). Additionally, symptom severity scores for participants meeting ME/CFS criteria were similar in both COVID-19 groups and were significantly greater than for those not meeting ME/CFS criteria. The high symptom burden for participants meeting ME/CFS criteria persisted through 12 months in both cohorts, emphasizing the potential for a long duration of illness and disability. It is also important to note that the prevalence of individual symptoms, such as postexertional malaise and sleep problems, was higher than the full complex of ME/CFS symptoms and may also impose a substantial burden to patients. These findings emphasize the importance of developing clinical management strategies for patients with post–acute infection syndromes.
Our study design required an acute infection prompting COVID-19 testing. While participants testing positive had an identifiable infection (SARS-CoV-2), we were unable to collect data on the specific infection that led to symptoms from those testing negative. Our finding that ME/CFS-like illness was equally likely to occur after SARS-CoV-2 and unknown infection is similar to findings in a prospective, population-based study of acute respiratory illness in adults in the UK that found symptom burdens to be similar among participants with and without prior SARS-CoV-2 infection.20 In contrast, a large retrospective analysis of electronic health records conducted in the UK in 2020 suggested that SARS-CoV-2 infection resulted in significantly more postacute symptoms than did influenza, although symptoms were also common following influenza.21 However, that study’s definition of ME/CFS was reliant on symptom documentation in electronic health records, which can vary based on clinician expectations and inquiry about postinfectious symptoms in patients with SARS-CoV-2 infection compared with influenza.
Increasingly, ME/CFS is recognized as a chronic sequela of a variety of infections. A recently published 17-year population-based cohort study (2000-2017) using data from the Taiwan National Health Insurance Research Database demonstrated an elevated risk of CFS following infection with varicella-zoster virus, Mycobacterium tuberculosis, Escherichia coli, Staphylococcus aureus, influenza virus, and Borrelia burgdorferi.22 The prevalence of ME/CFS-like illness in the present study sample (≤4.5%) was lower than that in several previous studies of ME/CFS following a specific infection or syndrome (ie, 27% in a 4-year follow-up study of 223 patients who experienced severe acute respiratory syndrome,23 13% in a 6-month follow-up study of 301 adolescents diagnosed with acute Epstein-Barr virus infection24). Study differences, such as population sample (eg, community, clinic, or tertiary care), methods of case ascertainment, case definition, and differences in the infection preceding ME/CFS could account for this. Given that there are over 100 million confirmed cases of COVID-19 illness in the US,25 the prevalence of ME/CFS-like illness in our study represents a high absolute proportion of individuals possibly affected with ME/CFS associated with COVID-19 (2.8-3.6 million individuals).
While there are limited published data on the prevalence of post–COVID-19 ME/CFS, our findings are similar to the prevalence of 2.5% recently reported in a 6-month follow-up study of 120 patients with COVID-19 hospitalized at a university-affiliated hospital in Tehran, Iran,26 and a cross-sectional survey of 437 participants conducted in Jordan that found 2.8% of the sample to have COVID-19–related ME/CFS.27 Given that our study included a large, diverse array of participants recruited primarily from ambulatory testing and community settings, we expected somewhat lower prevalence than reported in cohorts recruited from acute care settings where initial illnesses may have been more severe. Our estimates may underrate the potential burden of ME/CFS among those who were hospitalized or experienced substantial morbidity from their COVID-19 illness. The severity of ongoing illness may also have affected participants’ willingness to volunteer for our study.
Despite the low overall prevalence of ME/CFS-like illness, we observed a high individual prevalence of ME/CFS symptoms. At each follow-up, approximately one-third of participants in both the COVID-19–positive group and the COVID-19–negative group reported 1 or more of the 5 symptoms included in the IOM definition of ME/CFS. In both groups, unrefreshing sleep was most frequently reported (range, 20.2%-26.3%) followed by postexertional malaise (range, 16.9%-22.4%) and orthostatic intolerance (range 9.0%-13.1%). The IOM criteria for ME/CFS are based on the combination of core symptoms that best differentiate the illness from other diagnoses; however, in the absence of complete clinical evaluation, classification based only on symptoms cannot rule out other conditions that contribute to the illness experienced by participants. The similarities in symptoms between the COVID-19–positive and COVID-19–negative participants support the suggestion that the clinical approach to postacute infection syndromes would be similar and care for these patients could be managed in a similar clinical setting, contributing to efficiency.
Strengths and Limitations
Our study has several strengths. We conducted an in-depth study of ME/CFS after an acute index illness during the COVID-19 pandemic in a population that included both COVID-19–positive and COVID-19–negative individuals. By including COVID-19–negative individuals who presented with another acute infection–like illness, we could assess the differential risk of ME/CFS following SARS-CoV-2 infection compared with other uncharacterized acute illnesses. We collected standardized and detailed self-reported symptom data at multiple time points. Symptom-based illnesses are often not recognized, and clinicians may inaccurately or unsystematically code them in electronic medical records28; thus, studies using data from electronic health records lacking patient-reported data are inadequate to understand the epidemiology of SARS-CoV-2–associated postacute syndromes. Other strengths include the large sample size from multiple, diverse geographic locations and settings (eg, ambulatory, emergency, and inpatient) across the US and inclusion of English and Spanish speakers. Our use of a robust IPW strategy helped mitigate the impact of significant baseline differences between COVID-19–positive and COVID-19–negative groups when evaluating the association of COVID-19 status with ME/CFS.
Our study also has limitations. Differences in baseline characteristics between COVID-19–positive and COVID-19–negative groups may not have been fully mitigated despite the robust IPW strategy. In particular, new SARS-CoV-2 infections were more common in the COVID-19–negative group, and some individuals may have been unaware of a subsequent infection. New infection was used as an adjustment factor, mitigating but not eliminating its impact. In both groups, symptoms suggestive of ME/CFS were reported prior to the index illness, but information was not complete enough to identify preexisting ME/CFS-like illness. This could have led to misclassification of ME/CFS-like illness in that we may have attributed symptoms to the index illness when those symptoms may have predated the illness. Furthermore, as ME/CFS is a symptom-based diagnosis, assessment of ME/CFS relies on self-reported symptoms that may be subject to recall and reporting bias. We used standardized questionnaires to assess symptoms to mitigate this problem. The specific infections or etiology for the acute symptoms in the COVID-19–negative group were not documented and likely heterogeneous. Some participants classified as having ME/CFS may have had an alternative diagnosis to explain their ME/CFS symptoms. To track the ME/CFS symptoms at early time points following the index illness, we did not consider 6-month duration in our ME/CFS algorithm, as would be used clinically. Less than one-third of all respondents (28.6%) provided data at all follow-up time points, so we were unable to fully evaluate stability of ME/CFS symptoms over time. However, the use of GEE allowed population average estimates to be generated at each time point with all available data included.
False-positive and false-negative COVID-19 test results at enrollment may have led to misclassification in the cohorts.29 Although we adjusted for reports of subsequent COVID-19 illness in our main model, it is possible that not everyone with a subsequent illness was symptomatic or was tested for COVID-19; thus, we may have underreported the frequency of these events. Additionally, we did not collect histories of other infection or diagnostic tests and thus could not characterize the specific infection that might account for ME/CFS in the COVID-19–negative group. The requirement for access to a verifiable COVID-19 test and internet-enabled device to complete surveys may have biased the sample to a more engaged and technologically savvy population. Furthermore, we did not include vaccination status in our analysis.
Conclusions
In this prospective, multicenter cohort study of participants with acute infection–like symptoms prompting SARS-CoV-2 testing, the prevalence of ME/CFS symptoms was similar between COVID-19–positive and COVID-19–negative individuals. At 12 months, 2.8% of those in the COVID-19–positive group and 4.5% in the COVID-19–negative group met the definition of ME/CFS. Our findings suggest that ME/CFS may follow several precipitating events (acute COVID-19 illness, other acute infections, or life disruptions due to the COVID-19 pandemic) but that regardless of reason or exact percentages, there will be millions affected who will seek care.
eFigure 1. Flowchart of INSPIRE Study Sample
eAppendix 1. CDC ME/CFS Symptom Screener–Short Form, Version 1.2
eTable 1. Operationalized Algorithm for the 2015 IOM ME/CFS Case Definition
eAppendix 2. List of Conditions Potentially Contributing to ME/CFS Symptoms Entered by Participants
eAppendix 3. Other Races Entered by Participants
eTable 2. Observed Distribution of Confounders and Covariates Between COVID-19 Groups
eFigure 2. Absolute Standardized Differences Between COVID-19 Groups
eFigure 3. Marginal Effects of Index COVID-19 Status on the ME/CFS Outcomes Based on Matched Sample
Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) Group
Data Sharing Statement
References
- 1.Choutka J, Jansari V, Hornig M, Iwasaki A. Unexplained post-acute infection syndromes. Nat Med. 2022;28(5):911-923. doi: 10.1038/s41591-022-01810-6 [DOI] [PubMed] [Google Scholar]
- 2.Komaroff AL, Bateman L. Will COVID-19 lead to myalgic encephalomyelitis/chronic fatigue syndrome? Front Med (Lausanne). 2021;7:606824. doi: 10.3389/fmed.2020.606824 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Kujawski S, Zalewski P, Newton JL. Do some long COVID patients suffer from ME/CFS? Medical Research Journal. 2021;6(4):279-280. doi: 10.5603/MRJ.a2021.0049 [DOI] [Google Scholar]
- 4.Naess H, Sundal E, Myhr KM, Nyland HI. Postinfectious and chronic fatigue syndromes: clinical experience from a tertiary-referral centre in Norway. In Vivo. 2010;24(2):185-188. [PubMed] [Google Scholar]
- 5.Anjana NKN, Annie TT, Siba S, Meenu MS, Chintha S, Anish TSN. Manifestations and risk factors of post COVID syndrome among COVID-19 patients presented with minimal symptoms—a study from Kerala, India. J Family Med Prim Care. 2021;10(11):4023-4029. doi: 10.4103/jfmpc.jfmpc_851_21 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Bell ML, Catalfamo CJ, Farland LV, et al. Post-acute sequelae of COVID-19 in a non-hospitalized cohort: results from the Arizona CoVHORT. PLoS One. 2021;16(8):e0254347. doi: 10.1371/journal.pone.0254347 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.González-Andrade F. Post-COVID-19 conditions in Ecuadorian patients: an observational study. Lancet Reg Health Am. 2022;5:100088. doi: 10.1016/j.lana.2021.100088 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Ford ND, Slaughter D, Edwards D, et al. Long COVID and significant activity limitation among adults, by age—United States, June 1-13, 2022, to June 7-19, 2023. MMWR Morb Mortal Wkly Rep. 2023;72(32):866-870. doi: 10.15585/mmwr.mm7232a3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Valdez AR, Hancock EE, Adebayo S, et al. Estimating prevalence, demographics, and costs of ME/CFS using large scale medical claims data and machine learning. Front Pediatr. 2019;6:412. doi: 10.3389/fped.2018.00412 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.O’Laughlin KN, Thompson M, Hota B, et al. ; INSPIRE Investigators . 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 One. 2022;17(3):e0264260. doi: 10.1371/journal.pone.0264260 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative . The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: guidelines for reporting observational studies. Int J Surg. 2014;12(12):1495-1499. doi: 10.1016/j.ijsu.2014.07.013 [DOI] [PubMed] [Google Scholar]
- 12.Nacul LC, Lacerda EM, Pheby D, et al. Prevalence of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) in three regions of England: a repeated cross-sectional study in primary care. BMC Med. 2011;9:91. doi: 10.1186/1741-7015-9-91 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Collin SM, Crawley E, May MT, Sterne JAC, Hollingworth W; UK CFS/ME National Outcomes Database . The impact of CFS/ME on employment and productivity in the UK: a cross-sectional study based on the CFS/ME national outcomes database. BMC Health Serv Res. 2011;11(1):217. doi: 10.1186/1472-6963-11-217 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Ho RT, Chan JS, Wang CW, et al. A randomized controlled trial of qigong exercise on fatigue symptoms, functioning, and telomerase activity in persons with chronic fatigue or chronic fatigue syndrome. Ann Behav Med. 2012;44(2):160-170. doi: 10.1007/s12160-012-9381-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Committee on the Diagnostic Criteria for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, Board on the Health of Select Populations, and Institute of Medicine. Beyond Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Redefining an Illness. National Academies Press; 2015. [PubMed] [Google Scholar]
- 16.Hays RD, Spritzer KL, Schalet BD, Cella D. PROMIS-29 v2.0 profile physical and mental health summary scores. Qual Life Res. 2018;27(7):1885-1891. doi: 10.1007/s11136-018-1842-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Cella D, Riley W, Stone A, et al. ; PROMIS Cooperative Group . The Patient-Reported Outcomes Measurement Information System (PROMIS) developed and tested its first wave of adult self-reported health outcome item banks: 2005-2008. J Clin Epidemiol. 2010;63(11):1179-1194. doi: 10.1016/j.jclinepi.2010.04.011 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Northwestern University. HealthMeasures . Accessed June 7, 2023. https://www.healthmeasures.net/explore-measurement-systems/promis
- 19.Gottlieb M, Wang RC, Yu H, et al. ; Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) Group . Severe fatigue and persistent symptoms at 3 months following severe acute respiratory syndrome coronavirus 2 infections during the Pre-Delta, Delta, and Omicron time periods: a multicenter prospective cohort study. Clin Infect Dis. 2023;76(11):1930-1941. doi: 10.1093/cid/ciad045 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Vivaldi G, Pfeffer PE, Talaei M, Basera TJ, Shaheen SO, Martineau AR. Long-term symptom profiles after COVID-19 vs other acute respiratory infections: an analysis of data from the COVIDENCE UK study. EClinicalMedicine. 2023;65:102251. doi: 10.1016/j.eclinm.2023.102251 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Taquet M, Dercon Q, Luciano S, Geddes JR, Husain M, Harrison PJ. Incidence, co-occurrence, and evolution of long-COVID features: a 6-month retrospective cohort study of 273 618 survivors of COVID-19. PLoS Med. 2021;18(9):e1003773. doi: 10.1371/journal.pmed.1003773 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Chang H, Kuo CF, Yu TS, Ke LY, Hung CL, Tsai SY. Increased risk of chronic fatigue syndrome following infection: a 17-year population-based cohort study. J Transl Med. 2023;21(1):804. doi: 10.1186/s12967-023-04636-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Lam MH, Wing YK, Yu MW, et al. Mental morbidities and chronic fatigue in severe acute respiratory syndrome survivors: long-term follow-up. Arch Intern Med. 2009;169(22):2142-2147. doi: 10.1001/archinternmed.2009.384 [DOI] [PubMed] [Google Scholar]
- 24.Katz BZ, Shiraishi Y, Mears CJ, Binns HJ, Taylor R. Chronic fatigue syndrome after infectious mononucleosis in adolescents. Pediatrics. 2009;124(1):189-193. doi: 10.1542/peds.2008-1879 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.World Health Organization. Number of COVID-19 cases reported to WHO. Accessed October 17, 2023. https://data.who.int/dashboards/covid19/cases?n=c
- 26.Simani L, Ramezani M, Darazam IA, et al. Prevalence and correlates of chronic fatigue syndrome and post-traumatic stress disorder after the outbreak of the COVID-19. J Neurovirol. 2021;27(1):154-159. doi: 10.1007/s13365-021-00949-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.AlMuhaissen S, Abu Libdeh A, ElKhatib Y, Alshayeb R, Jaara A, Bardaweel SK. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and COVID-19: is there a connection? Curr Med Res Opin. 2023;39(8):1119-1126. doi: 10.1080/03007995.2023.2242244 [DOI] [PubMed] [Google Scholar]
- 28.Menachemi N, Collum TH. Benefits and drawbacks of electronic health record systems. Risk Manag Healthc Policy. 2011;4:47-55. doi: 10.2147/RMHP.S12985 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Wisk LE, Gottlieb MA, Spatz ES, et al. ; INSPIRE Group . Association of initial SARS-CoV-2 test positivity with patient-reported well-being 3 months after a symptomatic illness. JAMA Netw Open. 2022;5(12):e2244486. doi: 10.1001/jamanetworkopen.2022.44486 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eFigure 1. Flowchart of INSPIRE Study Sample
eAppendix 1. CDC ME/CFS Symptom Screener–Short Form, Version 1.2
eTable 1. Operationalized Algorithm for the 2015 IOM ME/CFS Case Definition
eAppendix 2. List of Conditions Potentially Contributing to ME/CFS Symptoms Entered by Participants
eAppendix 3. Other Races Entered by Participants
eTable 2. Observed Distribution of Confounders and Covariates Between COVID-19 Groups
eFigure 2. Absolute Standardized Differences Between COVID-19 Groups
eFigure 3. Marginal Effects of Index COVID-19 Status on the ME/CFS Outcomes Based on Matched Sample
Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) Group
Data Sharing Statement