Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

Dominik Menges; Tala Ballouz; Alexia Anagnostopoulos; Hélène E Aschmann; Anja Domenghino; Jan S Fehr; Milo A Puhan

doi:10.1371/journal.pone.0254523

. 2021 Jul 12;16(7):e0254523. doi: 10.1371/journal.pone.0254523

Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

Dominik Menges ^1,^#, Tala Ballouz ^1,^#, Alexia Anagnostopoulos ¹, Hélène E Aschmann ¹, Anja Domenghino ^1,², Jan S Fehr ¹, Milo A Puhan ^1,^*

Editor: Martin Chtolongo Simuunza³

PMCID: PMC8274847 PMID: 34252157

Abstract

Background

Longer-term consequences after SARS-CoV-2 infection are becoming an important burden to societies and healthcare systems. Data on post-COVID-19 syndrome in the general population are required for the timely planning of healthcare services and resources. The objective of this study was to assess the prevalence of impaired health status and physical and mental health symptoms among individuals at least six months after SARS-CoV-2 infection, and to characterize their healthcare utilization.

Methods

This population-based prospective cohort study (Zurich SARS-CoV-2 Cohort) enrolled 431 adults from the general population with polymerase chain reaction-confirmed SARS-CoV-2 infection reported to health authorities between 27 February 2020 and 05 August 2020 in the Canton of Zurich, Switzerland. We evaluated the proportion of individuals reporting not to have fully recovered since SARS-CoV-2 infection, and the proportion reporting fatigue (Fatigue Assessment Scale), dyspnea (mMRC dyspnea scale) or depression (DASS-21) at six to eight months after diagnosis. Furthermore, the proportion of individuals with at least one healthcare contact after their acute illness was evaluated. Multivariable logistic regression models were used to assess factors associated with these main outcomes.

Results

Symptoms were present in 385 (89%) participants at diagnosis and 81 (19%) were initially hospitalized. At six to eight months, 111 (26%) reported not having fully recovered. 233 (55%) participants reported symptoms of fatigue, 96 (25%) had at least grade 1 dyspnea, and 111 (26%) had DASS-21 scores indicating symptoms of depression. 170 (40%) participants reported at least one general practitioner visit related to COVID-19 after acute illness, and 10% (8/81) of initially hospitalized individuals were rehospitalized. Individuals that have not fully recovered or suffer from fatigue, dyspnea or depression were more likely to have further healthcare contacts. However, a third of individuals (37/111) that have not fully recovered did not seek further care.

Conclusions

In this population-based study, a relevant proportion of participants suffered from longer-term consequences after SARS-CoV-2 infection. With millions infected across the world, our findings emphasize the need for the timely planning of resources and patient-centered services for post-COVID-19 care.

Background

As of February 2021, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has resulted in more than 110 million infected cases and almost 2.5 million lives lost, at significant costs to healthcare systems and societies worldwide [1]. While initial public health responses focused on reducing the acute burden of coronavirus disease 2019 (COVID-19), a growing body of evidence indicates that SARS-CoV-2 infection can also result in longer-term physical and mental health consequences, which are of increasing concern for healthcare systems [2–4]. Such consequences lasting for longer than three months after infection are currently referred to as “post-COVID-19 syndrome” or “Long Covid” [4].

Few observational studies, predominantly conducted in patients hospitalized for acute COVID-19, have examined the persistence of symptoms and development of complications after SARS-CoV-2 infection beyond three months [5–9]. These studies reported that 15% up to 76% of infected individuals may experience persistent complaints for at least six months after acute illness [5, 9]. Further studies in hospitalized patients found that up to 20% of patients had to be rehospitalized [10], and up to 80% may require follow-up in primary care within 2 months of hospital discharge [11]. However, current evidence shows that post-COVID-19 syndrome does not only occur in individuals with severe disease requiring hospitalization or in older individuals with comorbidities, but also in young and previously healthy individuals with mild disease [3, 7, 9, 12, 13]. Data regarding the full burden of post-COVID-19 syndrome in the broader population of infected individuals is currently lacking. It is increasingly acknowledged that specific healthcare services and resources will be required to support the needs of individuals suffering from post-COVID-19 syndrome [2, 4, 14]. In response, several countries have started to set up specialized clinics [15, 16], and multiple patient support groups and networks for affected individuals have been formed to improve the general understanding of post-COVID-19 syndrome and identify needs for healthcare systems [14].

To successfully plan healthcare services and efficiently allocate public health resources, it is essential to determine the burden of longer-term consequences of SARS-CoV-2 infection and the needs of affected individuals. In this population-based study of SARS-CoV-2 infected individuals surveyed at least six months after diagnosis, we aimed to assess the longer-term physical and mental health impact of COVID-19 and the associated healthcare utilization. Thereby, we aimed to provide an evidence base for the planning of healthcare services for individuals suffering from post-COVID-19 syndrome.

Methods

Study design and participants

This study is based on data from participants of the Zurich SARS-CoV-2 Cohort study, a prospective, longitudinal cohort of polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infected individuals diagnosed between 27 February 2020 and 05 August 2020. We recruited study participants from within contact tracing at the Department of Health of the Canton of Zurich, Switzerland, based on mandatory laboratory reporting of all individuals diagnosed with SARS-CoV-2. We screened all SARS-CoV-2-positive individuals for whom contact information was available for eligibility. Eligibility criteria were being aged 18 years or older and able to follow study procedures, having sufficient knowledge of the German language, and residing in the Canton of Zurich. We enrolled participants into the study between 06 October 2020 and 26 January 2021, at a median of 7.2 months (range 5.9 to 10.3 months) after their diagnosis. The study was prospectively registered on the International Standard Randomised Controlled Trial Number registry (ISRCTN14990068) and was approved by the responsible ethics committee of the Canton of Zurich, Switzerland (Kantonale Ethik-Kommission Zürich; BASEC-Nr. 2020–01739). Electronic or written informed consent was obtained from all participants.

Data sources and outcome measurement

After enrolment, participants completed an electronic baseline questionnaire including questions on socio-demographics, medical comorbidities and risk factors, details on their acute SARS-CoV-2 infection, current health status and symptoms, healthcare contacts since diagnosis, and health-related quality of life. All data was collected through the Research Electronic Data Capture (REDCap) survey system.

Acute COVID-19 was defined as symptoms, consequences and healthcare contacts within four weeks of diagnosis. To capture the longer-term effects of SARS-CoV-2 infection, we evaluated whether participants who were symptomatic in the acute phase had fully recovered compared to their normal health status before infection using a four-category scale (i.e., feeling “recovered and symptom free”, “better but not fully recovered”, “neither better nor worse”, or “worse”). We assessed the presence and type of any new or ongoing symptoms since the acute illness using a comprehensive list of symptoms. Additionally, we reviewed and coded comments in free text fields for further new or ongoing symptoms not captured by the preconceived questionnaire.

We evaluated the presence of fatigue using the Fatigue Assessment Scale (FAS), using a score of 22 or more as a threshold for determining the presence of relevant fatigue [17]. To assess longer-term respiratory complications, we administered the modified Medical Research Council (mMRC) dyspnea scale [18]. We assessed the presence and severity of depression, anxiety and stress symptoms using the 21-item Depression, Anxiety and Stress Scale (DASS-21). We calculated category scores as the sum of subscale item scores multiplied by two and assigned corresponding severity levels according to official user guidance [19, 20]. We evaluated health-related quality of life using the EQ-5D-5L instrument and visual analogue scale (EQ VAS) [21, 22]. We used the Dutch value set for calculating EQ-5D-5L index scores, as no value set or guidance on the most appropriate value set for Switzerland is available, and we judged the population of the Netherlands to be relatively similar to the Swiss population.

We assessed healthcare service utilization by eliciting all healthcare contacts that participants have had since their acute illness. We asked participants about any general practitioner visits, medical hotline calls, and hospital admissions, as well as the main reason for each contact. To evaluate healthcare utilization specifically due to COVID-19, we restricted our analysis to healthcare contacts reported to be related to persistent or worsening symptoms, complications or new medical diagnoses related to COVID-19, or routine follow-up after COVID-19. In addition, we asked participants to report any medical conditions that have been newly diagnosed since their acute illness and whether the condition was evaluated as COVID-19-related by their physician or themselves.

Statistical analysis

We used descriptive statistics to analyze participant characteristics and outcomes of interest, and present results for the entire study population as well as stratified by age groups, sex, and hospitalization status.

We examined the data for missing values and report such where applicable. For responses to the FAS and DASS-21 instruments, we replaced missing data with the mean of the scores from the other available items. This was done for a maximum of two missing values for the FAS and for a maximum of one value for the DASS-21. We omitted FAS or DASS-21 responses with higher amounts of missing data from respective analyses. For the EQ-5D-5L, responses with invalid and missing data were omitted given the small amount of missing data (n = 4). No imputation was applied for other missing data.

We assessed associations of potential predictors with the primary outcomes using univariable and multivariable logistic regression models. We based model selection on clinical and epidemiological reasoning and the Akaike Information Criterion (AIC). We defined age group, sex and initial hospitalization as a priori covariables in the models based on the findings of other studies. We performed model selection separately for each outcome of interest by including variables that improved model fit based on AIC, with a difference of 2 points considered relevant. For the outcome of (non-)recovery, we restricted the analysis to initially symptomatic participants since the respective question was conditional on the presence of symptoms at time of infection. We report regression analysis results as odds ratios (OR) with corresponding 95% confidence interval (CI) and two-sided Wald-type statistical test. No p-value adjustment was applied. All analyses were performed using R version 4.0.2 [23].

In sensitivity analyses, we stratified results into time periods with limited testing (period before 25 June 2020, testing restricted to high-risk or severely symptomatic individuals) and increased testing (period after 25 June 2020, all symptomatic individuals could be tested). Additionally, we stratified results into time periods with limited and high public awareness of post-COVID-19 syndrome (questionnaire completion in periods before and after 09 November 2020, when major Swiss news outlets started reporting about post-COVID-19 syndrome). Last, we descriptively compared participants and nonparticipants for age, sex, presence of symptoms and hospitalization at infection to assess potential selection bias.

Results

Study population

Between 27 February 2020 and 05 August 2020, 4639 individuals were diagnosed with SARS-CoV-2 in the Canton of Zurich (Fig 1). Contact information was available for 2209 individuals, among which 1309 were eligible and invited to participate in our study. 442 individuals agreed to participate (participation rate 34%) and 431 were included in this analysis.

The median age of participants was 47 years (IQR 33 to 58 years) and 50% were female (Table 1). At least one chronic comorbidity was reported by 147 (34%) participants. During acute infection, 385 (89%) participants were symptomatic, with a median of 6 (IQR 3 to 8) symptoms reported. Symptoms were described as mild to moderate in 221 (51%) and severe to very severe in 164 participants (38%). Most commonly reported symptoms were fatigue (64%), fever (63%), cough (50%) and loss of taste or smell (49%). 81 (19%) participants were hospitalized due to COVID-19 for a median duration of 7 days (IQR 4 to 15 days).

Table 1. Characteristics of study participants enrolled in the Zurich SARS-CoV-2 cohort study.

Variable	N = 431
Age (years)
Median (IQR)	47 (33 to 58)
Age group (years)
18–39	164 (38.1%)
40–64	205 (47.6%)
≥65	62 (14.4%)
Sex
Female	214 (49.7%)
Male	217 (50.3%)
Time since diagnosis (days)
Median (IQR)	220 (181 to 232)
Initial symptom severity
Asymptomatic	46 (10.7%)
Mild to moderate	221 (51.3%)
Severe to very severe	164 (38.1%)
Initial symptom count
Median (IQR)	6 (3 to 8)
Missing	1
Initial symptom duration (days)
Median (IQR)	10 (6 to 20)
Missing	8
Hospitalization and ICU stay
Non-hospitalized	350 (81.2%)
Hospitalized without ICU stay	71 (16.5%)
Hospitalized with ICU stay	10 (2.3%)
Intubation during ICU stay (N = 10)	7 (70%)
Smoking status
Non-smoker	245 (57.2%)
Ex-smoker	122 (28.5%)
Smoker	61 (14.3%)
Missing	3
Body mass index (kg/m²)
Median (IQR)	24.8 (22.2 to 27.5)
Missing	8
Comorbidities
No comorbidity	283 (65.7%)
At least one comorbidity	147 (34.1%)
Missing	1
Education
None or mandatory school	20 (4.7%)
Vocational training or specialized baccalaureate	186 (43.5%)
Higher technical school or college	106 (24.8%)
University	116 (27.1%)
Missing	3
Employment
Employed	321 (75.4%)
Student	14 (3.3%)
Retired	62 (14.6%)
Unemployed or other	29 (6.8%)
Missing	5
Income (CHF)
<6’000	133 (32.8%)
6’000–12’000	156 (38.4%)
>12’000	117 (28.8%)
Missing	25

Open in a new tab

CHF = Swiss Francs, ICU = Intensive Care Unit, IQR = Interquartile Range.

Compared to individuals not participating in our study, participants in our study were younger on average, and a lower proportion was hospitalized for COVID-19 (19% compared to 24% of nonparticipants) (S1 Table).

Recovery and longer-term symptoms

Overall, 111 (26%) participants reported that they had not fully recovered at six to eight months after SARS-CoV-2 infection (Table 2). A higher percentage of female participants and initially hospitalized individuals reported not having fully recovered compared to males and non-hospitalized individuals, respectively. In multivariable analyses among initially symptomatic participants, we found evidence that severe to very severe symptoms during acute illness and the presence of comorbidities were associated with non-recovery (Fig 2 and S2 Table). Furthermore, females were less likely to have recovered compared to males, while there was no evidence for an association of age or initial hospitalization with non-recovery.

Table 2. Relative health status, fatigue, dyspnea, mental health, and health-related quality of life in study participants at six to eight months after SARS-CoV-2 infection.

Variable	Age group			Sex		Hospitalization		Overall, N = 431
Variable	18–39 years, N = 164	40–64 years, N = 205	≥65 years, N = 62	Female, N = 214	Male, N = 217	Non-hospitalized, N = 350	Hospitalized, N = 81	Overall, N = 431
Recovery
Recovered to normal health status	133 (81.1%)	140 (68.3%)	47 (75.8%)	148 (69.2%)	172 (79.3%)	268 (76.6%)	52 (64.2%)	320 (74.2%)
Not recovered to normal health status	31 (18.9%)	65 (31.7%)	15 (24.2%)	66 (30.8%)	45 (20.7%)	82 (23.4%)	29 (35.8%)	111 (25.8%)
Self-reported symptoms
No new or ongoing symptoms	120 (73.2%)	151 (73.7%)	54 (87.1%)	151 (70.6%)	174 (80.2%)	263 (75.1%)	62 (76.5%)	325 (75.4%)
Any new or ongoing symptoms	44 (26.8%)	54 (26.3%)	8 (12.9%)	63 (29.4%)	43 (19.8%)	87 (24.9%)	19 (23.5%)	106 (24.6%)
Recovery and symptoms
Recovered and symptom-free	105 (64.0%)	116 (56.6%)	44 (71.0%)	114 (53.3%)	151 (69.6%)	221 (63.1%)	44 (54.3%)	265 (61.5%)
Not recovered or experiencing symptoms	59 (36.0%)	89 (43.4%)	18 (29.0%)	100 (46.7%)	66 (30.4%)	129 (36.9%)	37 (45.7%)	166 (38.5%)
Fatigue (measured by FAS)
No fatigue	59 (36.0%)	100 (49.0%)	34 (58.6%)	86 (40.8%)	107 (49.8%)	154 (44.1%)	39 (50.6%)	193 (45.3%)
Fatigue	105 (64.0%)	104 (51.0%)	24 (41.4%)	125 (59.2%)	108 (50.2%)	195 (55.9%)	38 (49.4%)	233 (54.7%)
Missing	0	1	4	3	2	1	4	5
Dyspnea (measured by mMRC scale)
mMRC grade 0	126 (82.4%)	139 (74.3%)	34 (61.8%)	139 (70.9%)	160 (80.4%)	259 (81.4%)	40 (51.9%)	299 (75.7%)
mMRC grade 1	25 (16.3%)	39 (20.9%)	17 (30.9%)	48 (24.5%)	33 (16.6%)	53 (16.7%)	28 (36.4%)	81 (20.5%)
mMRC grade ≥2	2 (1.3%)	9 (4.8%)	4 (7.3%)	9 (4.6%)	6 (3.0%)	6 (1.9%)	9 (11.7%)	15 (3.8%)
Missing	11	18	7	18	18	32	4	36
Depression (measured by DASS-21)
No depression	123 (75.0%)	151 (74.0%)	43 (71.7%)	149 (70.6%)	168 (77.4%)	263 (75.4%)	54 (68.4%)	317 (74.1%)
Mild to moderate depression	33 (20.1%)	39 (19.1%)	13 (21.7%)	50 (23.7%)	35 (16.1%)	68 (19.5%)	17 (21.5%)	85 (19.9%)
Severe to very severe depression	8 (4.9%)	14 (6.9%)	4 (6.7%)	12 (5.7%)	14 (6.5%)	18 (5.2%)	8 (10.1%)	26 (6.1%)
Missing	0	1	2	3	0	1	2	3
Anxiety (measured by DASS-21)
No anxiety	114 (69.5%)	136 (67.3%)	41 (68.3%)	125 (59.5%)	166 (76.9%)	246 (70.7%)	45 (57.7%)	291 (68.3%)
Mild to moderate anxiety	38 (23.2%)	47 (23.3%)	18 (30.0%)	64 (30.5%)	39 (18.1%)	82 (23.6%)	21 (26.9%)	103 (24.2%)
Severe to very severe anxiety	12 (7.3%)	19 (9.4%)	1 (1.7%)	21 (10.0%)	11 (5.1%)	20 (5.7%)	12 (15.4%)	32 (7.5%)
Missing	0	3	2	4	1	2	3	5
Stress (measured by DASS-21)
No stress	134 (82.2%)	169 (82.8%)	54 (93.1%)	169 (80.1%)	188 (87.9%)	293 (84.2%)	64 (83.1%)	357 (84.0%)
Mild to moderate stress	21 (12.9%)	26 (12.7%)	4 (6.9%)	33 (15.6%)	18 (8.4%)	43 (12.4%)	8 (10.4%)	51 (12.0%)
Severe to very severe stress	8 (4.9%)	9 (4.4%)	0 (0.0%)	9 (4.3%)	8 (3.7%)	12 (3.4%)	5 (6.5%)	17 (4.0%)
Missing	1	1	4	3	3	2	4	6
EQ-5D mobility
No mobility problems	156 (95.1%)	180 (87.8%)	45 (75.0%)	188 (88.3%)	193 (89.4%)	324 (92.8%)	57 (71.2%)	381 (88.8%)
Mobility problems	8 (4.9%)	25 (12.2%)	15 (25.0%)	25 (11.7%)	23 (10.6%)	25 (7.2%)	23 (28.7%)	48 (11.2%)
Missing	0	0	2	1	1	1	1	2
EQ-5D self care
No problems with self-care	164 (100.0%)	203 (99.0%)	61 (100.0%)	212 (99.5%)	216 (99.5%)	348 (99.4%)	80 (100.0%)	428 (99.5%)
Problems with self-care	0 (0.0%)	2 (1.0%)	0 (0.0%)	1 (0.5%)	1 (0.5%)	2 (0.6%)	0 (0.0%)	2 (0.5%)
Missing	0	0	1	1	0	0	1	1
EQ-5D usual activities
No problems during usual activities	146 (89.0%)	184 (89.8%)	55 (90.2%)	184 (86.4%)	201 (92.6%)	322 (92.0%)	63 (78.8%)	385 (89.5%)
Problems during usual activities	18 (11.0%)	21 (10.2%)	6 (9.8%)	29 (13.6%)	16 (7.4%)	28 (8.0%)	17 (21.2%)	45 (10.5%)
Missing	0	0	1	1	0	0	1	1
EQ-5D pain & discomfort
No pain or discomfort present	124 (75.6%)	124 (61.1%)	29 (47.5%)	132 (62.3%)	145 (67.1%)	241 (69.3%)	36 (45.0%)	277 (64.7%)
Pain or discomfort present	40 (24.4%)	79 (38.9%)	32 (52.5%)	80 (37.7%)	71 (32.9%)	107 (30.7%)	44 (55.0%)	151 (35.3%)
Missing	0	2	1	2	1	2	1	3
EQ-5D anxiety & depression
No anxiety or depression present	107 (65.2%)	144 (70.2%)	46 (75.4%)	131 (61.5%)	166 (76.5%)	241 (68.9%)	56 (70.0%)	297 (69.1%)
Anxiety or depression present	57 (34.8%)	61 (29.8%)	15 (24.6%)	82 (38.5%)	51 (23.5%)	109 (31.1%)	24 (30.0%)	133 (30.9%)
Missing	0	0	1	1	0	0	1	1
EQ-5D-5L index score
Median (IQR)	1.00 (0.86 to 1.00)	0.89 (0.85 to 1.00)	0.89 (0.82 to 1.00)	0.89 (0.82 to 1.00)	1.00 (0.87 to 1.00)	1.00 (0.86 to 1.00)	0.88 (0.82 to 1.00)	0.89 (0.85 to 1.00)
Range	0.41 to 1.00	0.07 to 1.00	0.47 to 1.00	0.37 to 1.00	0.07 to 1.00	0.07 to 1.00	0.37 to 1.00	0.07 to 1.00
Missing	0	2	2	2	2	3	1	4
EQ VAS
Median (IQR)	85 (80 to 90)	85 (77 to 90)	80 (70 to 88)	85 (77 to 90)	85 (79 to 90)	85 (80 to 90)	80 (70 to 89)	85 (77 to 90)
Range	20 to 100	25 to 100	24 to 95	20 to 100	24 to 100	25 to 100	20 to 97	20 to 100
Missing	2	6	2	6	4	5	5	10

Open in a new tab

DASS-21 = Depression, Anxiety and Stress Score (21 items), EQ = EuroQol, FAS = Fatigue Assessment Scale, IQR = Interquartile Range, mMRC = modified Medical Research Council, VAS = Visual Analogue Scale.

Fig 2 — Panel (a) shows associations for not having fully recovered among initially symptomatic participants from multivariable logistic regression models adjusted for age, sex, initial hospitalization, symptom severity and presence of comorbidities. Panel (b) demonstrates associations for presence of fatigue (based on Fatigue Assessment Scale) from models adjusted for age, sex, and initial hospitalization. Panel (c) displays associations for presence of dyspnea (mMRC grade ≥1) from models adjusted for age, sex, initial hospitalization, smoking status, respiratory comorbidity and body mass index. Panel (d) shows associations for presence of depressive symptoms (based on DASS-21) from models adjusted for age, sex, initial hospitalization and symptom severity.

Similarly, 106 (25%) participants reported new or ongoing symptoms, with a higher percentage in females compared to males (Table 2). Fatigue (12%), cough (10%), sore throat (9%) and headache (9%) were the most frequently reported symptoms. Taste and smell disturbances were reported by 21 (5%) and rash by 3 (1%) individuals. Among non-recovered participants, 51 (46%) also described experiencing new or ongoing symptoms. Meanwhile, 55 (52%) participants reporting such symptoms stated not having fully recovered. Overall, 166 (39%) participants reported either not having fully recovered or having new or ongoing symptoms.

Fatigue

Among all participants, 233 (55%) participants having a score indicating fatigue, with a median FAS score of 22 (IQR 19 to 25) (Table 2). Younger individuals and female participants more frequently reported symptoms of fatigue compared to older age groups and males, respectively. In multivariable analyses, we found evidence that individuals aged 40 years or older were less likely to experience fatigue compared to 18–39 year-old participants (Fig 2 and S3 Table). However, we found no evidence for an association of sex, initial symptom severity or hospitalization with fatigue.

Dyspnea

A total of 96 (25%) participants reported to suffer from mMRC grade 1 dyspnea or higher (Table 2). We observed a higher percentage of grade ≥1 dyspnea among older age individuals, females, and initially hospitalized participants. In multivariable analyses, we found evidence for an association of grade ≥1 dyspnea with female sex, initial hospitalization, higher body mass index and presence of comorbidities, but not for initial symptom severity, smoking status or presence of a chronic respiratory condition (Fig 2 and S4 Table).

Depression, anxiety and stress

Overall, 111 (26%) participants reported symptoms of depression, 135 (32%) reported symptoms of anxiety, and 68 (16%) reported symptoms of stress (Table 2). Higher proportions of participants reported depressive symptoms in older age groups and among females. Similar contrasts were observed for symptoms of anxiety. Meanwhile, younger participants and females more often reported stress symptoms compared to older individuals and males, respectively. In multivariable analyses, we only found lower education status and being unemployed to be associated with symptoms of depression (Fig 2 and S5 Table).

Overlap of main outcomes and health-related quality of life

In total, 296 (69%) participants were categorized as non-recovered or experiencing fatigue, dyspnea or depression. Among these, 19 (6.4%) participants reported all four outcomes, while 130 (44%) suffered only from one of them (S1 Fig). Most frequent combinations were fatigue and depression (n = 94, 32%), fatigue and non-recovery (n = 78, 26%), and fatigue and mMRC grade ≥1 dyspnea (n = 68, 23%). Among all participants, 225 (53%) reported problems in at least one EQ-5D-5L dimension. Most frequently affected dimensions were pain/discomfort (n = 151, 39%) and anxiety/depression (n = 133, 31%) (Table 2).

Healthcare service utilization

A total of 170 (40%) participants reported having had at least one contact with the healthcare system for reasons related to COVID-19 (Table 3). Out of 81 initially hospitalized individuals, 8 (10%) were rehospitalized at least once due to persistent symptoms or COVID-19-related complications. 224 (52%) participants reported at least one general practitioner visit for any reason, and 150 (36%) had a general practitioner visit related to COVID-19. Among those, the median number of COVID-19-related general practitioner visits was 2 (IQR 1 to 3). Older and initially hospitalized individuals more frequently reported having seen a general practitioner. Additionally, 31 (7%) participants reported to have called a medical hotline for a reason related to COVID-19. Among non-recovered participants, 33% (37/111) did not report any further healthcare contacts (S6 Table).

Table 3. Healthcare use and complications at six to eight months after SARS-CoV-2 infection.

Variable	Age group			Sex		Hospitalization		Overall, N = 431
Variable	18–39 years, N = 164	40–64 years, N = 205	≥65 years, N = 62	Female, N = 214	Male, N = 217	Non-hospitalized, N = 350	Hospitalized, N = 81	Overall, N = 431
GP visit related to COVID-19	33 (20.4%)	85 (42.7%)	32 (53.3%)	80 (38.5%)	70 (32.9%)	100 (29.2%)	50 (63.3%)	150 (35.6%)
Missing	2	6	2	6	4	8	2	10
Number of GP visits related to COVID-19 ^a
1–2	22 (67%)	63 (75%)	21 (66%)	56 (71%)	50 (71%)	70 (71%)	36 (72%)	106 (71%)
3–5	10 (30%)	18 (21%)	8 (25%)	19 (24%)	17 (24%)	26 (26%)	10 (20%)	36 (24%)
≥6	1 (3%)	3 (4%)	3 (9%)	4 (5%)	3 (4%)	3 (3%)	4 (8%)	7 (5%)
Missing	0	1	0	1	0	1	0	1
Medical hotline contact related to COVID-19	16 (9.8%)	13 (6.3%)	2 (3.3%)	19 (8.9%)	12 (5.6%)	25 (7.2%)	6 (7.4%)	31 (7.2%)
Missing	0	0	1	0	1	1	0	1
Number of medical hotline contacts related to COVID-19^a
1–2	14 (88%)	7 (70%)	2 (100%)	15 (88%)	8 (73%)	18 (78%)	5 (100%)	23 (82%)
3–5	2 (12%)	3 (30%)	0 (0%)	2 (12%)	3 (27%)	5 (22%)	0 (0%)	5 (18%)
≥6	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)	0 (0%)
Missing	0	3	0	2	1	2	1	3
Rehospitalizations related to COVID-19 (N = 81)	1 (10%)	3 (7%)	4 (14%)	4 (11%)	4 (10%)	-	8 (10%)	8 (10%)
Number of rehospitalizations related to COVID-19 ^a
1	0 (0%)	3 (100%)	4 (100%)	3 (75%)	4 (100%)	-	7 (88%)	7 (88%)
2–3	1 (100%)	0 (0%)	0 (0%)	1 (25%)	0 (0%)	-	1 (12%)	1 (12%)
GP visit or rehospitalization related to COVID-19	34 (21.0%)	85 (42.7%)	33 (55.0%)	82 (39.4%)	70 (32.9%)	100 (29.2%)	52 (65.8%)	152 (36.1%)
Missing	2	6	2	6	4	8	2	10
Healthcare contact related to COVID-19	45 (27.8%)	92 (46.2%)	33 (55.0%)	94 (45.2%)	76 (35.7%)	116 (33.9%)	54 (68.4%)	170 (40.4%)
Missing	2	6	2	6	4	8	2	10
New medical diagnoses	12 (7.3%)	47 (22.9%)	18 (29.0%)	36 (16.8%)	41 (18.9%)	43 (12.3%)	34 (42.0%)	77 (17.9%)
Type of new medical diagnosis ^b
COVID-19 related complication (medically evaluated)	2 (17%)	17 (36%)	8 (44%)	12 (33%)	15 (37%)	12 (28%)	15 (44%)	27 (35%)
COVID-19 related complication (self-evaluated)	3 (25%)	6 (13%)	2 (11%)	6 (17%)	5 (12%)	7 (16%)	4 (12%)	11 (14%)
Non COVID-19 related diagnosis or unclear	7 (58%)	24 (51%)	8 (44%)	18 (50%)	21 (51%)	24 (56%)	15 (44%)	39 (51%)

Open in a new tab

DASS-21 = Depression, Anxiety and Stress Score (21 items), EQ = EuroQol, FAS = Fatigue Assessment Scale, GP = General Practitioner, IQR = Interquartile Range, mMRC = modified Medical Research Council, VAS = Visual Analogue Scale.

^a percentage within each category of healthcare contact (general practitioner visit, medical hotline call, rehospitalisation),

^b percentage among all medical diagnoses.

Since infection, 77 (18%) participants reported a new physician-diagnosed medical condition. 27 (35%) of these diagnoses were considered as related to COVID-19 by their physician (Table 3). Most frequently reported COVID-19-related conditions concerned the respiratory system (56%), followed by neuro-cognitive (30%), cardiovascular (11%), and skin disorders (11%). In multivariable analyses, we found evidence for an association between healthcare use and initial hospitalization, having experienced severe to very severe symptoms, female sex, and age ≥40 years (Fig 3 and S7 Table). Furthermore, not having fully recovered, grade ≥1 dyspnea, fatigue and symptoms of depression were associated with further healthcare contacts after acute COVID-19.

Fig 3 shows associations for having at least one further healthcare contact after initial COVID-19, based on multivariable logistic regression models adjusted for age, sex, initial hospitalization, and initial symptom severity.

Sensitivity analyses

Sensitivity analyses of the main outcomes and health-related quality of life stratified into time periods of limited and increased testing, as well as limited and increased awareness of post-COVID-19 syndrome yielded similar results across the different time periods (S8 Table).

Discussion

Main findings

In this population-based cohort study, we found that one in four people had not fully recovered within six to eight months after SARS-CoV-2 infection. More than half of the participants in our study reported symptoms of fatigue. One fourth suffered from some degree of dyspnea or had symptoms of depression. Overall, more than two thirds had not recovered or experienced fatigue, dyspnea or depression at the time of follow-up, with only partial overlap between these outcomes. While not all of these outcomes are necessarily attributable to COVID-19, our study showed that an important proportion of infected individuals may develop post-COVID-19 syndrome and that a wide range of healthcare services may be required to support their needs.

Two fifths of study participants had at least one further healthcare contact related to COVID-19 after acute illness. 36% of participants reported further general practitioner visits, 7% calls to medical hotlines, and 10% of initially hospitalized participants were rehospitalized at least once for persistent symptoms or complications. Compared to recovered individuals, those not having fully recovered were more than three times more likely to have further healthcare contacts. These findings highlight the considerable long-term impact that COVID-19 may have both on affected individuals and healthcare systems worldwide.

Evidence in context

The NICE guidelines defined post-COVID-19 syndrome as signs and symptoms developing during or after COVID-19 and continuing for more than 12 weeks [4]. Various studies have described a wide range of physical, cognitive and psychological symptoms persisting up to three months in individuals recovering from COVID-19 [24–33]. Yet, only few studies have assessed the persistence of symptoms beyond three months after infection [5–9].

Compared to studies that enrolled patients who were hospitalized for acute COVID-19 [5, 6], we observed a lower percentage of individuals suffering from longer-term symptoms. While these differences could be partly due to older participant populations and the restriction to hospitalized patients in their studies, we still observed lower proportions of non-recovery and persistent symptoms among hospitalized patients and older individuals. Meanwhile, a longitudinal cohort including 91% of participants with mild disease found persistent symptoms in 33% of outpatients and 31% of hospitalized patients [7]. These observations are more comparable to our findings. While differences in study populations and outcome measurement are likely to strongly affect the comparability of studies on post-COVID-19 syndrome, a relatively high prevalence of fatigue, dyspnea or exercise intolerance, and psychological symptoms have consistently been noted across studies [5–7, 12, 13].

Findings regarding longer-term sequalae are similar to those from prior coronavirus outbreaks [34], with 40% of severe acute respiratory syndrome (SARS) survivors reporting chronic fatigue up to four years after infection [35]. Similar chronic symptoms, in particular fatigue, have been also described in other viral (e.g. Ebola virus, Epstein-Barr virus, Dengue virus), and bacterial (e.g. Borrelia burgdorferi) infections [36–40]. Results of two recent studies comparing outcomes in individuals with COVID-19 to individuals with influenza are suggestive of a higher burden of a wide range of longer-term sequalae associated with COVID-19 [8, 41].

Only few studies so far have described the utilization of healthcare services after COVID-19 [10, 11, 42–44]. At two months, 9% to 20% of patients hospitalized for COVID-19 were found to require rehospitalization, with a higher risk in older individuals and those with comorbidities [10, 11, 42–44]. The observed rehospitalization rate in our study is broadly consistent with these estimates. One study found that 78% of hospitalized participants had seen a primary care physician after hospital discharge for any reason after 2 months [11]. In our study, 63% of hospitalized participants reported having had a general practitioner visit after hospital discharge. As noted above, differences in study populations likely affect the comparison of results across studies. Further studies based on standardized assessments of health outcomes and symptom complexes will be necessary to capture the full spectrum of post-COVID-19 syndrome.

Implications for healthcare resource planning

The management and care of individuals with post-COVID-19 syndrome is likely to become a substantial burden for healthcare systems worldwide. In Switzerland, 0.7 million individuals have been diagnosed with COVID-19 [45], and more than 2 million are estimated to have been infected according to current seroprevalence studies [46]. Based on our estimates, a relevant number of individuals suffering from longer-term complications has to be expected, which will require some degree of support or healthcare services. In our study, we provide more detailed data on healthcare utilization incurring due to COVID-19. More than a third of infected individuals in our study needed an average of two further primary care consultations related to protracted symptoms or complications. Interestingly, we also observed that despite an increased likelihood of seeking care in those who have not returned to their normal health status, approximately one third of these participants did not report any further healthcare contact after their acute illness. This indicates that there may be a relevant need among previously infected individuals for additional services specialized in the care of people with post-COVID-19 syndrome. Our study provides important evidence for understanding the longer-term complications and burden of COVID-19 on healthcare systems and for planning public health resources and tailored services accordingly.

Limitations

By relying on official records of all diagnosed infections, our study provided a unique opportunity to evaluate post-COVID-19 syndrome in the general population, based on the full spectrum of disease severity. However, our study also has several limitations.

First, most participants included in this analysis were diagnosed with COVID-19 during the first pandemic wave in Switzerland. The capacity constraints in SARS-CoV-2-testing up to June 2020 may have selected for a population with a higher risk of experiencing severe disease as only those qualified for testing at that time. Furthermore, increased awareness of post-COVID-19 syndrome may have resulted in more frequent reporting of health issues by participants. However, sensitivity analyses stratified by time periods of limited and increased testing and limited and increased awareness of post-COVID-19 syndrome did not show a relevant difference between the respective time periods (S8 Table).

Second, self-selection bias may have occurred if individuals who are more concerned with their health or experiencing symptoms related to post-COVID-19 syndrome were more likely to participate. This may have biased our results towards higher estimates of non-recovery and healthcare use than in the full population of infected individuals. Furthermore, the primarily electronic setup of our study may have influenced participation. On one side, this may have led to an underrepresentation of older individuals and those with difficulties using the electronic platform, as well as those with severe impairments due to post-COVID-19 syndrome or other conditions. We undertook strong efforts to include such individuals by establishing repeated contacts via phone prior to enrolment and encouraging the support by relatives for electronic surveys and alternatively offering phone interviews. In our study, the proportion of older individuals and individuals initially hospitalized for COVID-19 was lower in our study compared to nonparticipants (S1 Table). This may have biased the results towards lower estimates of non-recovery and healthcare use. On the other side, the digital nature of the follow-up may have facilitated the recruitment of participants who prefer not to present for in-person study visits (e.g., for convenience or health and mobility issues) [47]. Compared to studies relying on study site visits, the electronic setup may thus have increased the diversity of the study population. Overall, it is thus difficult to estimate the magnitude and direction of potential biases arising from participant selection. Nevertheless, we also consider the population-based approach a strength of our study.

Third, we did not have a baseline (pre-COVID-19) assessment of participants’ physical and mental health. Thus, it is impossible to distinguish the effects of COVID-19 from pre-existing conditions. The interpretation of our findings regarding depression and anxiety is further limited by the psychological burden that the pandemic may impose in general [48, 49]. While we tried to compare our results with estimates from the general population, applicable comparison data was not available. Other studies investigating longer-term sequelae after SARS-CoV-2 infection found a relevant excess risk for longer-term symptoms among infected individuals compared to SARS-CoV-2-negative control groups [9, 50]. Further research is required to gain better insights into the disease and healthcare burden attributable to SARS-CoV-2 infection.

Last, we did not evaluate the use of specialized medical (e.g., psychological/psychiatric care) or diagnostic services in our assessment. Thus, the true extent of healthcare service utilization may be underestimated. The unavailability of targeted post-COVID-19 care programs in Switzerland at the time of enrolment may have led to an underestimation of the healthcare demand to be expected once such programs become available. Additionally, it is important to consider case detection rates and population subgroups infected when estimating the impact of COVID-19 on healthcare systems. In contexts with limited testing and detection of infected individuals, the need for specialized healthcare services may be underestimated without adjustment for underdetection. Furthermore, the spread of SARS-CoV-2 likely varied across countries regarding which population groups were primarily affected, which may also influence the expected burden of post-COVID-19 syndrome on healthcare systems in other contexts.

Conclusion

Our population-based cohort study showed that a considerable proportion of SARS-CoV-2 infected individuals experience longer-term consequences and have a relevant demand for healthcare services. A wide range of services and patient-centered, integrative approaches will be required to support the recovery of these individuals. It is thus crucial to timely allocate resources and plan healthcare services to respond to the needs of those suffering from post-COVID-19 syndrome.

Supporting information

S1 Table. Comparison of population characteristics of participants of the Zurich SARS-CoV-2 Cohort study and individuals not participating in the study.

(DOCX)

Click here for additional data file.^{(15.8KB, docx)}

S2 Table. Results from univariable and multivariable logistic regression models for the outcome of not having fully recovered at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(18.8KB, docx)}

S3 Table. Results from univariable and multivariable logistic regression models for the outcome of fatigue at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(19.1KB, docx)}

S4 Table. Results from univariable and multivariable logistic regression models for the outcome of mMRC dyspnea grade ≥1 at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(19.6KB, docx)}

S5 Table. Results from univariable and multivariable logistic regression models for the outcome of depression at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(21.5KB, docx)}

S6 Table. Overlap of participants not having recovered or experiencing fatigue, dyspnea, or depression and healthcare use at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(16.3KB, docx)}

S7 Table. Results from univariable and multivariable logistic regression models for the outcome of having at least one further healthcare contact (defined as rehospitalization, general practitioner visit or medical hotline call) related to COVID-19 within six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(21.6KB, docx)}

S8 Table. Sensitivity analysis of relative health status, fatigue, dyspnea, mental health, and health-related quality of life in study participants at six to eight months after SARS-CoV-2 infection, stratified into time periods of limited and increased testing for SARS-CoV-2, as well as with limited and increased awareness of post-COVID-19 syndrome.

(DOCX)

Click here for additional data file.^{(24.2KB, docx)}

S1 Fig. Venn diagram of the overlap of participants that have not fully recovered or are experiencing fatigue, dyspnea or depression at six to eight months after SARS-CoV-2 infection (total N = 296).

(DOCX)

Click here for additional data file.^{(202.5KB, docx)}

S1 File. Original de-identified dataset underlying the analyses included in the study.

(XLSX)

Click here for additional data file.^{(82.8KB, xlsx)}

Acknowledgments

We would like to thank the study administration staff and the staff of the Corona Center of the University of Zurich for their excellent work and dedication to this study. Furthermore, we thank the Department of Health of the Canton of Zurich for their support and collaboration in realizing the study. And last, we thank all the study participants for their valuable time and commitment to the Zurich SARS-CoV-2 Cohort.

Data Availability

All relevant data are within the manuscript and its Supporting information files. Exact participant age and stratification variables used for sensitivity analysis cannot be shared publicly to ensure anonymity of study participants.

Funding Statement

The Zurich SARS-CoV-2 Cohort study is part of the Corona Immunitas research program, coordinated by the Swiss School of Public Health (SSPH+) and funded through SSPH+ fundraising, including funding by the Swiss Federal Office of Public Health, the Cantons of Switzerland (Basel, Vaud and Zurich), private funders (ethical guidelines for funding stated by SSPH+ were respected) and institutional funds of the participating universities. Additional funding specific to this study was provided by the Department of Health of the Canton of Zurich and the University of Zurich Foundation. Study funders had no role in study design, data collection and analysis, interpretation, decision to publish or preparation of this manuscript.

References

1.World Health Organization (WHO). Coronavirus Disease (COVID-19) Situation Reports: Weekly Epidemiological Update 23 February 2021. [cited 25 Feb 2021]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports
2.Greenhalgh T, Knight M, A’Court C, Buxton M, Husain L. Management of post-acute covid-19 in primary care. BMJ. 2020;370: m3026. doi: 10.1136/bmj.m3026 [DOI] [PubMed] [Google Scholar]
3.National Institute for Health Research (NIHR). Living with Covid19. 15 Oct 2020. [cited 25 Jan 2021]. [Google Scholar]
4.National Institute for Health and Care Excellence (NICE). COVID-19 rapid guideline: managing the long-term effects of COVID-19. NICE; 2020. [cited 19 Jan 2021]. https://www.nice.org.uk/guidance/ng188 [PubMed] [Google Scholar]
5.Huang C, Huang L, Wang Y, Li X, Ren L, Gu X, et al. 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. Lancet. 2021;397: 220–232. doi: 10.1016/S0140-6736(20)32656-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Bellan M, Soddu D, Balbo PE, Baricich A, Zeppegno P, Avanzi GC, et al. Respiratory and Psychophysical Sequelae Among Patients With COVID-19 Four Months After Hospital Discharge. JAMA Netw Open. 2021;4: e2036142. doi: 10.1001/jamanetworkopen.2020.36142 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Logue JK, Franko NM, McCulloch DJ, McDonald D, Magedson A, Wolf CR, et al. Sequelae in Adults at 6 Months After COVID-19 Infection. JAMA Netw Open. 2021;4: e210830. doi: 10.1001/jamanetworkopen.2021.0830 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Taquet M, Geddes JR, Husain M, Luciano S, Harrison PJ. 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. The Lancet Psychiatry. 2021;8: 416–427. doi: 10.1016/S2215-0366(21)00084-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Havervall S, Rosell A, Phillipson M, Mangsbo SM, Nilsson P, Hober S, et al. Symptoms and Functional Impairment Assessed 8 Months After Mild COVID-19 Among Health Care Workers. JAMA. 2021;325: 2015. doi: 10.1001/jama.2021.5612 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Donnelly JP, Wang XQ, Iwashyna TJ, Prescott HC. Readmission and Death After Initial Hospital Discharge Among Patients With COVID-19 in a Large Multihospital System. JAMA. 2021;325: 304. doi: 10.1001/jama.2020.21465 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Chopra V, Flanders SA, O’Malley M, Malani AN, Prescott HC. Sixty-Day Outcomes Among Patients Hospitalized With COVID-19. Ann Intern Med. 2020; M20-5661. doi: 10.7326/M20-5661 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Davis HE, Assaf GS, McCorkell L, Wei H, Low RJ, Re’em Y, et al. Characterizing Long COVID in an International Cohort: 7 Months of Symptoms and Their Impact. medRxiv. 2020; 2020.12.24.20248802. doi: 10.1101/2020.12.24.20248802 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Sudre CH, Murray B, Varsavsky T, Graham MS, Penfold RS, Bowyer RC, et al. Attributes and predictors of long COVID. Nat Med. 2021;27: 626–631. doi: 10.1038/s41591-021-01292-y [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Norton A, Olliaro P, Sigfrid L, Carson G, Paparella G, Hastie C, et al. Long COVID: tackling a multifaceted condition requires a multidisciplinary approach. The Lancet Infectious Diseases. 2021; doi: 10.1016/S1473-3099(21)00043-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.National Health Service (NHS) England. Long COVID patients to get help at more than 60 clinics. [cited 25 Feb 2021]. https://www.england.nhs.uk/2020/12/long-covid-patients-to-get-help-at-more-than-60-clinics/
16.Center for Disease Control and Prevention (CDC). Coronavirus Disease 2019 (COVID-19). In: Centers for Disease Control and Prevention [Internet]. 11 Feb 2020 [cited 18 Mar 2020]. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-criteria.html
17.Michielsen HJ, De Vries J, Van Heck GL. Psychometric qualities of a brief self-rated fatigue measure: The Fatigue Assessment Scale. Journal of Psychosomatic Research. 2003;54: 345–352. doi: 10.1016/s0022-3999(02)00392-6 [DOI] [PubMed] [Google Scholar]
18.Mahler DA, Wells CK. Evaluation of Clinical Methods for Rating Dyspnea. Chest. 1988;93: 580–586. doi: 10.1378/chest.93.3.580 [DOI] [PubMed] [Google Scholar]
19.Depression Anxiety Stress Scales (DASS). [cited 25 Feb 2021]. http://www2.psy.unsw.edu.au/dass/
20.Lovibond SH, Lovibond PF, Psychology Foundation of Australia. Manual for the depression anxiety stress scales. Sydney, N.S.W.: Psychology Foundation of Australia; 1995.
21.Herdman M, Gudex C, Lloyd A, Janssen MF, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20: 1727–1736. doi: 10.1007/s11136-011-9903-x [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Devlin N, Parkin D, Janssen B. An Introduction to EQ-5D Instruments and Their Applications. In: Devlin N, Parkin D, Janssen B, editors. Methods for Analysing and Reporting EQ-5D Data. Cham: Springer International Publishing; 2020. pp. 1–22. doi: 10.1007/978-3-030-47622-9_1 [DOI] [PubMed] [Google Scholar]
23.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. 2017. https://www.R-project.org/ [Google Scholar]
24.Carfì A, Bernabei R, Landi F, for the Gemelli Against COVID-19 Post-Acute Care Study Group. Persistent Symptoms in Patients After Acute COVID-19. JAMA. 2020;324: 603. doi: 10.1001/jama.2020.12603 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.Carvalho-Schneider C, Laurent E, Lemaignen A, Beaufils E, Bourbao-Tournois C, Laribi S, et al. Follow-up of adults with noncritical COVID-19 two months after symptom onset. Clin Microbiol Infect. 2021;27: 258–263. doi: 10.1016/j.cmi.2020.09.052 [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Garrigues E, Janvier P, Kherabi Y, Bot AL, Hamon A, Gouze H, et al. Post-discharge persistent symptoms and health-related quality of life after hospitalization for COVID-19. Journal of Infection. 2020;81: e4–e6. doi: 10.1016/j.jinf.2020.08.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Goërtz YMJ, Van Herck M, Delbressine JM, Vaes AW, Meys R, Machado FVC, et al. Persistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome? ERJ Open Res. 2020;6: 00542–02020. doi: 10.1183/23120541.00542-2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Halpin SJ, McIvor C, Whyatt G, Adams A, Harvey O, McLean L, et al. Postdischarge symptoms and rehabilitation needs in survivors of COVID-19 infection: A cross-sectional evaluation. Journal of Medical Virology. 2021;93: 1013–1022. doi: 10.1002/jmv.26368 [DOI] [PubMed] [Google Scholar]
29.Mandal S, Barnett J, Brill SE, Brown JS, Denneny EK, Hare SS, et al. ‘Long-COVID’: a cross-sectional study of persisting symptoms, biomarker and imaging abnormalities following hospitalisation for COVID-19. Thorax. 2021;76: 396–398. doi: 10.1136/thoraxjnl-2020-215818 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Taquet M, Luciano S, Geddes JR, Harrison PJ. Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA. Lancet Psychiatry. 2021;8: 130–140. doi: 10.1016/S2215-0366(20)30462-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Townsend L, Dyer AH, Jones K, Dunne J, Mooney A, Gaffney F, et al. Persistent fatigue following SARS-CoV-2 infection is common and independent of severity of initial infection. PLOS ONE. 2020;15: e0240784. doi: 10.1371/journal.pone.0240784 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Wong AW, Shah AS, Johnston JC, Carlsten C, Ryerson CJ. Patient-reported outcome measures after COVID-19: a prospective cohort study. Eur Respir J. 2020;56. doi: 10.1183/13993003.03276-2020 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Xiong Q, Xu M, Li J, Liu Y, Zhang J, Xu Y, et al. Clinical sequelae of COVID-19 survivors in Wuhan, China: a single-centre longitudinal study. Clinical Microbiology and Infection. 2021;27: 89–95. doi: 10.1016/j.cmi.2020.09.023 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Moldofsky H, Patcai J. Chronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study. BMC Neurol. 2011;11: 37. doi: 10.1186/1471-2377-11-37 [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Lam MH-B. Mental Morbidities and Chronic Fatigue in Severe Acute Respiratory Syndrome Survivors: Long-term Follow-up. Arch Intern Med. 2009;169: 2142. doi: 10.1001/archinternmed.2009.384 [DOI] [PubMed] [Google Scholar]
36.Jones JF, Ray CG, Minnich LL, Hicks MJ, Kibler R, Lucas DO. Evidence for Active Epstein-Barr Virus Infection in Patients with Persistent, Unexplained Illnesses: Elevated Anti-Early Antigen Antibodies. Ann Intern Med. 1985;102: 1–7. doi: 10.7326/0003-4819-102-1- [DOI] [PubMed] [Google Scholar]
37.Straus SE, Tosato G, Armstrong G, Lawley T, Preble OT, Henle W, et al. Persisting Illness and Fatigue in Adults with Evidence of Epstein-Barr Virus Infection. Ann Intern Med. 1985;102: 7–16. doi: 10.7326/0003-4819-102-1-7 [DOI] [PubMed] [Google Scholar]
38.Seet RCS, Quek AML, Lim ECH. Post-infectious fatigue syndrome in dengue infection. Journal of Clinical Virology. 2007;38: 1–6. doi: 10.1016/j.jcv.2006.10.011 [DOI] [PubMed] [Google Scholar]
39.Hickie I, Davenport T, Wakefield D, Vollmer-Conna U, Cameron B, Vernon SD, et al. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ. 2006;333: 575. doi: 10.1136/bmj.38933.585764.AE [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Islam MF, Cotler J, Jason LA. Post-viral fatigue and COVID-19: lessons from past epidemics. Fatigue: Biomedicine, Health & Behavior. 2020;8: 61–69. doi: 10.1080/21641846.2020.1778227 [DOI] [Google Scholar]
41.Al-Aly Z, Xie Y, Bowe B. High-dimensional characterization of post-acute sequelae of COVID-19. Nature. 2021;594: 259–264. doi: 10.1038/s41586-021-03553-9 [DOI] [PubMed] [Google Scholar]
42.Bowles KH, McDonald M, Barrón Y, Kennedy E, O’Connor M, Mikkelsen M. Surviving COVID-19 After Hospital Discharge: Symptom, Functional, and Adverse Outcomes of Home Health Recipients. Ann Intern Med. 2020; M20-5206. doi: 10.7326/M20-5206 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Lavery AM, Preston LE, Ko JY, Chevinsky JR, DeSisto CL, Pennington AF, et al. Characteristics of Hospitalized COVID-19 Patients Discharged and Experiencing Same-Hospital Readmission—United States, March–August 2020. MMWR Morb Mortal Wkly Rep. 2020;69: 1695–1699. doi: 10.15585/mmwr.mm6945e2 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.McCarthy CP, Murphy S, Jones-O’Connor M, Olshan DS, Khambhati JR, Rehman S, et al. Early clinical and sociodemographic experience with patients hospitalized with COVID-19 at a large American healthcare system. EClinicalMedicine. 2020;26: 100504. doi: 10.1016/j.eclinm.2020.100504 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Swiss Federal Office of Public Health (FOPH). COVID-19 Switzerland: Coronavirus Dashboard. [cited 6 Jun 2021]. https://www.covid19.admin.ch/en/overview
46.Stringhini S, Zaballa M-E, Perez-Saez J, Pullen N, de Mestral C, Picazio A, et al. Seroprevalence of anti-SARS-CoV-2 antibodies after the second pandemic peak. Lancet Infect Dis. 2021; doi: 10.1016/S1473-3099(21)00054-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Puhan MA, Steinemann N, Kamm CP, Müller S, Kuhle J, Kurmann R, et al. A digitally facilitated citizen-science driven approach accelerates participant recruitment and increases study population diversity. Swiss Medical Weekly. 2018;148. doi: 10.4414/smw.2018.14623 [DOI] [PubMed] [Google Scholar]
48.Vindegaard N, Benros ME. COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain, Behavior, and Immunity. 2020;89: 531–542. doi: 10.1016/j.bbi.2020.05.048 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.de Quervain D, Aerni A, Amini E, Bentz D, Coynel D, Freytag V, et al. The Swiss Corona Stress Study: second pandemic wave, November 2020. OSF Preprints; 2020. [Google Scholar]
50.Cirulli ET, Barrett KMS, Riffle S, Bolze A, Neveux I, Dabe S, et al. Long-term COVID-19 symptoms in a large unselected population. medRxiv. 2020; 2020.10.07.20208702. doi: 10.1101/2020.10.07.20208702 [DOI] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0254523.r001

Decision Letter 0

Martin Chtolongo Simuunza

Transfer Alert

This paper was transferred from another journal. As a result, its full editorial history (including decision letters, peer reviews and author responses) may not be present.

13 May 2021

PONE-D-21-12057

Burden of Post-COVID-19 Syndrome and Implications for Healthcare Service Planning: A Population-based Cohort Study

PLOS ONE

Dear Dr. Puhan,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Based on the comments from the reviewers, I am recommending that you make substantial revisions to your manuscript. You will need to pay more attention to your study designs and adequately describe the inclusion and exclusion criteria for patient recruitment. It is evident in this manuscript that the results may be biased because the way the patients were recruited. Please include this issue in your discussion by pointing out the limitations of the presented results. You also carried out a sensitivity analysis but there is no mention of this in the results. Please submit your revised manuscript after you have attended to all the reviewer's comments as advised in this letter.

Please submit your revised manuscript by Jun 25 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Martin Chtolongo Simuunza, PhD

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please provide additional details regarding participant consent. In the ethics statement in the Methods and online submission information, please ensure that you have specified what type you obtained (for instance, written or verbal, and if verbal, how it was documented and witnessed). If your study included minors, state whether you obtained consent from parents or guardians. If the need for consent was waived by the ethics committee, please include this information.

Once you have amended this/these statement(s) in the Methods section of the manuscript, please add the same text to the “Ethics Statement” field of the submission form (via “Edit Submission”).

For additional information about PLOS ONE ethical requirements for human subjects research, please refer to http://journals.plos.org/plosone/s/submission-guidelines#loc-human-subjects-research.

3. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

4. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

5. Please include captions for your Supporting Information files at the end of your manuscript, and update any in-text citations to match accordingly. Please see our Supporting Information guidelines for more information: http://journals.plos.org/plosone/s/supporting-information.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

Reviewer #3: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This study addresses a relevant issue: long-term sequelae of COVID-19.

Of 4639 SARS-CoV-2 positive patients, 2209 could be followed up and 1309 fulfilled the inclusion criteria.

Of these, 442 consented to the studies and 431 were finally included.

Of these, 385 reported continued symptoms or impairment due to the previous COVID-19.

Nevertheless, the study leaves some questions in my opinion:

The very high rate of patients reporting symptoms (385/431) suggests that there is a significant bias.

Can anything be said from the health data about the ≈900 patients who met the inclusion criteria but did not participate (anonymized analysis of age, sex, hospitalization rate during acute illness, comorbidities, social class, etc)?

In the absence of baseline data (the authors correctly note this), it is difficult to quantify a "true" effect of COVID-19.

The excellent health care system in Switzerland may lead to a particularly fine-grained resolution of the data compared to the rest of the world. The number of patients evaluated is very small compared to the total number of patients affected in Switzerland, Europe or worldwide.

A comparison to patients with similar diseases (e.g. influenza, pneumococcal pneumonia) would be helpful to compare the results. From studies in the setting pulmonary, medicine, infectious diseases or intensive care medicine, it is known that the rate of patients who still report symptoms and limitations months after the acute illness is high.

Reviewer #2: Comments

Overall Comment

Very good study, informative and timely. Only minor clarifications and corrections requested.

Comment 1. Line 229, Kindly clarify the direction of the association with Body Mass Index.

Comment 2. There is no comment on sensitivity analysis in the results or discussion.

Comment 3. Kindly clarify. In the third condition of sensitivity analysis, the period with high public awareness of post-COVID-19 syndrome (period after 09 November 2020) leaves no participants positive in that period to be selected since you only considered individuals who tested positive between 27th February 2020 and 5th August 2020.

Reviewer #3: It is an interesting work, which analyzes the clinical evolution of patients with COVID in the long term (7 months)

It presents fundamental biases in the selection of the population, which make the results difficult to extrapolate to other populations

In the first place, the selection is made with patients who are able to fill out the electronic form, which may, on the one hand, limit access to older people or people with more associated pathology.

Second, a third of the patients that have been selected are recruited. It is not described whether the characteristics (at least age, sex, hospitalization) of this population are similar to the population that was included in the study.

Likewise, this population willing to participate in the survey may overestimate persistent symptoms, since those patients with symptoms will tend to answer more frequently

In this way, the population included is young, although a third with comorbidity, and hospital admission in a very significant proportion

What is interesting about the study is the stratification of symptoms, and the evaluation of the overlap of dyspnea, fatigue, or non-recovery with depressive symptoms

It is striking that many of the symptoms are associated with initial severity but not with hospitalization.

The description of the series, with stratification of long-term symptoms, evaluation of the demand for health care and analysis of associated factors, offers relevant information

But the selection bias of this population should be pointed out more intensively in the limitations.

Likewise, I do not believe that the data allow us to offer a real vision of healthcare needs. These can only be estimated, if a population is evaluated without so many selection biases, so a reflection on this message should be made

The message cannot be transferred to the global population of COVID patients, given the previously mentioned biases, so it should be qualified in the Implications for healthcare resource planning section

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2021 Jul 12;16(7):e0254523. doi: 10.1371/journal.pone.0254523.r002

Author response to Decision Letter 0

9 Jun 2021

Editor comments

Many thanks for your comments and suggestions. We agree with you and the reviewers that potential selection bias arising from the recruitment of our participants may have important implications for the interpretation of our findings. We have further expanded on this limitation in the discussion (see lines 392-410). Regarding the results from sensitivity analysis, we had briefly discussed these in lines 388-390 (limitations section). We now additionally report on sensitivity analyses in the results section (lines 297-300).

Additional Journal Requirements

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

The manuscript has been edited to meet the style requirements of PLOS ONE. Please find the changes highlighted within the text. As part of this revision, the supplementary material has been reordered and is now provided in individual files.

Additional details regarding informed consent have been added to the manuscript (line 98) and in the submission form.

In your revised cover letter, please address the following prompts:

We will share de-identified individual participant data as part of this resubmission (Supplementary File S10). Please note that we cannot provide the exact participant age and the stratification variables used in sensitivity analysis, since these could allow the triangulation and indirect identification of individuals included in our study during time periods with low SARS-CoV-2 case numbers. All presented main analyses can be reproduced with the data provided.

4. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please delete it from any other section.

The ethics section is now included only in the Methods section.

Captions for Supporting Information have been added at the end of the manuscript.

Reviewers' comments

Reviewer #1:

This study addresses a relevant issue: long-term sequelae of COVID-19. Of 4639 SARS-CoV-2 positive patients, 2209 could be followed up and 1309 fulfilled the inclusion criteria.

Of these, 442 consented to the studies and 431 were finally included.

Of these, 385 reported continued symptoms or impairment due to the previous COVID-19.

Nevertheless, the study leaves some questions in my opinion:

The very high rate of patients reporting symptoms (385/431) suggests that there is a significant bias.

Many thanks for this valuable feedback. We agree that potential sources for selection bias are an important consideration in interpreting the findings of our study. As was previously reported in the discussion section (moved now to the results section, lines 195-197) and in S9 Table (which provides a comparison of the enrolled and non-enrolled participants), our population was younger and a lower proportion was hospitalized secondary to COVID-19 (19% versus 24%). Additionally, a higher proportion of our study participants had symptoms (89.3% compared to 80.7% in nonparticipants). However, it is to be noted that symptom assessment in non-participants is based on data collected by contact tracers as well as mandatory reporting by physicians and laboratories before contact tracing was fully established in May 2020. Due to these circumstances, data from individuals infected before May 2020 is incomplete. Additionally, we have no information on whether the non-participants developed symptoms after the initial contact tracing call, which may partly explain the lower proportion of symptomatic non-participants. While further information on the socio-demographic characteristics of non-participants would have been very useful, such data was not collected/available.

In the absence of baseline data (the authors correctly note this), it is difficult to quantify a "true" effect of COVID-19.

This is equally an important point. From the data collected in our study, it is not possible to estimate the "true effect". As stated in the manuscript, we attempted to use reference health data from Switzerland to estimate the proportion of individuals with symptoms attributable to SARS-CoV-2 infection. However, no applicable health data was available. Certainly, a comparison with other diseases could provide additional context, and we agree that other diseases may have similar longer-term effects on physical and mental health. We included a brief discussion on this subject in the manuscript (lines 341-347). However, we consider a detailed discussion to be unlikely to improve the estimation of the "true effect" of SARS-CoV-2 infection due to the same issues with transportability and representativeness of study populations. Thus, we do not believe that the comparison with other illnesses would influence the message of our manuscript targeted at the public health response to COVID-19 specifically.

Reviewer #2:

Overall Comment

Very good study, informative and timely. Only minor clarifications and corrections requested.

Comment 1. Line 229, Kindly clarify the direction of the association with Body Mass Index.

Many thanks for your valuable feedback on our manuscript. Grade ≥1 dyspnea was associated with higher body mass index- we have added the direction of the association to the text (line 388).

Comment 2. There is no comment on sensitivity analysis in the results or discussion.

Thank you for pointing this out. Please note that we had commented on the sensitivity analysis in the limitation section within the discussion (lines 388-390). However, we now also briefly report on this analysis in the results section (see lines 297-300).

Many thanks for this comment. The time period of “awareness of post-COVID-19 syndrome” that we refer to is not related to the time of SARS-CoV-2 diagnosis but rather the time of recruitment into the study and completion of the questionnaire (5.9 to 10.3 months after diagnosis corresponds to October 2020 to January 2021). To avoid any confusion for the readers, we have now made this explicitly clear in the text (line 167).

Reviewer #3:

It is an interesting work, which analyzes the clinical evolution of patients with COVID in the long term (7 months)

It presents fundamental biases in the selection of the population, which make the results difficult to extrapolate to other populations

Likewise, this population willing to participate in the survey may overestimate persistent symptoms, since those patients with symptoms will tend to answer more frequently

In this way, the population included is young, although a third with comorbidity, and hospital admission in a very significant proportion.

Many thanks for your valuable feedback on our manuscript and this important comment. We agree that potential sources for selection bias are an important consideration in interpreting the findings of our study. The primarily electronic nature of our study may well have influenced participation in our study. In the results section (lines 195-197) and in S9 Table (which provides a comparison of the enrolled and non-enrolled participants), we provided a comparison of participants and non-participants. In brief, our population was younger and a lower proportion was hospitalized secondary to COVID-19 (19% versus 24%). Thus, your concerns are certainly valid. However, this study also constitutes one of very few in which sampling of participants was based on a population-based sample among all identified cases, while many others were based exclusively on hospitalized (or hospital-diagnosed) or purposive samples suffering from similar issues. As such, our enrollment process is well documented and transparent with respect to these limitations. Furthermore, the digital nature of the follow-up may also have facilitated the recruitment of participants who would prefer not to present for in-person study visits (e.g., for convenience or health and mobility issues). For example, experiences from the Multiple Sclerosis registry in Switzerland have shown that digital questionnaires may even increase the diversity of the study population (e.g. those with severe disease; https://doi.org/10.4414/smw.2018.14623). We did everything possible to enable everyone to participate, e.g. by having repeated phone contacts prior to the use of the electronic enrollment system (encouraging help by family members) and performing phone interviews with individuals that were unable to use a computer. Our experience was that participation and motivation among those that we were able to contact was exceptionally high compared to other studies we have conducted due to the high public interest, regardless of the personal burden. However, we have revised the limitations section to make these considerations more explicit (lines 392-410).

What is interesting about the study is the stratification of symptoms, and the evaluation of the overlap of dyspnea, fatigue, or non-recovery with depressive symptoms

It is striking that many of the symptoms are associated with initial severity but not with hospitalization.

The description of the series, with stratification of long-term symptoms, evaluation of the demand for health care and analysis of associated factors, offers relevant information

But the selection bias of this population should be pointed out more intensively in the limitations.

The considerations about selection bias certainly also apply to healthcare needs. However, it is difficult to estimate the direction of any potential bias. On one side, older and more severely ill individuals may be underrepresented, leading to estimates that are too low. On the other side, individuals with issues may be more likely to participate, leading to estimates that are too high. We expanded on this issue in the limitations section (lines 426-432).

Please see above - we extended on this in the limitations section. Our study contributes to the evidence on post-COVID-19 syndrome through data from a unique, population-based sample. More research is needed to summarize all available evidence and provide meta-estimates to estimate the "true" effects of the pandemic. However, in light of current systematic reviews, our estimates seem to lie more or less in the middle of what has already been published. We are positive that this work adds important evidence to the current literature.

Attachment

Submitted filename: ZSAC_PostCovid Syndrome_Response to Reviewers_20210609.docx

Click here for additional data file.^{(59KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0254523.r003

Decision Letter 1

Martin Chtolongo Simuunza

18 Jun 2021

PONE-D-21-12057R1

Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

PLOS ONE

Dear Dr. Puhan,

The reviewers are of the view that you have made substantial revisions that has greatly improved the manuscript. However, there are a few other minor concerns that you will have to attend to that they think will further improve the manuscript. I consider all the suggestions to be very important and should be attended to. However of major concern to me is the choice of the reference category especially for nominal variables, as it will also improve the precision of the estimates. Please attend to them and resubmit your manuscript as advised in this letter.

Please submit your revised manuscript by Aug 02 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Martin Chtolongo Simuunza, PhD

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

Reviewer #1: After the revision the manuscript „Burden of post-COVID-19 syndrome and implications for healthcare service planning: a population-based cohort study” (PONE-D-21-12057_R1) by Menges and colleagues has improved substantially. My questions were answered satisfactorily for the most part. The remaining gaps are adequately discussed by the authors in the limitations.

Please correct line 417 “On one side,...” instead of “One one side,…”

Reviewer #2: All my previous comments were answered and I am satisfied with the responses. I just have the following final comments:

Comment 1: Line 168 – 170 the sentence looks incomplete. I think it is missing the word “bias”. As in “to assess potential selection bias”.

Comment 2: Table 1 Kindly put units in brackets for the variable “initial symptom duration” (days). just like you had put for the variable “time since diagnosis (days”.

Comment 3: The multivariate logistics regression analysis results in table 2 are ok and well presented. However, there is possible misallocation of the reference group or level for some of the significant covariables. For example, the covariable “gender” for outcome “non-recovery” and “dyspnea”. Also the covariable age group for outcome “fatigue” etc. It is preferable that the level with the lower proportion of the outcome variable should be the reference level for that covariable. However, this does not change the significance of the results and it may only be a matter of preference of reporting.

Comment 4: looking at the results in figure 2, isn’t the covariable “presence of comorbidity” also significantly associated with outcome “dyspnea”?

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

PLoS One. 2021 Jul 12;16(7):e0254523. doi: 10.1371/journal.pone.0254523.r004

Author response to Decision Letter 1

21 Jun 2021

Journal Requirements

-> We revised the publication list and updated the references for Sudre et al., 2021 (replaced medrxiv preprint with publication in Nature Medicine), as well as Mandal et al., 2021 and Al-Aly et al., 2021 (updated reference to most recent record). To our best knowledge, none of the cited articles has been retracted.

Reviewer #1

After the revision the manuscript „Burden of post-COVID-19 syndrome and implications for healthcare service planning: a population-based cohort study” (PONE-D-21-12057_R1) by Menges and colleagues has improved substantially. My questions were answered satisfactorily for the most part. The remaining gaps are adequately discussed by the authors in the limitations.

-> Thank you very much for your thorough review of our study and your positive feedback. We are happy that we were able to address your concerns to your satisfaction.

Please correct line 417 “On one side,...” instead of “One one side,…”

-> We have corrected this mistake.

Reviewer #2

All my previous comments were answered and I am satisfied with the responses. I just have the following final comments:

-> Thank you very much for your insightful comments and your positive feedback. We are happy that we were able to satisfactorily respond to your concerns.

Comment 1: Line 168 – 170 the sentence looks incomplete. I think it is missing the word “bias”. As in “to assess potential selection bias”.

-> We changed the wording to "to assess potential selection bias.".

Comment 2: Table 1 Kindly put units in brackets for the variable “initial symptom duration” (days). just like you had put for the variable “time since diagnosis (days”.

-> Thank you for raising this to our attention. We included the units for initial symptom duration (days) and BMI (kg/m2) in Table 1, as well as for time from symptom onset to diagnosis (days) in Table S1.

-> We agree that the results for regression analyses may be easier to interpret with a different allocation of the reference group for some variables. We changed the reference for sex in all analyses (Fig 2-3; S2-S5 Table, S8 Table), in line with your suggestions and the reporting in the text. Meanwhile, our preference would be to keep the current reporting for the other variables, for the following reasons: First, we would favor to use consistent reference levels for variables with varying direction of associations across analyses for the different outcomes (e.g. for age group, ICU stay). Second, we would prefer using the lowest levels for variables of ordinal nature (e.g. for age group, income, education), and the most frequent level (e.g. "employed") for employment. We investigated your suggestion and feel that our data is more interpretable as it is currently presented. Also, the precision of the respective estimates is negatively affected when changing the reference level (e.g. since the group of students and university-educated individuals is rather small). In our resubmission, we include both our suggested version for the figures and tables, as well as an alternative version (version 2) more in line with your suggestions. We would like to leave it up to the editor to decide which presentation of the data is preferred for publication.

Comment 4: looking at the results in figure 2, isn’t the covariable “presence of comorbidity” also significantly associated with outcome “dyspnea”?

-> This is correct - we added a statement regarding associations of the presence of comorbidities and chronic respiratory conditions with dyspnea to the manuscript (lines 246-248).

Attachment

Submitted filename: ZSAC_PostCovid Syndrome_Response to Reviewers_R2_20210621.docx

Click here for additional data file.^{(51.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0254523.r005

Decision Letter 2

Martin Chtolongo Simuunza

29 Jun 2021

Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

PONE-D-21-12057R2

Dear Dr. Puhan,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Martin Chtolongo Simuunza, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0254523.r006

Acceptance letter

Martin Chtolongo Simuunza

2 Jul 2021

PONE-D-21-12057R2

Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

Dear Dr. Puhan:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Martin Chtolongo Simuunza

Academic Editor

PLOS ONE

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Table. Comparison of population characteristics of participants of the Zurich SARS-CoV-2 Cohort study and individuals not participating in the study.

(DOCX)

Click here for additional data file.^{(15.8KB, docx)}

S2 Table. Results from univariable and multivariable logistic regression models for the outcome of not having fully recovered at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(18.8KB, docx)}

S3 Table. Results from univariable and multivariable logistic regression models for the outcome of fatigue at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(19.1KB, docx)}

S4 Table. Results from univariable and multivariable logistic regression models for the outcome of mMRC dyspnea grade ≥1 at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(19.6KB, docx)}

S5 Table. Results from univariable and multivariable logistic regression models for the outcome of depression at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(21.5KB, docx)}

S6 Table. Overlap of participants not having recovered or experiencing fatigue, dyspnea, or depression and healthcare use at six to eight months after diagnosis.

(DOCX)

Click here for additional data file.^{(16.3KB, docx)}

(DOCX)

Click here for additional data file.^{(21.6KB, docx)}

(DOCX)

Click here for additional data file.^{(24.2KB, docx)}

S1 Fig. Venn diagram of the overlap of participants that have not fully recovered or are experiencing fatigue, dyspnea or depression at six to eight months after SARS-CoV-2 infection (total N = 296).

(DOCX)

Click here for additional data file.^{(202.5KB, docx)}

S1 File. Original de-identified dataset underlying the analyses included in the study.

(XLSX)

Click here for additional data file.^{(82.8KB, xlsx)}

Attachment

Submitted filename: ZSAC_PostCovid Syndrome_Response to Reviewers_20210609.docx

Click here for additional data file.^{(59KB, docx)}

Attachment

Submitted filename: ZSAC_PostCovid Syndrome_Response to Reviewers_R2_20210621.docx

Click here for additional data file.^{(51.4KB, docx)}

Data Availability Statement

[pone.0254523.ref001] 1.World Health Organization (WHO). Coronavirus Disease (COVID-19) Situation Reports: Weekly Epidemiological Update 23 February 2021. [cited 25 Feb 2021]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports

[pone.0254523.ref002] 2.Greenhalgh T, Knight M, A’Court C, Buxton M, Husain L. Management of post-acute covid-19 in primary care. BMJ. 2020;370: m3026. doi: 10.1136/bmj.m3026 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref003] 3.National Institute for Health Research (NIHR). Living with Covid19. 15 Oct 2020. [cited 25 Jan 2021]. [Google Scholar]

[pone.0254523.ref004] 4.National Institute for Health and Care Excellence (NICE). COVID-19 rapid guideline: managing the long-term effects of COVID-19. NICE; 2020. [cited 19 Jan 2021]. https://www.nice.org.uk/guidance/ng188 [PubMed] [Google Scholar]

[pone.0254523.ref005] 5.Huang C, Huang L, Wang Y, Li X, Ren L, Gu X, et al. 6-month consequences of COVID-19 in patients discharged from hospital: a cohort study. Lancet. 2021;397: 220–232. doi: 10.1016/S0140-6736(20)32656-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref006] 6.Bellan M, Soddu D, Balbo PE, Baricich A, Zeppegno P, Avanzi GC, et al. Respiratory and Psychophysical Sequelae Among Patients With COVID-19 Four Months After Hospital Discharge. JAMA Netw Open. 2021;4: e2036142. doi: 10.1001/jamanetworkopen.2020.36142 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref007] 7.Logue JK, Franko NM, McCulloch DJ, McDonald D, Magedson A, Wolf CR, et al. Sequelae in Adults at 6 Months After COVID-19 Infection. JAMA Netw Open. 2021;4: e210830. doi: 10.1001/jamanetworkopen.2021.0830 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref008] 8.Taquet M, Geddes JR, Husain M, Luciano S, Harrison PJ. 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: a retrospective cohort study using electronic health records. The Lancet Psychiatry. 2021;8: 416–427. doi: 10.1016/S2215-0366(21)00084-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref009] 9.Havervall S, Rosell A, Phillipson M, Mangsbo SM, Nilsson P, Hober S, et al. Symptoms and Functional Impairment Assessed 8 Months After Mild COVID-19 Among Health Care Workers. JAMA. 2021;325: 2015. doi: 10.1001/jama.2021.5612 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref010] 10.Donnelly JP, Wang XQ, Iwashyna TJ, Prescott HC. Readmission and Death After Initial Hospital Discharge Among Patients With COVID-19 in a Large Multihospital System. JAMA. 2021;325: 304. doi: 10.1001/jama.2020.21465 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref011] 11.Chopra V, Flanders SA, O’Malley M, Malani AN, Prescott HC. Sixty-Day Outcomes Among Patients Hospitalized With COVID-19. Ann Intern Med. 2020; M20-5661. doi: 10.7326/M20-5661 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref012] 12.Davis HE, Assaf GS, McCorkell L, Wei H, Low RJ, Re’em Y, et al. Characterizing Long COVID in an International Cohort: 7 Months of Symptoms and Their Impact. medRxiv. 2020; 2020.12.24.20248802. doi: 10.1101/2020.12.24.20248802 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref013] 13.Sudre CH, Murray B, Varsavsky T, Graham MS, Penfold RS, Bowyer RC, et al. Attributes and predictors of long COVID. Nat Med. 2021;27: 626–631. doi: 10.1038/s41591-021-01292-y [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref014] 14.Norton A, Olliaro P, Sigfrid L, Carson G, Paparella G, Hastie C, et al. Long COVID: tackling a multifaceted condition requires a multidisciplinary approach. The Lancet Infectious Diseases. 2021; doi: 10.1016/S1473-3099(21)00043-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref015] 15.National Health Service (NHS) England. Long COVID patients to get help at more than 60 clinics. [cited 25 Feb 2021]. https://www.england.nhs.uk/2020/12/long-covid-patients-to-get-help-at-more-than-60-clinics/

[pone.0254523.ref016] 16.Center for Disease Control and Prevention (CDC). Coronavirus Disease 2019 (COVID-19). In: Centers for Disease Control and Prevention [Internet]. 11 Feb 2020 [cited 18 Mar 2020]. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-criteria.html

[pone.0254523.ref017] 17.Michielsen HJ, De Vries J, Van Heck GL. Psychometric qualities of a brief self-rated fatigue measure: The Fatigue Assessment Scale. Journal of Psychosomatic Research. 2003;54: 345–352. doi: 10.1016/s0022-3999(02)00392-6 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref018] 18.Mahler DA, Wells CK. Evaluation of Clinical Methods for Rating Dyspnea. Chest. 1988;93: 580–586. doi: 10.1378/chest.93.3.580 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref019] 19.Depression Anxiety Stress Scales (DASS). [cited 25 Feb 2021]. http://www2.psy.unsw.edu.au/dass/

[pone.0254523.ref020] 20.Lovibond SH, Lovibond PF, Psychology Foundation of Australia. Manual for the depression anxiety stress scales. Sydney, N.S.W.: Psychology Foundation of Australia; 1995.

[pone.0254523.ref021] 21.Herdman M, Gudex C, Lloyd A, Janssen MF, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20: 1727–1736. doi: 10.1007/s11136-011-9903-x [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref022] 22.Devlin N, Parkin D, Janssen B. An Introduction to EQ-5D Instruments and Their Applications. In: Devlin N, Parkin D, Janssen B, editors. Methods for Analysing and Reporting EQ-5D Data. Cham: Springer International Publishing; 2020. pp. 1–22. doi: 10.1007/978-3-030-47622-9_1 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref023] 23.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria. 2017. https://www.R-project.org/ [Google Scholar]

[pone.0254523.ref024] 24.Carfì A, Bernabei R, Landi F, for the Gemelli Against COVID-19 Post-Acute Care Study Group. Persistent Symptoms in Patients After Acute COVID-19. JAMA. 2020;324: 603. doi: 10.1001/jama.2020.12603 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref025] 25.Carvalho-Schneider C, Laurent E, Lemaignen A, Beaufils E, Bourbao-Tournois C, Laribi S, et al. Follow-up of adults with noncritical COVID-19 two months after symptom onset. Clin Microbiol Infect. 2021;27: 258–263. doi: 10.1016/j.cmi.2020.09.052 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref026] 26.Garrigues E, Janvier P, Kherabi Y, Bot AL, Hamon A, Gouze H, et al. Post-discharge persistent symptoms and health-related quality of life after hospitalization for COVID-19. Journal of Infection. 2020;81: e4–e6. doi: 10.1016/j.jinf.2020.08.029 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref027] 27.Goërtz YMJ, Van Herck M, Delbressine JM, Vaes AW, Meys R, Machado FVC, et al. Persistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome? ERJ Open Res. 2020;6: 00542–02020. doi: 10.1183/23120541.00542-2020 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref028] 28.Halpin SJ, McIvor C, Whyatt G, Adams A, Harvey O, McLean L, et al. Postdischarge symptoms and rehabilitation needs in survivors of COVID-19 infection: A cross-sectional evaluation. Journal of Medical Virology. 2021;93: 1013–1022. doi: 10.1002/jmv.26368 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref029] 29.Mandal S, Barnett J, Brill SE, Brown JS, Denneny EK, Hare SS, et al. ‘Long-COVID’: a cross-sectional study of persisting symptoms, biomarker and imaging abnormalities following hospitalisation for COVID-19. Thorax. 2021;76: 396–398. doi: 10.1136/thoraxjnl-2020-215818 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref030] 30.Taquet M, Luciano S, Geddes JR, Harrison PJ. Bidirectional associations between COVID-19 and psychiatric disorder: retrospective cohort studies of 62 354 COVID-19 cases in the USA. Lancet Psychiatry. 2021;8: 130–140. doi: 10.1016/S2215-0366(20)30462-4 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref031] 31.Townsend L, Dyer AH, Jones K, Dunne J, Mooney A, Gaffney F, et al. Persistent fatigue following SARS-CoV-2 infection is common and independent of severity of initial infection. PLOS ONE. 2020;15: e0240784. doi: 10.1371/journal.pone.0240784 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref032] 32.Wong AW, Shah AS, Johnston JC, Carlsten C, Ryerson CJ. Patient-reported outcome measures after COVID-19: a prospective cohort study. Eur Respir J. 2020;56. doi: 10.1183/13993003.03276-2020 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref033] 33.Xiong Q, Xu M, Li J, Liu Y, Zhang J, Xu Y, et al. Clinical sequelae of COVID-19 survivors in Wuhan, China: a single-centre longitudinal study. Clinical Microbiology and Infection. 2021;27: 89–95. doi: 10.1016/j.cmi.2020.09.023 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref034] 34.Moldofsky H, Patcai J. Chronic widespread musculoskeletal pain, fatigue, depression and disordered sleep in chronic post-SARS syndrome; a case-controlled study. BMC Neurol. 2011;11: 37. doi: 10.1186/1471-2377-11-37 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref035] 35.Lam MH-B. Mental Morbidities and Chronic Fatigue in Severe Acute Respiratory Syndrome Survivors: Long-term Follow-up. Arch Intern Med. 2009;169: 2142. doi: 10.1001/archinternmed.2009.384 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref036] 36.Jones JF, Ray CG, Minnich LL, Hicks MJ, Kibler R, Lucas DO. Evidence for Active Epstein-Barr Virus Infection in Patients with Persistent, Unexplained Illnesses: Elevated Anti-Early Antigen Antibodies. Ann Intern Med. 1985;102: 1–7. doi: 10.7326/0003-4819-102-1- [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref037] 37.Straus SE, Tosato G, Armstrong G, Lawley T, Preble OT, Henle W, et al. Persisting Illness and Fatigue in Adults with Evidence of Epstein-Barr Virus Infection. Ann Intern Med. 1985;102: 7–16. doi: 10.7326/0003-4819-102-1-7 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref038] 38.Seet RCS, Quek AML, Lim ECH. Post-infectious fatigue syndrome in dengue infection. Journal of Clinical Virology. 2007;38: 1–6. doi: 10.1016/j.jcv.2006.10.011 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref039] 39.Hickie I, Davenport T, Wakefield D, Vollmer-Conna U, Cameron B, Vernon SD, et al. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ. 2006;333: 575. doi: 10.1136/bmj.38933.585764.AE [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref040] 40.Islam MF, Cotler J, Jason LA. Post-viral fatigue and COVID-19: lessons from past epidemics. Fatigue: Biomedicine, Health & Behavior. 2020;8: 61–69. doi: 10.1080/21641846.2020.1778227 [DOI] [Google Scholar]

[pone.0254523.ref041] 41.Al-Aly Z, Xie Y, Bowe B. High-dimensional characterization of post-acute sequelae of COVID-19. Nature. 2021;594: 259–264. doi: 10.1038/s41586-021-03553-9 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref042] 42.Bowles KH, McDonald M, Barrón Y, Kennedy E, O’Connor M, Mikkelsen M. Surviving COVID-19 After Hospital Discharge: Symptom, Functional, and Adverse Outcomes of Home Health Recipients. Ann Intern Med. 2020; M20-5206. doi: 10.7326/M20-5206 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref043] 43.Lavery AM, Preston LE, Ko JY, Chevinsky JR, DeSisto CL, Pennington AF, et al. Characteristics of Hospitalized COVID-19 Patients Discharged and Experiencing Same-Hospital Readmission—United States, March–August 2020. MMWR Morb Mortal Wkly Rep. 2020;69: 1695–1699. doi: 10.15585/mmwr.mm6945e2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref044] 44.McCarthy CP, Murphy S, Jones-O’Connor M, Olshan DS, Khambhati JR, Rehman S, et al. Early clinical and sociodemographic experience with patients hospitalized with COVID-19 at a large American healthcare system. EClinicalMedicine. 2020;26: 100504. doi: 10.1016/j.eclinm.2020.100504 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref045] 45.Swiss Federal Office of Public Health (FOPH). COVID-19 Switzerland: Coronavirus Dashboard. [cited 6 Jun 2021]. https://www.covid19.admin.ch/en/overview

[pone.0254523.ref046] 46.Stringhini S, Zaballa M-E, Perez-Saez J, Pullen N, de Mestral C, Picazio A, et al. Seroprevalence of anti-SARS-CoV-2 antibodies after the second pandemic peak. Lancet Infect Dis. 2021; doi: 10.1016/S1473-3099(21)00054-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref047] 47.Puhan MA, Steinemann N, Kamm CP, Müller S, Kuhle J, Kurmann R, et al. A digitally facilitated citizen-science driven approach accelerates participant recruitment and increases study population diversity. Swiss Medical Weekly. 2018;148. doi: 10.4414/smw.2018.14623 [DOI] [PubMed] [Google Scholar]

[pone.0254523.ref048] 48.Vindegaard N, Benros ME. COVID-19 pandemic and mental health consequences: Systematic review of the current evidence. Brain, Behavior, and Immunity. 2020;89: 531–542. doi: 10.1016/j.bbi.2020.05.048 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254523.ref049] 49.de Quervain D, Aerni A, Amini E, Bentz D, Coynel D, Freytag V, et al. The Swiss Corona Stress Study: second pandemic wave, November 2020. OSF Preprints; 2020. [Google Scholar]

[pone.0254523.ref050] 50.Cirulli ET, Barrett KMS, Riffle S, Bolze A, Neveux I, Dabe S, et al. Long-term COVID-19 symptoms in a large unselected population. medRxiv. 2020; 2020.10.07.20208702. doi: 10.1101/2020.10.07.20208702 [DOI] [Google Scholar]

PERMALINK

Burden of post-COVID-19 syndrome and implications for healthcare service planning: A population-based cohort study

Dominik Menges

Tala Ballouz

Alexia Anagnostopoulos

Hélène E Aschmann

Anja Domenghino

Jan S Fehr

Milo A Puhan

Roles

Abstract

Background

Methods

Results

Conclusions

Background

Methods

Study design and participants

Data sources and outcome measurement

Statistical analysis

Results

Study population

Fig 1. Flow chart for the inclusion of SARS-CoV-2 infected individuals from the Canton of Zurich, diagnosed between 27 February 2020 and 05 August 2020.

Table 1. Characteristics of study participants enrolled in the Zurich SARS-CoV-2 cohort study.

Recovery and longer-term symptoms

Table 2. Relative health status, fatigue, dyspnea, mental health, and health-related quality of life in study participants at six to eight months after SARS-CoV-2 infection.

Fig 2. Associations for non-recovery, fatigue, dyspnea and depression at six to eight months after SARS-CoV-2 infection.

Fatigue

Dyspnea

Depression, anxiety and stress

Overlap of main outcomes and health-related quality of life

Healthcare service utilization

Table 3. Healthcare use and complications at six to eight months after SARS-CoV-2 infection.

Fig 3. Associations for healthcare service utilization at six to eight months after SARS-CoV-2 infection.

Sensitivity analyses

Discussion

Main findings

Evidence in context

Implications for healthcare resource planning

Limitations

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Martin Chtolongo Simuunza

Roles

Transfer Alert

Author response to Decision Letter 0

Decision Letter 1

Martin Chtolongo Simuunza

Roles

Author response to Decision Letter 1

Decision Letter 2

Martin Chtolongo Simuunza

Roles

Acceptance letter

Martin Chtolongo Simuunza

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases