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Article https://doi.org/10.1038/s41467-025-56994-5
Prospective cohort study of fatigue before
and after SARS-CoV-2 infection in the
Netherlands
Anne J. Huiberts
1
, Siméon de Bruijn
1
, Stijn P. Andeweg
1
, Christina E. Hoeve
1
,
Maarten Schipper
2
,HesterE.deMelker
1
, Janneke HHM van de Wijgert
3
,
Susan van den Hof
1
, Cees C. van den Wijngaard
1
& Mirjam J. Knol
1
Fatigue is one of the most common persistent symptoms of SARS-CoV-2
infection. We aimed to assess fatigue during and after a SARS-CoV-2 infection
by age, sex, presence of a medical risk condition, SARS-CoV-2 variant and
vaccination status, accounting for pre-infection fatigue and compared with
uninfected individuals. We used data from an ongoing prospective cohort
study in the Netherlands (VASCO). We included 22,705 first infections repor-
ted between 12 July 2021 and 9 March 2024. Mean fatigue scores increased
during infection, declined rapidly in the first 90 days post-infection, but
remained elevated until at least 270 days for Delta and 120 days for Omicron
infections. Prevalence of severe fatigue was 18.5% before first infection. It
increased to 24.4% and 22.5% during acute infection and decreased to 21.2%
and 18.9% at 90 days after Delta and Omicron infection, respectively. The
prevalence among uninfected participants was lower than among matched
Delta-infected participants during the acute phase of the infection and 90 days
post-infection. For matched Omicron-infected individuals this was only
observed during the acute phase. We observed no differences in mean post- vs
pre-infection fatigue scores at 90-270 days post-infection by vaccination sta-
tus. The impact of SARS-CoV-2 infectionontheprevalenceofseverefatigue
was modest at population level, especially for Omicron.
The majority of individuals recover from an acute SARS-CoV-2 infec-
tion within a couple of weeks but some experience persisting
symptoms1,2. The WorldHealth Organizationuses the term Post-COVID
condition (PCC) when symptoms have persisted for at least 90 days1.
Fatigue is reported by a third to half of individuals with COVID-19 as
one of the symptoms that they experienced during the acute phase of
the infection2,3. It is also often one of the symptoms that lingers after
the acute phase2, and is one of the most common and debilitating
symptoms of PCC3–5. Reported PCC prevalences vary widely depend-
ing on the PCC definition and symptom assessment methods
employed, populations studied, timing of assessments, among other
factors4.
Older persons, females, and persons with pre-existing comor-
bidities have been reported to have a higher risk of persisting fatigue
after a SARS-CoV-2 infection5–7. COVID-19 disease severity5,7–9,SARS-
CoV-2 variant of concern10,11 and repeat infections11,12 have been asso-
ciated with post-infection fatigue and with PCC too, but results are
uncertain and/or inconsistent across studies6,13–16.Furthermore,
whereas research has shown that COVID-19 vaccination has provided
protection against severe disease and mortality, and to a lesser extent
Received: 28 August 2024
Accepted: 7 February 2025
Check for updates
1
Centre for Infectious Disease Control, National Institute for Public Health and Environment (RIVM), Bi lthoven, the Netherlands.
2
Department of Statistics, Data
Science and Modelling, National Institute for Public Health and Environment (RIVM), Bilthoven, the Netherlands.
3
Julius Center for Health Sciences and
Primary Care, University Medical Center Utrecht (UMCU), Utrecht, the Netherlands. e-mail: mirjam.knol@rivm.nl
Nature Communications | (2025) 16:1923 1
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against infection17,18, its protective effect against post-infection fatigue
and PCC, has not been conclusively established. Meta-analyzes suggest
a protective effect of vaccination19–21, but the included studies are of
variable quality and substantially heterogeneous in study designs,
study populations and measured outcomes22.
Estimating the frequency and severity of, and risk factors for, per-
sisting fatigue after a SARS-CoV-2 infection is challenging22,23.Studiesare
often cross-sectional in nature and onlyassessparticipantsafterSARS-
CoV-2 infection, while fatigue might have already been present before
the infection. Fatigue is common in the general population24 and might
be affected by seasonal effects. In addition, COVID-19 related restric-
tions during the pandemic may have affected fatigue levels, also in
individuals who never had COVID-19. Therefore, detailed information
about fatigue before and after SARS-CoV-2 infection, and in uninfected
individuals, is essential to provide better insight into the independent
effect of a SARS-CoV-2 infection on persistent fatigue.
In this prospective cohort study, we assessed fatigue during and
after a SARS-CoV-2 infection by age, sex, presence of a medical risk
condition, SARS-CoV-2 variant and vaccination status, taking into
account pre-infection fatigue scores alongside fatigue over time in
matched uninfected individuals.
Results
Study population
A total of 22,705 first infections between 12 July 2021 and 9 March 2024
with available pre- and post-infection scores on the fatigue severity
subscale of the Checklist Individual Strength or CIS-fatigue scores were
reported (Table 1). Most first infections (21,642, 95%) were attributed to
the Omicron variant. For these first infections, 25,246 pre-infection and
63,497 post-infection fatigue scores were available (Supplementary file,
Figure S1). Most participants had been booster vaccinated at the time of
infection (20,307, 89%). Additionally, 6414 repeat Omicron infections
with available pre-infection and post-infection CIS-fatigue scores were
reported of which the majority concerned a second infection (5488, 86%)
and were classified as post-Omicron BA.5 (6,120, 95%). Participants
reporting a repeat infection, compared to a first infection, were more
often below 60 years (55% vs 48%). During the period in which bivalent
booster vaccinations were available, 7,959 infections with pre- and post-
infection fatigue scores were available. The participants reporting these
infections often (4816; 61%) had received a bivalent booster vaccination
before infection. In total, 2,331 (10%) first infections, 988 (15%) repeat
infections, and 1141 (14%) infections during the bivalent vaccination
period were excluded from post- vs pre-infection CIS-fatigue score
analyzes because only one pre-infection score was available which was
0-14 days before the infection.
Fatigue among infected participants
First infections: pre-infection fatigue score. Overall unadjusted mean
fatiguescoreswerevisualizedinSupplementaryfile, Figure S2. The
proportion of participants reporting the maximum CIS-fatigue score
was small ( < 2%; Supplementary file, Table S1). Adjusted mean pre-
infection fatigue scores differed between subgroups (Supplementary
file, Figure S3) with significantly (t-test p< 0.001) higher means for
femalesvsmales(23.5(95%CI23.1–23.9) vs 20.9 (20.4–21.3)), 18–59
year-olds (24.3 (23.9–24.7) vs 60–85 years-old at 20.0 (19.6–20.4)) and
those with vs without a medical risk condition (24.5 (24.0–25.0) vs 19.8
(19.4–20.2)). Mean pre-infection scores also differed significantly
(p< 0.001) between unvaccinated participants (20.8; 20.2–21.5), pri-
mary vaccinated participants (23.4; 23.0–23.8) and booster vaccinated
participants (22.3; 21.9–22.7). Mean pre-infection scores did not differ
significantly by variant of infection with means of 22.0 (21.3–22.6) for
Delta infections and 22.4 (22.0–22.7) for Omicron infections (p=0.246).
First infections: post- vs pre-infection fatigue. The proportion of
participants with ≥6 points increase in CIS-fatigue scores compared to
pre-infection was largest in the first 30 days post-infection (Supple-
mentary file, Figure S4A). For Omicron infections the proportions of
participants with ≥6 points increase or decrease in CIS-fatigue scores
compared to pre-infection were similar from about 120 days post-
infection (about 20%). Unadjusted mean post- vs pre-infection CIS-
fatigue scores per 10-day time intervals since the infection showed a
large increase during the acute phase of the infection followed by a
steep decline in the first 90 days, and approaching zero (thus pre-
infection levels) after 150 days for Omicron infections and 270 days for
Delta infections (Supplementary file, Figure S5). Adjusted mean post-
vs pre-infection CIS-fatigue scores showed a similar pattern (Fig. 1).
Peak means of up to 8 points during acute infection were observed,
with higher peak means (p< 0.001) for 60-85 year-olds, those without
a medical risk condition, and for Delta infections (Supplementary file,
Table S2). Also, unvaccinated participants had a higher peak mean
compared to primary vaccinated (p= 0.008) and booster vaccinated
(p= 0.008) participants. Adjusted means showed a steep decline in the
first 90 days and were non-significantly different from zero after
120 days for Omicron infections and declined towards near zero but
remained significantly elevated up to 270 days for Delta infections.
Means were 2.5 (1.8–3.2), 1.6 (1.0–2.2) and 1.5 (0.7–2.3) at 90, 180 and
270 days after Delta infection and 0.5 (0.1–1.0), 0.1 (−0.4–0.5) and 0.4
(−0.1–0.9) after Omicron infection, which differed significantly at 90
Table 1 | Characteristics of participants reporting first and
repeat infections (n=23,591)
First
infections1
(n=22,705)
Repeat
infections2
(n= 6414)
First or repeat infec-
tions during bivalent
vaccination
program3(n=7959)
Age at baseline4
18–59 years 10970 (48.3%) 3496 (54.5%) 3438 (43.2%)
60–85 years 11735 (51.7%) 2918 (45.5%) 4521 (56.8%)
Sex
Female 14652 (64.5%) 4497 (70.1%) 5261 (66.1%)
Medical risk condition5
Yes 6502 (28.6%) 1660 (25.9%) 2434 (30.6%)
Variant of infection6
Delta 1063 (4.7%) - -
Omicron 21642 (95.3%) 6414 (100%) 7959 (100%)
BA.1/BA.2 11294 (49.7%) 0 (0%) 0 (0%)
BA.4/BA.5 6119 (27.0%) 294 (4.6%) 2061 (25.9%)
Post BA.5 4229 (18.6%) 6120 (95.4%) 5898 (74.1%)
Vaccination status prior to the reported infection
Unvaccinated 437 (1.9%) 72 (1.1%) 69 (0.9%)
Primary series 1961 (8.6%) 205 (3.2%) 187 (2.3%)
Booster 20307 (89.4%) 6137 (95.7%) 7703 (96.8%)
Acute symptoms
Symptomatic 21,337 (94.0%) 5597 (87.3%) 7229 (90.8%)
Asymptomatic 852 (3.8%) 412 (6.4%) 323 (4.1%)
Missing 516 (2.3%) 405 (6.3%) 407 (5.1%)
1First infections were reported between 12 July 2021 and 9 March 2024; pre- and post-infection
CIS-fatigue questionnaires were completed between 18 May 2021 and 7 April 2024. 2Repeat
infections were reported between13 August 2022 and 15 March2024; completedpre- and post-
infection CIS-fatigue questionnaireswere between 27July 2022 and 7 April2024. 3First or repeat
infections during thebivalent vaccination program were reported between29 September 2022
and 2 October 2023. 415 participants were excluded because age was missing. 5A medical risk
condition was present when a participant reported to have oneor more of the following con-
ditions: diabetes mellitus, lung disease or asthma, asplenia, cardiovascular disease, immune
deficiency, cancer, liver disease, neurological disease, renal disease, organ or bone marrow
transplantation. 6Determinedbased on the periodin which > 90% of the casesin the Netherlands
was caused by Delta (12 July 2021–19 December 2021) or Omicron (from 10 January 2022). The
Omicron period was subdivided into Omicron BA.1 and BA.2 (10 January 2022–5 June 2022),
Omicron BA.5 (6 June 2022–13 November 2022) and post-Omicron BA.5 (from 14 November
2022). In the latter period multipledifferent Omicron subvariants circulated in the Netherlands.
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 2
Content courtesy of Springer Nature, terms of use apply. Rights reserved
(p< 0.001), 180 days ((p<0.001)and270days(p= 0.003) (Table 2). At
90, 180 and 270 days post-infection, no significant differences in mean
post- vs pre-infection CIS-fatigue scores were present by age group or
vaccination status. In females, means were higher than in males at 90
(p = 0.004) and 180 days post-infection (p= 0.049), but differences
were small (0.6 (95%CI 0.2–1.0) and 0.4 (0.0–0.8), respectively).
When limiting the analysis to Omicron infections, adjusted mean
post- vs pre-infection CIS-fatigue scores during the acute phase of the
infection were lowest for Omicron BA.1/BA.2 infections (3.2; 2.7–3.7),
followed by Omicron BA.5 infections (5.2; 4.4–5.9) and highest for
post-Omicron BA.5 infections (7.1; 6.3–8.0) (p< 0.001). Means were
significantly higher for Omicron BA.5 infections (0.6; 0.2–1.1) than
Omicron BA.1/BA.2 (p= 0.001) and post-Omicron BA.5 (p=0.030) at
180 days post-infection but the differences were small (Supplementary
file, Figure S6). Among Omicron infections, means of 60–85-year-olds
were significantly higher at 90 (p=0.001) and 180 days (p= 0.016)
compared to 18–59-year-olds, but differences were small (0.3 and 0.2,
respectively). Differences in means at 90 to 270 days post-infection by
other covariables were comparable to the analysis that also included
Delta infections.
First infections: prevalence of severe fatigue. The estimated adjus-
ted prevalence of severe fatigue at 30 days before a Delta infection was
18.5% (16.5–20.7) (Table 2and Fig. 2). This increased to 24.4%
(22.1–27.0) during the acute phase of the infection, and then decreased
to 21.2% (18.9–23.6) at 90 days post-infection and 18.8% (16.5–21.3) at
180 days post-infection. The prevalence at 30 days before an Omicron
infection was 18.5% (17.5-19.6). This increased to 22.5% (21.4–23.6)
during the acute phase of the infection and decreased to 18.9%
(17.8–19.9) at 90 days and 18.6% (17.5–19.7) at 180 days post-infection.
Smaller numbers lead to lessprecise prevalence estimates at 270 days,
especially for Delta infections. Differences between Delta and Omicron
were notstatistically significant before infectio n (p=0.987),duringthe
acute phase of the infection (p=0.138) or at 90 (p= 0.057), 180
(p= 0.889) or 270 days post-infection (p=0.170).
Results of the subgroup analysis limited to symptomatic first
infections (21,337, 94%) were not substantially different from results of
the analysis among all first infections (Supplementary file, Figure S7).
Participants with asymptomatic Delta infection (76, 7.1%) showed a
mean post- vs-pre-infection CIS-fatigue score of 4 points during the
acute phase of the infection and this remained at about the same level
up to at least 270 days post-infection,while for asymptomatic Omicron
infections (776, 3.6%) the mean post-infection CIS-fatigue score was
not significantly different from the pre-infection score at any of the
timepoints (Supplementary file, Figure S8). The sensitivity analysis in
which fatigue scores after vaccination after infection were removed
showed similar results as the primary analyzes (Supplementary file,
Figure S9).
First and repeat omicron infections. Our second analysis assessing
first and repeat Omicron infections showed a significantly higher
adjusted mean post- vs pre-infection CIS-fatigue score during the acute
phase of the infection for first infections (5.6; 95%CI 4.9–6.2) com-
pared to repeat infections (4.1; 3.5–4.7) (p< 0.001) (Table 2and Sup-
plementary file, Figure S10). Differences in mean post- vs pre-infection
CIS-fatigue score between first and repeat infections at 90 days (1.0 vs
0.7), 180 days (0.1 vs 0.6) and 270 days (0.5 vs 0.5) were small and
mostly non-significant (p=0.245,p= 0.039 and p= 0.97, respectively).
Estimated prevalence of severe fatigue was higher before a first (20.3%;
19.2–21.4) than before a repeat infection (17.7%; 16.6–18.8) (p< 0.001);
this was also true during the acute phase of the infection (23.3%;
22.2–24.4 for first infections and 20.2%; 19.1–21.4 for repeat infections;
p< 0.001). Prevalence of severe fatigue decreased to 21.3% and 18.4%
for first and repeat infections at 90 days post-infection.Up to 270 days
post-infection, prevalence of severe fatigue remained significantly
lower for repeat versus first infections.
Infections during bivalent booster vaccination campaign.Ourthird
analysis among infections reported during the period when bivalent
booster vaccinations were available did not show significant
−2
−1
0
1
2
3
4
5
6
7
8
9
10
0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Post− vs pre−infection fatigue score
Age group 18−59 years
60−85 years
−2
−1
0
1
2
3
4
5
6
7
8
9
10
0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Post− vs pre−infection fatigue score
Sex Female
Male
−2
−1
0
1
2
3
4
5
6
7
8
9
10
0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Post− vs pre−infection fatigue score
Medical risk Without medical risk condition
With medical risk condition
−2
−1
0
1
2
3
4
5
6
7
8
9
10
0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Post− vs pre−infection fatigue score
Variant of infection Delta
Omicron
−2
−1
0
1
2
3
4
5
6
7
8
9
10
0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Post− vs pre−infection fatigue score
Vaccination status
Unvaccinated
Primary vaccinated
Booster vaccinated
Fig. 1 | Adjusted mean post- vs pre-infection CIS-fatigue scores with 95%CI over
time since first SARS-CoV-2 infection, by covariable. Each panel visualizes the
adjustedmean post- vs pre-infection CIS-fatigue scoreswith 95% CI over timesince
infection and colored by covariable level.Results are adjusted for the othershown
covariables and time since infectionis included as penalized spline. CIS = Checklist
Individual Strength; CI = Confidence Interval.
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 3
Content courtesy of Springer Nature, terms of use apply. Rights reserved
differences in adjusted mean post- vs pre-infection CIS-fatigue score
by bivalent vaccination status during the acute phase of the infection
or 90 to 270 days post-infection (Table 2). The estimated adjusted
prevalence of severe fatigue at 30 dayspre-infection was higher among
those who did not receive bivalent vaccination (19.5%; 95%CI
18.4–20.6) than among those who did receive bivalent vaccination
(16.3%; 15.2–17.3) (p< 0.001). The prevalence increased to 23.5% and
19.8% for non-vaccinated and vaccinated participants, respectively,
duringthe acute phase of the infection. Theprevalence then decreased
over timein both groups.The prevalenceremained significantly higher
among non-vaccinated compared to vaccinated participants up to at
least 270 days post infection with odds ratios remaining stable over
time. Furthermore, we observed small but significant differences in
mean post- vs pre-infection CIS-fatigue score between Omicron BA.5
and post-Omicron BA.5 infections at 90 days (p< 0.001), 180 days
(p< 0.001) and 270 days (p= 0.032) post-infection, with higher means
after Omicron BA.5 infections than post-Omicron BA.5 infections. The
differences in mean scores were, however, small (0.9, 1.1 and 0.6,
respectively).
Matched analysis
A total of 10,627 infected individuals could be matched with unin-
fected individuals (Supplementary file, Table S3). The majority of
infections were attributed to the Omicron variant (92%). For the mat-
ched analysis, 31,317 CIS-fatigue questionnaires were available for
uninfected participants and 41,376 for infected participants (Supple-
mentary file, Figure S11). Visualization of unadjusted mean CIS-fatigue
score dynamics over time indicated that means among uninfected
individuals remained stable over timewhile those of matched infected
individuals showed large variation over time (Supplementary file,
Figure S12). About 20% of the matched uninfected participants showed
≥6 points increase in CIS-fatigue scores, while a similar percentage
Table 2 | Adjusted mean post- vs pre-infection CIS-fatigue scores and prevalence of severe fatigue at 30 days pre-infection and
0, 90, 180, and 270 days post-infection
Post- vs pre-infection CIS-fatigue scores Prevalence of severe fatigue (CIS-fatigue score ≥35)
Days since
infection
Covariable Adjusted mean
(95% CI)
Difference (95% CI) P-value1Adjusted prevalence
(95% CI)
Odds ratio
(95% CI)
P-value1
Variant of first infection2
-30 Delta Reference 18.5% (16.5–20.7)
Omicron Reference - - 18.5% (17.5–19.6) 1.0 (0.9–1.2) 0.987
0 Delta 7.7 (6.7–8.6) 24.4% (22.1–27.0)
Omicron 5.1 (4.4–5.9) 2.5 (1.8–3.2) < 0.001 22.5% (21.4–23.6) 0.9 (0.8–1.0) 0.138
90 Delta 2.6 (2.0–3.2) 21.2% (18.9–23.6)
Omicron 0.5 (0.1–1.0) 2.0 (1.5–2.6) < 0.001 18.9% (17.8–19.9) 0.9 (0.7–1.0) 0.057
180 Delta 1.6 (1.0–2.2) 18.8% (16.5–21.3)
Omicron 0.1 (−0.4–0.5) 1.6 (1.1–2.1) < 0.001 18.6% (17.5–19.7) 1.0 (0.8–1.2) 0.889
270 Delta 1.5 (0.7–2.3) 17.5% (15.2–20.1)
Omicron 0.4 (−0.1−0.9) 1.1 (0.4–1.9) 0.003 19.4% (18.2–20.6) 1.1 (0.9–1.4) 0.170
First versus repeat infections3
−30 First Reference 20.3% (19.2–21.4)
Repeat Reference - - 17.7% (16.6–18.8) 0.8 (0.8-0.9) < 0.001
0 First 5.6 (4.9–6.2) 23.3% (22.2–24.4)
Repeat 4.1 (3.5–4.7) 1.4 (0.8–2.1) <0.001 20.2% (19.1–21.4) 0.8 (0.8-0.9) < 0.001
90 First 1.0 (0.6–1.3) 21.3% (20.2–22.4)
Repeat 0.7 (0.3–1.1) 0.2 (–0.2–0.6) 0.245 18.4% (17.4–19.5) 0.8 (0.8-0.9) < 0.001
180 First 0.1 (–0.3–0.6) 20.2% (19.1–21.3)
Repeat 0.6 (0.2–1.0) –0.5 (–0.9–0.0) 0.039 17.7% (16.6–18.9) 0.9 (0.8-0.9) < 0.001
270 First 0.5 (0.1–0.9) 20.4% (19.1–21.7)
Repeat 0.5 (0.0–1.0) 0.0 (–0.5–0.5) 0.972 18.2% (16.9–19.5) 0.9 (0.8-0.9) < 0.001
First and repeat infections by bivalent booster vaccination status4
−30 Non-vaccinated Reference 19.5% (18.4–20.6)
Vaccinated Reference - - 16.3% (15.2–17.3) 0.8 (0.7–0.9) < 0.001
0 Non-vaccinated 5.2 (4.6–5.7) 23.5% (22.3–24.7)
Vaccinated 5.0 (4.5–5.5) 0.2 (−0.3-0.7) 0.390 19.8% (18.7–20.9) 0.8 (0.7–0.9) < 0.001
90 Non-vaccinated 0.9 (0.6–1.3) 20.4% (19.3–21.5)
Vaccinated 0.9 (0.5–1.2) 0.1 (−0.3-0.4) 0.777 17.0% (16.1–18.1) 0.8 (0.7–0.9) < 0.001
180 Non-vaccinated 0.6 (0.3–0.9) 20.3% (19.1–21.5)
Vaccinated 0.7 (0.4–1.0) −0.1 (−0.5−0.2) 0.520 17.0% (15.9–18.1) 0.8 (0.7–0.9) < 0.001
270 Non-vaccinated 0.4 (0.0–0.8) 20.6% (19.2–22.1)
Vaccinated 0.7 (0.3–1.0) −0.3 (−0.8−0.2) 0.258 17.3% (16.0–18.6) 0.8 (0.7–0.9) < 0.001
1Two-sided t-test without adjustmentfor multiple comparisons. 2Estimates were adjusted for age group (18–59years, 60–85 years),sex (male, female), medical risk condition (yes, no),vaccination
status (unvaccinated,primary vaccinated, booster vaccinated),and time since infectionas penalized spline. 3Estimates were adjustedfor age group (18–59 years, 60–85 years), sex (male,female),
medical risk condition (yes, no), vaccination status (unvaccinated, primary vaccinated, booster vaccinated), variant of infection (Omicron BA.1/BA.2, Omicron BA.5, post-Omicron BA.5), and time
since infection as penalized spline. 4Estimateswere adjusted for age group (18-59 years, 60-85 years), sex (male, female), medical risk condition (yes, no), variant of infection (Omicron BA.1/BA.2,
Omicron BA.5, post-Omicron BA.5), infection number (first, repeat) and time since infection as penalized spline.
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 4
Content courtesy of Springer Nature, terms of use apply. Rights reserved
showed ≥6 points decrease (Supplementary file, Figure S4B). The
proportion of participants reporting the maximum CIS-fatigue score
was small ( < 2%; Supplementary file, Table S4). Comparable to our first
analysis, adjusted means also showed an increase in mean CIS-fatigue
scores during the acute phase of the infection compared to pre-
infection scores, with a higher peak and a later return to near pre-
infection levels for Delta infections compared to Omicron infections
(Supplementary file, Figure S13 and Table S2). Adjusted means of
matched uninfected participants showed a steady, slightly increasing
pattern over time. Adjusted mean post- vs pre-infection CIS-fatigue
scores after Delta infection were significantly elevated compared to
controls at 90, 180 and 270 days post-infection with differences of 1.9
(1.2–2.7), 1.3 (0.6–2.0) and 1.0 (0.1–1.9), respectively. After Omicron
infection, adjusted means only exceeded adjusted meansof controls at
90 days post-infection, with a difference of 0.5 (0.2–0.9). The pre-
valence of severe fatigue among matched uninfected participants
slowly increased over time from 14.4% at 30 days pre-infectionto 17.7%
at 270 days post-infection (Fig. 3). The prevalence was significantly
lower than among Delta infected participants during the acute phase
of the infection (14.9% vs 27.8%, p<0.001) and 90 dayspost-infection
(16.3% vs 23.3%, p< 0.001). For Omicron infections this was also
observed during the acute phase of the infection (14.9% vs 23.8%,
p< 0.001), but no difference was present at 90 days post-infection
(16.3% vs 15.8%, p=0.290).
Discussion
We performed a prospective study in which we included an uninfected
control group based on serology and in which we adjusted for pre-
infection symptoms. We found that fatigue scores increased during
SARS-CoV-2 infection, declined rapidly in the first 90 days after
infection, but remained elevated until at least 270 days for Delta
infections and 120 days for Omicron infections. At 90 to 180 days post-
infection, females showed higher post-infection fatigue scores com-
pared to pre-infection fatigue scores than males. The impact of SARS-
CoV-2 infection on the prevalence of severe fatigue was modest at
population level, especially for Omicron. We found prevalences of
severe fatigue of 21.2% and 18.9% at 90 days after a first Delta and
Omicron infection, respectively, while this prevalence was 18.5% before
infection. After 180 days, prevalences of severe fatigue were similar for
those with Delta and Omicron infections (18.8% and 18.6%at 180 days).
The prevalence of severe fatigue among uninfected participants
showed a slightly increasing pattern over time, suggesting no sub-
stantial impact of other factors fluctuatingovercalendartimeon
observed fatigue among infected persons. Despite somedifferences at
the time of acute infection, we did not observe an effect of primary or
booster vaccination or of bivalent booster vaccination (Autumn 2022
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Age group 18−59 years
60−85 years
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Sex Female
Male
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Sex Without medical risk condition
With medical risk condition
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Variant of infection Delta
Omicron
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Vaccination status
Unvaccinated
Primary vaccinated
Booster vaccinated
Fig. 2 | Adjusted prevalence of severe fatigue with 95% CI over time since first
SARS-CoV-2 infection, by covariable. Each panel visualizes the adjusted pre-
valence of severe fatigue with 95% CI over time since infection and colored by
covariable level. Results are adjusted for the other shown covariables and time
since infection is included as penalized spline. CI = Confidence Interval.
0
10
20
30
40
50
−90 −60 −30 0 30 60 90 120 150 180 210 240 270
Time (days since infection)
Prevalence severe fatigue
Variant of infection
Delta
Omicron
Uninfected
Fig. 3 | Adjusted prevalence of severe fatiguewith 95% CI before and after Delta
and Omicron SARS-CoV-2 infections and in matched uninfected participants.
Infected and uninfected participants were matched on month and year of pre-
infection CIS-fatigue assessment, the pre-infection CIS-fatigue score, age group
(18–59 years, 60–85 years), sex (male,female), medicalrisk condition (yes,no), and
vaccination status (unvaccinated, primary vaccinated, booster vaccinated). CIS =
Checklist Individual Strength; CI = Confidence Interval.
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 5
Content courtesy of Springer Nature, terms of use apply. Rights reserved
campaign) on long-term fatigue. Also, we did not observe substantial
differences in prevalence and trends in long-term fatigue between first
and repeat Omicron infections.
Only few studies on SARS-CoV-2-related fatigue or PCC included a
control group or were able to adjust for pre-infection symptoms.
National surveys conducted by the Office for National Statistics among
randomly sampled households from the United Kingdom (UK) popu-
lation included a matched control group25. They studied prevalence of
12 common symptoms, including (but not separately) fatigue, in the
pre-omicron period and reported that experiencing any of the symp-
toms was common among uninfected controls (3.4%). The prevalence
among infected participants was 9.4% at 4–8 weeks after infection and
decreased to 5.3%, 5.0%, 4.2% and 4.4% at 8–12, 12–16, 16–20 and
20–24 weeks after infection. The Lifelines COVID-19 cohort study, a
prospective, population-based observational cohort study of 76,422
participants in the Netherlands, corrected for pre-existing symptoms
before the onset of COVID-19, as well as symptom dynamics in a
matched control group26. They showed that fatigue of at least mod-
erate severity, i.e., score of ≥3 on a 5-point Likert scale, was present
among uninfected controls (3.7%). Also, the overall percentage of
participants with fatigue of at leastmoderate severity ( ≥3ona5-point
Likert scale) at 90–150 days after infection was 7.0%. This was higher
than the percentage of participantswith a substantial increase (1 point)
in fatigue severity to at least moderate severity (4.9%), thus when
taking into account severity before infection. Compared to the pre-
valence of symptoms in these two studies, pre-infection prevalence of
severe fatigue among our study population was considerably higher
(18.5%). However, we assessed fatigue as a standalone symptom (in
contrast to the British study), and we used CIS methodology that has
been validated for the Dutch population (in contrast to the Dutch
Lifelines study). The prevalence of the pre-infection severe CIS-fatigue
that we observed was comparable to the prevalence of severe CIS-
fatigue in the Dutch population (18%)24. The absolute increase in pre-
valence as a result of infection at 90 days post-infection (21.2% for
Delta infections) was comparable to what the other two studies
reported between controls and infected participants at 12–16 weeks
(3.4% vs 5.0%) and 90–150 days (3.7% vs 7.0%) after infection.
Both above mentioned studies also reported on risk factors for
long-term symptoms, or specifically long-term fatigue. The study from
the UK found a higher percentage of study participants reporting any
of 12 symptoms (including fatigue) 12–16 weeks after infection in
females (5.4% vs 4.5% in males), adults aged 50–69 years (5.8% vs 4.5%
in 25–34 year-olds), and people living with a pre-existing health con-
dition (7.4% vs 4.5% in those without). For fatigue as well as for other
symptoms, the Dutch Lifelines study reported longer persistence of
increased symptom severity (increase on a 5-point Likert scale)
90–150 days post-infection in females than males. Comparable to the
Dutch study, which also adjusted for fatigue present before infection,
we observed (small) differences in post- vs pre-infection fatigue score
at 90 and 180 days post-infection by sex but not by age group. That we
observed no differences by other determinants might thus be the
result of our adjustment for pre-infection scores.
The majority of the published studies included data from the first
one to two years of the pandemic and literature is limited on fatigue
after Omicron infections. A US study among community-based cases
described a lower proportion of participants reporting symptoms at
90 days after infection for Omicron versus pre-Omicron cases, but not
specifically for fatigue27. Yet, pre-Omicron infections included other
variants than Delta. A Dutch prospective study assessing prevalence of
severe fatigue, also using the CIS-fatigue score, reported significantly
higher prevalence at 3 months after Delta (25.6%) compared to Omi-
cron infections (22.6%)11. With the increasing level of immunity against
COVID-19 and the emergence of Omicron, the proportion of infections
being asymptomatic has increased28. A meta-analysis using data of five
studies reported 81% lower risk of fatigue after asymptomatic versus
symptomatic infection, with a pooled prevalence of fatigue of 9% after
asymptomatic and 22% after symptomatic infection29. They did not
study pre-infection prevalence of fatigue and attributed this 9% to the
infection. At a population level, we did not show significant differences
in fatigue compared with pre-infection levels up to 270 days post
asymptomatic Omicron infection, while differences post asympto-
matic Delta infection remained higher than pre-infection levels up to at
least 270 days. Therefore, a potentially larger proportion of Omicron
infections being asymptomatic is not expected to fully explain the
lower impact of Omicron infection on post-infection fatigue compared
to Delta infection. The emergence of Omicron and the increasing
proportion of infections being asymptomatic suggests the likelihood
of lingering post-infection fatigue or developing PCC when infected
might have decreased since the start of the pandemic.
Repeat infections are increasingly common30.AstudyfromtheUS
Department of Veterans Affairs showed that repeat infection con-
tributed to additional risk of fatigue (HR: 2.33; 95%CI 2.14–2.52) up to
six months post-infection31. However, this study estimated the risk of
fatigue after repeat infection compared to no repeat infection rather
than the risk after first versus repeat infection. Data from the UK
COVID-19 Infection Survey of 110,844 first and 11,244 second Omicron
infections showed lower prevalence of self-reported PCC at 12-20
weeks after second (2.4%) compared to first infection (4.0%)15.Among
those with self-reported PCC, prevalence of fatigue was slightly, non-
significantly higher after first (61.6%) than after second infection
(57.7%). A Dutch prospective study found higher prevalence of severe
fatigue on the CIS-fatigue subscale after Omicron repeat infection
(28%) than Omicron first infection (23%), but did not take into account
prevalence of severe fatigue pre-infection11. Pre-repeat infection mean
fatigue scores might have already been higher than first infection pre-
scores as a result of prior non-Omicron infections. Also, the study was
reliant on SARS-CoV-2 testing at testing facilities, of which accessibility
decreased during the Omicron period. Assuming the proportion
repeat infections increased with passing time, this might have resulted
in more severe repeat infections coming forward for testing. We did
not find substantial differences in CIS-fatigue scores from 90 days
post-infection between first and repeat infections when taking pre-
infection levels of fatigue into account. Results suggest there remains a
risk of long-term fatigue after repeat infection and this risk is com-
parable to the first infection.
Meta-analyzes suggest a protective effect of vaccination on the
risk of developing PCC, including fatigue19,20,32. However, included
studies are of variable quality and substantially heterogeneous in study
design, study period, study population and measured outcomes. A
study by the US Veterans Affairs reported a protective effect of vac-
cination on the risk of fatigue more than 30 days after infection for
hospitalized and ICU cases, but not for non-hospitalized cases33.
Another study from the US, among community-based cases rather
than severe COVID-19 cases, reported that vaccinated cases had lower
risk of fatigue and relative fatigue severity at 30 days after infection,
but not at 90 days after infection27. A Dutch prospective cohort study
among community cases reported severe fatigue to be less prevalent
at three months post-infection in cases with a booster (21.0%) com-
pared to the primary course cases (23.1%), but the difference was non-
significant11. A study from Israel analyzing electronic health records
found a reduced risk of dyspnea 30-90 days post-infection in vacci-
nated vs unvaccinated individuals, while risk of all other outcomes,
including weakness, were comparable34. In line with these results, we
did not find a difference by vaccination status in fatigue from 90 days
post-infection onwards among community, non-severe COVID-
19 cases.
Literature on the effect of bivalent vaccination on long-term
fatigue is scarce. A US longitudinal prospective survey-based study
among 505 symptomatic adult outpatients reported prevalence of
fatigue to be consistently lower among bivalent vaccinated
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 6
Content courtesy of Springer Nature, terms of use apply. Rights reserved
participants than those without bivalent vaccination through six
months post-infection, with 13.7% vs 23.7% at 6 months35. Their results
possibly differed from ours because they included more severe COVID-
19 cases and did not adjust for pre-infection levels of fatigue, which in
our population was higher among non-vaccinated. Our results imply
that new booster vaccination campaigns are not indicated to prevent
long-term fatigue after SARS-CoV-2 infection. However, new booster
vaccinations have shown benefit in preventing severe COVID-19 and
SARS-CoV-2 infections thereby indirectly also preventing long-term
fatigue36,37.
This study has several strengths. Fatigue was assessed using a
validated questionnaireat regular time points irrespective of infection.
Unlike many other studies, we took pre-infection levels of fatigue into
account to adjust for background prevalence of fatigue. We also
included uninfected participants as controls to take into account
changes in background prevalence over time caused by other factors.
Furthermore, our data shows that the VASCO study population
represents the Dutch general population well, asthe pre-infection CIS-
fatigue results, and pre-infection differences between age groups,
sexes, and medical risk groups, that we observed are comparable with
earlier results from population cohorts24,38–40.
This study also had limitations. Firstly, although the dropout rate
among VASCO participants is relatively low41, there might be selection
bias due to selective dropout. Secondly, fatigue is a complex multi-
faceted phenomenon and the CIS-fatigue questionnaire does not cover
all aspects of fatigue38,42,43. It was, for example, not designed to assess
post-exertional malaise38,42,44,aspecificsymptomdescribedby
patients with PCC. Fatigue is only one of the PCC symptoms and results
cannot be conveyed to other PCC symptoms, or PCC in general. Also,
despite somewhat reassuring results about the impact of long-term
fatigue after Omicron infection on the population level, we cannot
exclude that on the individual level people can still develop long-term
persisting fatigue after infection. Furthermore, the circulating SARS-
CoV-2 variant was defined by calendar time andis therefore likely to be
correlated with implementation of non-pharmaceutical interventions
over time; both may be independently associated with fatigue. We
observed an increasing pattern in fatigue over time among uninfected
participants with even somewhat higher fatigue than in Omi-
cron infected participants from 180 days after infection onwards, in
line with a similar observation in controls in another Dutch study on
post-COVID45. Although we cannot rule out selective drop-out of
controls as an explanation for these observations, an alternative
explanation might be increased circulation of other viruses after lifting
non-pharmaceutical COVID-19 measures in combination with viral
interference. Such viral interference may have led to temporal
increased immunity against other respiratory viruses in cases com-
pared to the uninfected controls46–48. Additionally, as not all indivi-
duals produce N-antibodies after SARS-CoV-2 infection and
N-antibody concentrations wane over time since infection49,50,a
small percentage of infections included as first infection might have
actually been a repeat infection. Also, a small percentage of the con-
trols might have actually been infected previously. Lastly, we were not
able to adjust for repeated measurements within persons in multi-
variate models. However, we do not expect a large influence on our
results, as the number of participants (23,591) is much larger than the
number of questionnaires per person (maximum of 6). Also, no dif-
ferences were observed with or without adjustment for repeated
measurements in univariate models.
In this well-controlled prospective cohort study increased levels
of mean fatigue scores after Omicron infection had resolved from
120 days post-infection, unlike after Delta infection. With the emer-
gence of Omicron and the increasing level of immunity against SARS-
CoV-2 globally, infections appear to have less impact on long-term
fatigue. We did not find evidence of an effect of vaccination on mean
long-term fatigue scores among infected individuals at population
level. However, as vaccination has shown benefitinpreventingsevere
COVID-19 and SARS-CoV-2 infections it thereby indirectly also pre-
vents long-term symptoms.
Methods
Study design and study population
The VAccine Study COvid-19 (VASCO) is a large ongoing prospective
cohort study with five-year follow-up in the Netherlands with the pri-
mary aim to estimate COVID-19 vaccine effectiveness against SARS-
CoV-2 infection41. Between 3 May 2021 and 15 December 2021, 45,552
community-dwelling adults aged 18–85 years were included. Partici-
pants had to be able to understand Dutch, as all study materials were
written in Dutch. Sociodemographic factors, health status, COVID-19
vaccination, COVID-19 related symptoms, and positive SARS-CoV-2
(self-)test data were collected using online questionnaires (every
month in year 1 and every three months thereafter). Participants could
also report any positive SARS-CoV-2 test in real time via the study
website or mobile phone application. To facilitate testing, self-tests
were provided to participants from May 2022 onwards, when com-
munity testing was scaled down. Data on self-reported fatigue was
collected every 3 months using a questionnaire validated in the Dutch
general population for this purpose (the fatigue severity subscale of
the Checklist Individual Strength or CIS)38,44. Additionally, participants
were asked to take a self-collected finger prick blood sample at home
at baseline and every 6 months during follow-up.
VASCO is conducted in accordance with the principles of the
Declaration of Helsinki and the study protocol was approved by the
not-for-profit independent Medical Ethics Committee of the Stichting
Beoordeling Ethiek Biomedisch Onderzoek (BEBO), Assen, the Nether-
lands (NL76815.056.21). Written informed consent was obtained from
all participants prior to enrollment into the study.
SARS-CoV-2 infection
First infections were defined as a first reported positive SARS-CoV-2
test without serological evidence of an unreported infection before
this positive test. An unreported infection was detected by the pre-
sence of antibodies against SARS-CoV-2 nucleocapsid protein (N-
antibodies) in finger prick blood samples. Samples were analyzed with
the Anti-SARS-CoV-2 assays on the Cobas e801 (Roche Diagnostics,
Mannheim, Germany) (see41 for an elaborate description). First infec-
tions were included if at least one CIS-fatigue score was available
1–90 days pre-infection, and at least one 0–300 days post-infection. If
participants experienced more than one infection, post-infection
questionnaires of the first infection had to be at least 14 days prior
to the subsequent infection. Repeat infections were defined as a
reported positive SARS-CoV-2 test at least 4 weeks after a preceding
reported or unreported infection. Repeat infections were included if
the infection and its preceding infection were considered to be caused
by Omicron(see below). Repeat infections were included if at least one
CIS-fatigue score was available 1–90 days pre-infection, and at least
one up to 300 days post-infection. Pre-infection questionnaires of
repeat infections had to be at least 180 days after the preceding
infection. Participants were considered uninfected up to 14 days prior
to their first reported positive testor up to their latest blood sample in
which no N-antibodies were detected. Participants without blood
sample results were excluded as controls. Participants were included
as uninfected controls if at least two CIS-fatigue scores were available
while remaining uninfected.
The virus variant of concern causing the infection was based on
the calendar period in which > 90% of the cases in the Netherlands
was caused by this variant51. Infections were considered to be caused
by either the Delta (12 July 2021–19 December 2021) or Omicron
(from 10 January 2022) variant. The Omicron period was subdivided
into Omicron BA.1 and BA.2 (10 January 2022–5 June 2022), Omicron
BA.5 (6 June 2022 –13 November 2022) and post-Omicron BA.5
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 7
Content courtesy of Springer Nature, terms of use apply. Rights reserved
(from 14 November 2022). In the latter period multiple different
Omicron subvariants circulated in the Netherlands. Infections dur-
ing the transition period from Delta to Omicron (n= 362) were
excluded from the analyzes. Infections were classified as sympto-
matic if symptoms were reported either in the questionnaire in
which the infection was reported, or in the questionnaire one month
after the reported infection. Infections were classified as asympto-
matic if participants reported to not have experienced any SARS-
CoV-2 related symptoms.
Outcomes
The CIS-fatigue severity subscale consists of 8 questions on a 7-point
Likert scale that assess the respondent’s experience of fatigue (Sup-
plementary file, Table S5). Scores range between 8 and 56 with higher
scores indicating more severe fatigue. The cut-off for severe fatigue is
≥3538. The CIS-fatigue has been well validated among patients with
chronic fatigue and in the working population38,42. The average CIS-
fatigue score in the general Dutch population is 2338.Wedefined the
post- vs pre-infection CIS-fatigue score as the difference between a
post-infection CIS-fatigue score (measured 0–300 days after positive
test) and the latest pre-infection CIS-fatigue score (14–90 days before
positive test). Infections for which only one pre-infection CIS-fatigue
score was available which was 0–14 days before infection (i.e., positive
test) were excluded from the analysis on post- vs pre-infection CIS-
fatigue scores.
Covariables
Covariables that were expected to be associated with the outcome
were measured. Demographic data were collected at baseline. A
medical risk condition was defined as present when a participant
reported to have one or more of the following conditions: diabetes
mellitus, lung disease or asthma, asplenia, cardiovascular disease,
immune deficiency, cancer, liver disease, neurological disease, renal
disease, organ or bone marrow transplantation.
Self-reported vaccination data were cross-checked through link-
age with the Dutch national COVID-19 vaccination Information and
Monitoring System (CIMS)52,53. The COVID-19 vaccination program in
the Netherlands started on 6 January 2021 and booster campaigns with
Comirnaty and Spikevax mRNA vaccines were initiated on 18 Novem-
ber 2021, 4 March 2022, 19 September 2023 and 2 October 2023 (see54
for detailed information). Vaccination status was categorized as
unvaccinated (no vaccination received), primary vaccination series
received (one doseof Jcovden 28+ days ago, or two doses of Vaxzevria,
Comirnaty or Spikevax 14+ days ago), or primary vaccination series
and one or multiple boosters received (7+ days ago). In the Nether-
lands, booster vaccinations administered between 19 September 2022
and 2 October 2023 were bivalent boosters, either original/Omicron
BA.1 or original/Omicron BA.4/BA.5.
Statistical analyzes
We explored unadjusted CIS-fatigue scores by describing mean post-
vs pre-infection CIS-fatigue scores by 10 days’intervals since infection
and by describing to what extent on the individual level participants
showed an increase or decrease of >=6 points in CIS-fatigue scores
post- vs pre-infection55,56. We performed a multivariable analysis on
three different outcomes: CIS-fatigue scores, post- vs pre-infection
CIS-fatigue scores, and severe fatigue prevalence. CIS-fatigue scores
and post- vs pre-infection CIS-fatigue scores were estimated as a
function of time since infection (penalized spline) using generalized
additive models (GAM) with Gaussian distributed outcome. The
probability of severe fatigue was estimated using a GAM with binomial
distributed outcome with a penalized spline for time since infection
and expressed as the estimated prevalence of severe fatigue. We were
not able to adjust for repeated measurements within persons in the
multivariate analyzes, but univariately no differences were observed
with or without adjustment for repeated measurements (Supplemen-
tary file, Figure S14).
The first analysis included all first infections and the covariables
dominant virus variant (Delta, Omicron), sex, age group, presence of a
medical risk condition and vaccination status. A second analysis
included both first and repeat Omicron infections. Included covari-
ables were the sameas in the first analysis with an additionalcovariable
indicating first or repeat infection. A third analysis was limited to
infections reported during the period in which bivalent booster vac-
cinations were available to estimate post-infection fatigue by bivalent
booster vaccination status. Other covariables were similar to the first
two models. All models are summarized in Supplementary file,
Table S6. The fitted models were used to estimate and visualize the
marginal means. Estimated marginal means are defined as equally
weighted means of predictions at specified margins and are often
called “adjusted means”57. Differences in estimated marginal means
(referred to as “adjusted means”throughout the manuscript) between
groups were determined and tested for significance using a t-test at 0,
90, 180, and 270 days post-infection. P-values < 0.05 were considered
statistically significant.
In the main analyzes, we assumed no effect of vaccination after
infection on fatigue scores. A sensitivity analysis was performed
excluding all questionnaires that were completed when a vaccina-
tion had been given after an infection to assess the possible effect of
this assumption. An additional sensitivity analysis was performed
stratifying first infections as symptomatic and asymptomatic infec-
tions. As a sensitivity analysis on the used smoothing terms, the
penalized spline was replaced by a cubic regression spline. This
resulted in only minor differences in results (Supplementary file,
Table S7 and Figures S15–S17).
Furthermore, to rule out any bias by seasonal patterns in fatigue
we additionally performed an analysis where we matched first infected
and uninfected individuals on month and year of pre-infection CIS-
fatigue assessment, the pre-infection CIS-fatigue score, age group, sex,
presence of a medical risk condition, and vaccination status. Any CIS-
fatigue questionnaire of an uninfected individual could be considered
a pre-infection CIS-fatigue assessment and could be matched to an
infected individual’s pre-infection CIS-fatigue assessment. After
matching, all subsequent CIS-fatigue assessments (at least one and
while remaining uninfected) were compared to the post-infection CIS-
fatigue assessments of infected individuals. The matching ratio was 1:1
and uninfected individuals could not be included more than once.
Post- vs pre-infection CIS-fatigue scores and prevalence of severe
fatigue were estimated as before by a function of time since first
infection by infection status.
All statistical analyzes were performed in statistical package R
version 4.3.3, using packages mgcv58,emmeans
59,andMatchIt
60.
Reporting summary
Further information on research design is available in the Nature
Portfolio Reporting Summary linked to this article.
Data availability
Anonymized data reported from this study can be obtained from the
corresponding author upon request, with a response timeframe of 3
weeks. The dataset may include individual data and a data dictionary
will be provided. Data requests should include a proposal for the
planned analyzes. Data transfer will require a signed data sharing
agreement.
Code availability
Analysis code is available upon request from the corresponding
author, with a response timeframe of 3 weeks.
Article https://doi.org/10.1038/s41467-025-56994-5
Nature Communications | (2025) 16:1923 8
Content courtesy of Springer Nature, terms of use apply. Rights reserved
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Acknowledgements
This work was funded by the Dutch Ministry of Health, Welfare and Sport.
Author contributions
All authors have read and approved the final manuscript. Hd.M.,
Jvd.W., Svd.H., Cvd.W., and M.K. designed the study. A.H., Sd.B., S.A.,
C.H., and M.S. contributed to data cleaning and/or data analysis. A.H.
drafted the manuscript. Sd.B., S.A., C.H., M.S., Hd.M., Jvd.W., Svd.H.,
Cvd.W., and M.K. critically reviewed the manuscript. M.K. is the
guarantor. The corresponding author attests that all listed authors
meet authorship criteria and that no others meeting the criteria
have been omitted.
Competing interests
The authors declare no competing interests.
Additional information
Supplementary information The online version contains
supplementary material available at
https://doi.org/10.1038/s41467-025-56994-5.
Correspondence and requests for materials should be addressed to
Mirjam J. Knol.
Peer review information Nature Communications thanks the anon-
ymous reviewer(s) for their contribution to the peer review of this work. A
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