Abstract

Background Some individuals experience prolonged illness after acute coronavirus disease 2019 (COVID-19). We assessed whether pre-infection symptoms affected post-acute COVID illness duration.

Methods Survival analysis was performed in adults (n=23 452) with community-managed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection prospectively self-logging data through the ZOE COVID Symptom Study app, at least weekly, from 8 weeks before to 12 weeks after COVID-19 onset, conditioned on presence versus absence of baseline symptoms (4–8 weeks before COVID-19). A case–control study was performed in 1350 individuals with long illness (≥8 weeks, including 906 individuals (67.1%) with illness ≥12 weeks), matched 1:1 (for age, sex, body mass index, testing week, prior infection, vaccination, smoking, index of multiple deprivation) with 1350 individuals with short illness (<4 weeks). Baseline symptoms were compared between the two groups, and against post-COVID symptoms.

Results Individuals reporting baseline symptoms had longer COVID-related symptom duration (median 15 days versus 10 days for individuals without baseline symptoms) with baseline fatigue nearly doubling duration. Two-thirds (910 (67.4%) of 1350) of individuals with long illness were asymptomatic beforehand. However, 440 (32.6%) had baseline symptoms, versus 255 (18.9%) of 1350 individuals with short illness (p<0.0001). Baseline symptoms doubled the odds ratio for long illness (2.14, 95% CI 1.78–2.57). Prior comorbidities were more common in individuals with long versus short illness. In individuals with long illness, baseline symptomatic (versus asymptomatic) individuals were more likely to be female, younger, and have prior comorbidities; and baseline and post-acute symptoms, and symptom burden, correlated strongly.

Conclusions Individuals experiencing symptoms before COVID-19 had longer illness duration and increased odds of long illness. However, many individuals with long illness were well before SARS-CoV-2 infection.

Shareable abstract

People with symptoms before COVID-19 report longer COVID-related illness. People with long (≥8 weeks) illness are twice as likely to have pre-COVID symptoms versus those with short (<4 weeks) illness; two-thirds of those with long illness are well beforehand. https://bit.ly/3vEsAjc

Introduction

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than three-quarters of a billion individuals worldwide. Individuals of older age, male sex and with prior comorbidities have poorer outcomes after acute infection, including higher rates of hospitalisation and mortality [1]. Many individuals hospitalised with coronavirus disease 2019 (COVID-19) experience protracted convalescence [2, 3], particularly individuals requiring ventilatory support; with the majority not fully recovered even 6 months post-discharge [4].

Many community-managed individuals also report protracted post-acute illness. An early community-based study found that 13.3% experienced illness beyond 4 weeks, and 2.8% beyond 12 weeks, with longer duration associated with female sex, older age, more severe acute illness and prior comorbidities [3]. In the United Kingdom (UK), ongoing symptomatic COVID-19 (OSC) and post-COVID-19 syndrome (PCS) are defined as otherwise-unexplained symptoms and signs for 4–12 weeks (OSC), or >12 weeks (PCS), after an acute illness attributable to SARS-CoV-2 infection [5], with some variation internationally in terminology and symptom duration (e.g. 8- versus 12-week threshold [6]).

PCS prevalence estimates vary substantially. A meta-analysis [7] highlighted the heterogeneity of published studies (I2=100%) with widely differing prevalence estimates (9–81%), varying globally, regionally, and by hospitalisation status. PCS prevalence estimates derive from predominantly hospitalised cohorts. In March 2023 the UK Office of National Statistics estimated that 1.9 million citizens (2.9% of the population) had self-reported long COVID (defined as symptoms for >4 weeks after either test-positive or suspected SARS-CoV-2 infection) [8]. An earlier UK study reported prevalence of PCS of 1.2–4.8% in test-positive individuals, considering only symptoms that limited day-to-day functioning [9]. Neither study included a control group. In contrast, a large UK primary-care study comparing community-managed adults with confirmed SARS-CoV-2 infection to a matched contemporaneous control cohort reported symptom prevalence (here, at least one symptom) at 12 weeks of 5.4% in infected versus 4.3% in uninfected individuals [10].

Ongoing and/or post-acute symptomatology after acute infection has been reported after many infections, including bacteria (e.g. Borrelia), viruses (e.g. Epstein–Barr virus), and parasites (e.g. Giardia), with many shared characteristics including fatigue, exertional intolerance and neurocognitive symptoms (“brain fog”) (recently comprehensively reviewed [11]). Post-acute infection syndromes are more common in females and younger individuals, although a relationship with initial illness severity is less clear [11]. Few studies assess pre-morbid risk factors for post-acute syndromes prospectively [12] despite possible influence of pre-morbid conditions on post-acute illness symptomatology [13]. Postulated nonexclusive mechanisms include remnant infection, autoimmunity induction and/or maladaptive tissue repair; however, for most affected individuals, definitive pathophysiology is unclear despite extensive investigations. Whether similar processes underpin PCS, and whether they are common to all PCS individuals, is unclear [14].

The ZOE COVID Symptom Study began in March 2020 with participating adults logging their health data contemporaneously across the pandemic. Thus, symptoms could be assessed prospectively and longitudinally in individuals subsequently contracting SARS-CoV-2, and irrespective of ultimate illness profile.

We hypothesised that symptoms and comorbidities before SARS-CoV-2 infection might contribute to post-acute symptomatology, including illness duration. We assessed 1) symptoms reported before COVID-19, in individuals subsequently experiencing long versus short illness; 2) symptom correlation before and after SARS-CoV-2 infection; and 3) whether prior symptoms and comorbidities affect post-COVID illness profile.

Material and methods

The ZOE COVID Symptom Study launched in the UK on 24 March 2020 as a collaboration between ZOE Ltd (London, UK), King's College London (KCL; London), Massachusetts General Hospital (Boston, MA, USA), Lund University (Lund, Sweden) and Uppsala University (Uppsala, Sweden) (ethics approval: KCL ethics committee Research Ethics Management Application System number 18210, review reference LRS-19/20–18210, with all individuals providing informed consent for use of their data in COVID-19 research at registration). After initial logging of baseline demographics, including comorbidities (supplementary table S1), participants were prompted daily to report any symptoms (direct questions and free text (supplementary table S1)), SARS-CoV-2 testing and results, and vaccination(s), using a phone-based app. Data collection expanded on 4 November 2020 to include more direct symptom questions. The cohort was surveyed regarding pre-pandemic mental health diagnoses in February–April 2021 [15] (supplementary table S2). The current dataset was cut on 30 May 2022 with symptom assessment altering 2 days later.

As described previously [3], COVID-19 was defined as symptoms associated with SARS-CoV-2 infection (supplementary table S1) commencing between 14 days before and 7 days after a self-reported positive PCR or lateral flow antigen test (LFAT). For individuals with multiple positive tests, subsequent illness profiles were defined for tests spaced >90 days apart. If ≤90 days apart, illness profile was defined according to the first positive test. Illness duration was calculated from first symptomatic day until return to asymptomatic (i.e. logging as healthy) [3, 16]. Consideration was given to possible right-censoring in duration calculation (ongoing illness at final data censoring; logging discontinuation while still symptomatic). To calculate illness duration attributable to acute SARS-CoV-2 infection, individuals were required to log as healthy for ≥1 week immediately before COVID-19 commencement [3, 16]. If symptoms were again logged within 1 week of a healthy report, illness was considered ongoing, thus allowing for illness fluctuation [3, 16].

The baseline period was defined as 4–8 weeks before COVID-19 onset, and the post-COVID period as 8–12 weeks after COVID-19 onset. To ensure consistent assessment in the entire cohort for the necessary 20 weeks, data were constrained to individuals in whom COVID-19 commenced between 30 December 2020 (8 weeks after 4 November 2020, date of symptom question expansion) and 2 March 2022 (12 weeks before 1 June 2022, date of symptom assessment alteration). Symptom burden was calculated as number of individual symptoms reported at least once during the defined period of assessment. Self-reported mental health diagnoses were considered overall, and for disorders that can include psychosis (supplementary table S2).

Short illness was defined as <4 weeks and long illness as ≥8 weeks.

Inclusion criteria were 1) self-reporting UK adults presenting with PCR- or LFAT-confirmed community-managed COVID-19, between 30 December 2020 and 2 March 2022; 2) logging at least once weekly, from ≥8 weeks before until ≥12 weeks after COVID-19 commencement; 3) logging as healthy in the week before COVID-19 commencement; and 4) comorbidity and demographic data logged at registration, with subsequent participation in the mental health survey.

In addition to nonadherence to inclusion criteria, individuals vaccinated within either baseline or post-COVID periods, or 1 week before these periods, were excluded, given symptom overlap between vaccination side-effects and COVID-19 [17].

For remaining individuals, a Cox model was performed, adjusting for demographic criteria including age, sex, body mass index, week of test, number of test-positive SARS-CoV-2 infections, smoking status, index of multiple deprivation and number of vaccinations, evaluating the effect of any symptom present at baseline on median duration overall, and for each symptom individually.

A matched case–control analysis was then performed. Individuals with long illness (≥8 weeks) were selected first. Individuals with short illness (<4 weeks) were then selected, matched 1:1 per previously listed demographic criteria using the Hungarian algorithm [18], minimising the Euclidean distance cost and ensuring equal weighting across all characteristics (normalising baseline variables before matching), without replacement for controls.

Data were compared across groups using the McNemar test for counts and Wilcoxon signed rank tests for continuous variables.

Using conditional logistic regression models, we assessed the odds of long illness duration according to baseline symptom presentation (considered overall (i.e. any symptoms at baseline) and for each individual symptom) using three levels of adjustment for covariates, as follows: 1) model 1: no adjustment; 2) model 2: as for model 1, with additional adjustment for presence of any comorbidity logged at registration (allergic rhinitis (hay fever), cancer, diabetes, kidney disease, heart disease, lung disease, asthma); 3) model 3: as for model 2, with additional adjustment for prior mental health diagnosis.

To investigate relationships between baseline and post-COVID symptoms, we assessed the odds of experiencing each individual symptom in the post-COVID period according to its presence at baseline, separately in individuals with long and with short illness, using logistic regression models with the three levels of adjustment detailed earlier, and adjusting for previously listed demographic variables. We further investigated possible sex-based difference in reporting at baseline and in the post-COVID period according to duration group given previous evidence of sex differences in post-acute infection syndromes [11], and OSC/PCS [8]. For symptoms with a severity scale (fatigue and dyspnoea), we compared severity during baseline and post-COVID periods in individuals reporting these symptoms at baseline; in addition, we considered dyspnoea specifically in individuals with prior asthma/lung disease. Seasonal effects on symptom reporting were assessed for each individual symptom separately for long and short illness groups, using summertime (May–September) as reference. As some comorbidities exhibit symptom seasonality (e.g. allergic rhinitis), adjustment for previously listed demographic variables and model 3 variables was applied.

For individuals with long illness, we investigated demographic differences according to baseline symptomatology (at least one symptom at baseline) using Chi-squared test for categorical and Mann–Whitney U-test for continuous variables. We investigated the relationship between baseline and post-COVID symptom burden using linear regression, adjusting for demographic variables.

For baseline comorbidities that differed between individuals with long versus short illness (table 1), we assessed whether presence of any of these comorbidities affected baseline symptom presentation and overall post-COVID symptom burden, using Chi-squared and Mann–Whitney U-tests, respectively. We investigated odds for individual baseline and post-COVID symptoms in individuals with long illness according to these comorbidities, using a logistic regression model adjusted for demographic variables.

TABLE 1

Demographic data of study participants

We repeated the conditional logistic regression analysis and other analyses for individuals with long illness, with minimal logging frequency of at least fortnightly (versus weekly), thus allowing for inclusion of less assiduous loggers and longer periodicity of symptom fluctuation.

False discovery rate adjustment using the Benjamini–Hochberg procedure was applied across all tested symptoms, in each analysis.

Results

Figure 1 shows participant selection. Table 1 presents the overall cohort before and after matching (supplementary table S3 presents these data per decade). Compared to the overall cohort of test-positive individuals, the selected cohort of regular loggers was older, with slightly more comorbidities. Censoring on mental health survey participation did not affect the cohort greatly except for sex (females more likely to participate); other characteristics were stable (data not shown).

FIGURE 1

Flowchart for study participant selection. LFAT: lateral flow antigen test; MH: mental health; COVID-19: coronavirus disease 2019. #: at least one health report logged weekly from 8 weeks before to 12 weeks after commencement of COVID-19; ¶: body mass index (BMI) <15 kg·m−2 or BMI >55 kg·m−2; age >100 years or age <18 years; no possibility to extract index of multiple deprivation.

The majority (906 (67.1%) out of 1350) individuals with long illness had illness duration beyond 12 weeks.

Impact of baseline symptoms on median illness duration

Reporting of any symptom at baseline increased median (interquartile range (IQR)) illness duration (from 10 (9–12) days to 15 (13–16 days)), noting that right censoring (unfinished illness) was identified for some long-illness individuals due to data censorship (n=338) and logging interruption while unhealthy (n=166). Considering individual symptoms, baseline reporting of fatigue, headache, sneezing, sore throat and rhinorrhoea increased median illness duration by 9, 7, 5, 5 and 4 days, respectively.

Matched case–control cohort analysisComorbidities

Considering the matched cohort (n=2700 individuals), 463 individuals reported lung disease and/or asthma: 310 (67.0%) reported both, 115 (24.8%) only asthma and 38 (8.2%) only lung disease. Thus “lung disease” and “asthma” categories were jointly considered. In contrast, 1326 individuals reported allergic rhinitis and/or asthma: 317 (23.9%) reported both, 910 (67.9%) only allergic rhinitis and 108 (8.1%) only asthma; thus, allergic rhinitis was considered separately.

Individuals with long (versus short) illness were more likely to report comorbidities of allergic rhinitis (p<0.001), asthma/lung disease (p<0.001), heart disease (p=0.044), diabetes (p=0.037) and/or a prior mental health diagnosis (p=0.003).

Baseline symptoms in individuals with short versus long illness

Individuals with long (versus short) illness were more likely to report baseline symptoms (440 (32.6%) versus 255 (16.8%), p<0.0001) (table 1). However, two-thirds (67.4%) of individuals with long illness were asymptomatic before COVID-19.

Logging frequency during the baseline and post-COVID periods did not differ between individuals with short versus long illness (median number of logs: 21 at baseline and 20 in post-COVID periods).

Considering individual symptoms at baseline (figure 2), the five commonest symptoms were the same regardless of ultimate illness duration, but were more prevalent in individuals with subsequent long (versus short) illness: headache (18.9% versus 9.4%), fatigue (13.0% versus 5.6%), sore throat (15.0% versus 8.8%), rhinorrhoea (14.3% versus 8.5%) and sneezing (11.9% versus 6.8%) (descriptive data only).

FIGURE 2

Symptom prevalence during the baseline period in individuals with long illness versus short illness (descriptive data only, unadjusted for comorbidities, week of testing, prior infection, vaccination status, smoking or index of multiple deprivation).

Baseline symptoms associated with increased odds of long illness

Adjusting for demographic variables, the odds ratio for long illness in symptomatic (versus asymptomatic) baseline status was 2.14 (95% CI 1.78–2.57).

Considered per symptom, with identical covariates, reporting of almost any individual symptom at baseline increased the odds of long illness (figure 3). However, no evidence of association was seen between long illness and baseline cutaneous symptoms (red welts, “blisters”, alopecia), rigors, or myalgia, and, after adjustment for prior comorbidities (model 2) and prior mental health diagnoses (model 3), dyspnoea or anorexia (“low appetite”).

FIGURE 3

Odds ratios from conditional logistic regression of individual symptoms in individuals with long illness versus short illness (reference group), according to baseline symptom reporting. Model 1: no adjustment; model 2: additionally adjusted for any comorbidity reported at registration; model 3: additionally adjusted for prior mental health diagnosis. Circle size represents baseline symptom prevalence in individuals with short versus long illness duration. Odds ratios are shown as dots with 95% confidence intervals as lines: results in red are significant after adjustment for multiple comparisons.

Symptom concordance over time

Figure 4 compares symptoms during baseline or post-COVID periods, in individuals with long or short illness (categories: stayed absent/appeared/disappeared/stayed present). Importantly, our inclusion criteria meant individuals with long illness had at least one symptom during the post-COVID period, whereas individuals with short illness had returned to asymptomatic for ≥1 week within 4 weeks of developing COVID-19 (although they might subsequently report symptoms again).

FIGURE 4

Concordance of symptoms between baseline and post-COVID (coronavirus disease 2019) periods, in individuals with short versus long illness (n=1350 in each group).

In individuals with long illness, individual symptoms were more likely in the post-COVID period if present at baseline, with exceptions of some cutaneous manifestations (figure 5). Adjusting for baseline comorbidities (model 2) and prior mental health diagnosis (model 3) made minimal difference.

FIGURE 5

Odds ratios of symptom concordance (i.e. present in the post-COVID (coronavirus disease 2019) period, if reported at baseline (reference period)) in individuals with long illness. Model 1: adjusted for age, sex, body mass index (BMI), vaccination number, prior infection, week of testing, smoking and index of multiple deprivation; model 2: additionally adjusted for comorbidities reported at registration; model 3: additionally adjusted for prior mental health diagnosis. Circle size refers to symptom prevalence during baseline and post-COVID periods. Symptoms are ordered by decreasing prevalence at baseline. Odds ratios are shown as dots with 95% CI as lines; results in red are significant after adjustment for multiple comparisons.

For comparison, and as expected given our inclusion criteria, fewer symptoms were reported in the post-COVID period in individuals with short illness, considering short illness overall (blue bars, figure 6b and d; and upper panels, supplementary figure S1) and by baseline individual symptom (supplementary figure S2). Symptoms more likely to be present during both baseline and post-COVID periods in this group included several upper respiratory symptoms (tinnitus, sore throat, rhinorrhoea, sneezing, hoarse voice) and some systemic symptoms (headache, lymphadenopathy, dizziness, myalgia, rigor, fatigue). Adjusting for baseline comorbidities (model 2) reduced significance for the rarest symptoms; adjusting further for prior mental health diagnosis (model 3) did not alter these results substantially.

Symptom reporting by sex

Symptom prevalence during both baseline and post-COVID periods varied by sex, whether illness was of long or short duration. Most symptoms were more commonly reported by females than males (descriptive data: figure 6, supplementary figure S1; statistical comparisons: supplementary table S4 (baseline symptoms) and supplementary table S5 (post-COVID symptoms). Sex differences in symptom prevalences appeared least for post-COVID symptoms in individuals with long illness (supplementary figure S1, lower right panel), and for baseline symptoms in individuals with short illness (supplementary figure S1, upper left panel). These findings should be interpreted descriptively, as we did not formally test for an interaction between symptoms and sex.

FIGURE 6

Symptom prevalence by sex in individuals with short and long illness duration, considered during a, c) baseline and b, d) post-COVID (coronavirus disease 2019) periods.

Symptom severity over time

Considering individuals with long illness and fatigue at baseline (176 individuals): 101 (57%) reported unchanged, 45 (26%) improved and 30 (17%) worsened fatigue severity. Considering individuals with long illness with dyspnoea at baseline (35 individuals): 22 (65%) reported unchanged, 11 (31%) improved and two (6%) worsened severity (supplementary table S1, supplementary figure S3).

For comparison, individuals with short illness duration showed improvement or resolution of either symptom if reported at baseline, noting again the bias imposed by our inclusion criteria.

Considering the 22 individuals with asthma/lung disease reporting dyspnoea at baseline (independent of disease duration): one (4.5%) reported worsening, 13 (59%) unchanged and eight (36%) decreasing or resolved dyspnoea.

Baseline symptoms and seasonality

Individuals with long illness were more likely to be asymptomatic at baseline if this period occurred during May–September versus other times of year (280 (30.8%) out of 910 versus 97 (22.0%) out of 440, p=0.002). Reciprocally, the odds ratio for experiencing some specific symptoms at baseline was higher in November–March versus May–September (for low mood, headache, rhinorrhoea, lymphadenopathy, chest pain, sneezing, sore throat and ophthalmodynia), after correcting for all model 3 covariates (data not shown).

Individuals with short illness also appeared to have more rhinorrhoea, sneezing and headache at baseline between November and March, though not significantly after false discovery rate adjustment.

Baseline symptoms in individuals with long illness

In individuals with long illness, 440 (32.6%) reported at least one symptom at baseline, whereas 910 (67.4%) were asymptomatic.

Symptomatic individuals were more likely to be female (336 (76.4%) of 440 versus 609 (66.9%) of 910, p=0.0004); younger (median (IQR) age 54 (46–62) years versus 59 (52–65) years, p<0.0001); have allergic rhinitis (248 (56.4%) of 440 versus 404 (44.3%) of 910, p<0.0001) and/or a prior mental health diagnosis (141 (32.0%) of 440 versus 230 (25.7%) of 910, p=0.011). 36 (7.1%) of 507 symptomatic individuals and 61 (5.6%) of 1088 asymptomatic individuals were healthcare workers (p=0.29).

Post-COVID symptom burden was higher in individuals with long illness who were symptomatic (versus asymptomatic) at baseline (median (IQR) symptom burden (6 (3–9) versus 4 (2–7), p<0.0001). Baseline symptom burden was associated with post-COVID symptom burden (p<0.0001; β=+5.6%, 95% CI (4.4–6.8%) per additional baseline symptom) after adjustment for all initial matching criteria.

Baseline symptomatic status (here, any symptom) did not affect the odds of experiencing post-COVID symptoms of cutaneous manifestations, palpitations, dyspnoea, cough, tinnitus, hoarse voice, fever, rigors, anorexia or dizziness. All other post-COVID symptoms were more common in individuals with long illness and any symptom at baseline, with the exception of anosmia/dysosmia, which was less likely post-COVID (OR 0.75, 95% CI 0.58–0.96; p=0.022) (figure 7).

FIGURE 7

Symptom prevalence in individuals with long illness according to baseline symptom reporting (any symptom reported versus no symptom); odds ratios of each individual symptom in the post-COVID (coronavirus disease 2019) period according to baseline symptom reporting (any reported symptom versus no symptom). Red lines indicate significantly increased odds. Symptoms are ordered by decreasing prevalence at baseline.

Influence of prior comorbidities on baseline and post-COVID symptoms

Having at least one prior comorbidity (here, including prior mental health diagnosis) was more common in individuals with long versus short illness (926 (68.6%) of 1350 individuals with long illness versus 668 (49.5%) of 1350 individuals with short illness; p<0.001). Individuals with long illness duration and at least one prior comorbidity (versus those without) were more likely to have baseline symptoms (here, any symptom) (326 (35.2%) of 926 versus 114 (26.9%) of 424, p=0.003) and experienced greater post-COVID symptom burden (median (IQR) 5 (2–9) versus 3 (2–6), p<0.0001) (supplementary figure S4).

Odds ratios for individual symptoms experienced during baseline and post-COVID periods in individuals with at least one prior comorbidity, per comorbidity, are shown in supplementary figure S5.

Sensitivity analysis

Easing logging regularity to fortnightly-minimum reporting and (consequently) defining end of illness as 2 weeks of healthy reports, then reselecting individuals for the matched study, gave remarkably stable results. Samples sizes increased to 2496 individuals per group. Prevalence of baseline symptoms in individuals with long illness was similar to previously, and again nearly twice that of individuals with short illness (794 (31.8%) versus 441 (17.7%)). The five commonest symptoms at baseline were unchanged, and again the same in both groups, in slightly different order and proportions (data not shown). As previously, all comorbidities (except kidney disease and cancer) and a prior mental health diagnosis were more common in individuals with long illness. Supplementary figure S6 presents raw symptom prevalences at baseline for short and long illness groups; supplementary figures S7 and S8 display odds ratios for symptom consistency between baseline and follow-up in individuals with short and long duration, respectively.

Discussion

Here we have shown a relationship between symptoms before COVID-19 and subsequent illness duration. Overall, individuals with long illness were nearly twice as likely to report symptoms 4–8 weeks before SARS-CoV-2 infection than individuals with short illness (32.5% versus 18.0%). However, two-thirds of individuals with long illness were asymptomatic before COVID-19.

The odds of long illness increased for any baseline symptom, and for most individual symptoms. Baseline and post-COVID individual symptoms correlated closely in individuals with long illness, although less evident in individuals with short illness, acknowledging the bias created by our selection criteria here.

Commonest baseline symptoms, regardless of illness duration, were rhinorrhoea, sneezing, sore throat, fatigue and headache, each with higher prevalence in individuals with subsequent long (versus short) illness. The cause of these baseline nonspecific symptoms is unclear, noting here low UK circulation of respiratory viruses beyond SARS-CoV-2 during the time period of this study [19] and that healthcare workers (with possibly greater workplace exposure to respiratory viruses) did not differ in baseline symptom status. Baseline symptoms might reflect noninfectious comorbidities and individuals with several prior comorbidities (most commonly allergic rhinitis, asthma/lung disease and a prior mental health diagnosis) were more likely to report symptoms during baseline and post-COVID periods (supplementary figure S4), although no clear differential symptom pattern within these groups was evident (supplementary figure S5).

Despite higher UK pollen counts in May–September, individuals with long illness were less likely to have baseline symptoms during this time. Several symptoms, including low mood, were more common in individuals with long illness and November–March baselines, noting that seasonal affective disorder was not solicited in the mental health questionnaire [15].

Our data suggest that some post-COVID symptoms, particularly in individuals with prior comorbidities, may reflect other, serious, non-COVID illness(es). If so, symptom misattribution to OSC/PCS might cause suboptimal management of these other illness(es), with persistence and/or worsening of the other condition consequently. Alternatively, individuals with these comorbidities might be at greater risk of SARS-CoV-2 infection, or of more severe COVID-19 [3]; their underlying comorbidities might be exacerbated by SARS-CoV-2 infection; and/or they may be more vulnerable to specific new pathologies initiated by SARS-CoV-2 infection. For example, post-COVID dyspnoea in individuals with asthma might represent usual asthma, post-viral asthma exacerbation and/or superimposed pathologies specific to SARS-CoV-2 infection such as post-pneumonitis fibrosis or pulmonary microembolism (pertinently, our data did not support worsening dyspnoea in individuals with asthma/lung disease; and recent systematic reviews and meta-analyses show asthma was associated with lower risk of SARS-CoV-2 infection or of severe COVID-19 [20]). Lastly, altered pandemic healthcare access might disproportionately affect individuals with prior comorbidities; however, there was no evidence of such differential access to UK primary care during the pandemic.

Our data concord with two large retrospective studies using primary care data [10, 21]. As mentioned, a large UK study of community-managed adults with (n=486 149) and without (n=1 944 580) SARS-CoV-2 infection showed moderately higher symptom prevalences in individuals with (versus without) SARS-CoV-2 12 weeks after index event, although this difference narrowed over time [10]. Similar to our analysis, longer symptom duration associated with female sex, younger age and several prior comorbidities including respiratory illnesses and mental health diagnoses; in contrast to our analysis, this study did not compare pre- versus post-infection symptoms per individual [10]. A German study of 51 630 general practice patients with COVID-19 reported PCS prevalence of 8.3% (without comparison population), associated with female sex, comorbidities of asthma and several mental health disorders, and, in contrast to our data, older age; prior symptoms (as opposed to prior comorbidities) were not assessed [21]. Our data also concord with a study of three longitudinal cohorts (54 960 participants; 3193 testing positively for SARS-CoV-2, of whom 1403 developed OSC/PCS), which showed that pre-infection psychological distress associated with increased risk of post-COVID symptoms [22]. Pertinently, the UK lockdown abruptly increased mental distress, particularly in females, younger adults, individuals with young children and individuals with pre-existing mental health conditions [23]; lockdown had a disproportionate effect on symptom experience in individuals with pre-existing mental health vulnerabilities [24].

In addition, our data concord with a substudy of the observational Dutch Lifelines cohort [25], which prospectively collected symptom data across the pandemic. Symptoms were considered pre- and post-infection (out to 90–150 days after illness onset, or matched time point) in 4231 individuals with COVID-19 (both community- and hospital-managed individuals) and 8462 controls. Symptom severity worsened more in the COVID-19 group (versus uninfected controls), both during acutely and during days 90–150, for several symptoms including breathlessness, chest pain, myalgias, anosmia and fatigue; overall, 21.4% of cases (versus 8.7% of controls) had substantial symptom increases 90–150 days after infection compared with pre-infection, an increased symptom severity burden of 12.7% above background. Again, a gender effect was evident: females reported greater symptom severity acutely and longer persistence of increased symptom severity than males. In contrast, we assessed only individuals with confirmed COVID-19, although our baseline pre-infection data also provide insights into background community symptom prevalences during the pandemic.

Lastly, nocebo effects need consideration. Media commentary regarding OSC/PCS has been widespread, often featuring “floating numerators”. Individuals with anxiety and psychological distress are particularly vulnerable to nocebo effects for pain [26]; whether applicable to the pandemic experience is unknown. Relevantly, a high nocebo effect was observed post-SARS-CoV-2 vaccination [27].

Sex and age effects

In both short- and long-illness groups, both sexes were similarly assiduous and persistent in reporting (data not shown), contributed to by study design. Nonetheless, whether ultimately experiencing long or short illness, individuals with baseline symptoms were more likely to be female, and younger than their asymptomatic counterparts. Our results concord with previous studies showing higher symptom reporting by females versus males for many conditions, including symptom prevalence in daily life [28] and post-acute infection syndromes [11]. Sex differences in illness presentation are increasingly recognised, with potential for differential gender-discriminatory healthcare. Our data concord with previous studies showing decreased symptom reporting (particularly stress-related symptoms) with age [28].

Strengths and limitations

Our study used prospective, dense and granular symptom reporting by each person in a large community-managed cohort over an extended time period, across confirmed SARS-CoV-2 infection, irrespective of ultimate illness duration, with each person serving as their own control. Our design and matching approach limited reporter bias, with no (or minimal) difference in logging frequency, duration, or assiduousness by baseline status or by illness duration. Although predominant circulating SARS-CoV-2 variants altered during this study, with differing risks of long illness across variants [16], we controlled for this by matching by testing week. National Health Service access to antiviral drugs (which might alter symptom severity and/or longevity) for community-managed individuals became available on the day our dataset was cut (30 May 2022), although we cannot exclude the possibility that some individuals obtained private prescriptions before this time. We have avoided the phrase “long COVID”: we do not have access to health records and individuals were not asked about this diagnosis formally. Thus, our data are agnostic to self-identification, in contrast to Office for National Statistics data that included in their definitions anyone with self-defined long COVID of >4 weeks [8]. Lastly, our data are from individuals with community-managed COVID-19, whereas most papers interrogating long symptom duration post-COVID-19 are dominated by data from hospitalised individuals in whom mechanisms underlying symptom duration are likely to be different.

We acknowledge that we have not captured participants’ changing social circumstances over time, which may affect symptom experience; for example, varying personal/regional lockdown requirements resulting in varying exposure to other (i.e. non SARS-CoV-2) viruses [19]; varying extent and duration of social isolation and loneliness; differential home-schooling responsibilities, which burden was disproportionally experienced by women and associated with markedly increased psychological distress [15].

The requirement for 1 week's asymptomatic logging record prior to COVID-19 symptom onset (to enable illness duration to be calculated [3]) may have biased our sample towards healthier people less affected by pre-existing comorbidities, resulting in underestimation of the relationship of prior symptoms and comorbidities with subsequent illness duration. Additionally, all individuals had community-managed COVID-19; our data cannot be extrapolated to hospitalised individuals.

Although the direct symptom questions expansion from November 2020 was informed by feedback from individuals experiencing OSC/PCS, pertinent symptoms may have been missed, although our direct questions covered the symptom groups in other PCS studies [10, 21, 25]. Furthermore, all but two symptom questions were binary (yes/no) with no available quantitative assessment or health record linkage.

Our analysis used data from the first reported SARS-CoV-2 positive result and subsequent illness duration. Evidence of repeated infection was used as demographic-matching criteria (45 in each group); however, as it transpired, only one illness episode was included per participant.

Overall, ZOE/COVID Symptom Study app users are not representative of the UK population (younger, more female, higher educational status, lower ethnic diversity, over-representative of healthcare workers). Moreover, individuals had to log assiduously, at length, which might bias our data towards individuals with specific app usage behaviours and potentially exclude individuals with app usage fatigue. To assess this we compared our study participants to all ZOE app symptomatic test-positive users, across the same time period: our cohort were more persistent than positive ZOE app users overall (time between symptom commencement and last report: median (IQR) 206 (140–292) days for our cohort versus 99 (15–159) days for test-positive symptomatic ZOE app users overall); and app fatigue was not evident, but the opposite, with strong correlation (Spearman ρ=0.465, p<0.00001) in all symptomatic test-positive app users between symptom duration and continuing app usage (both calculated from date of symptom onset). Although we cannot comment more granularly (e.g. possible differential dropout of individuals with particular symptoms), these data do not support app fatigue; and pertinently, two-thirds of our long illness group had symptoms for ≥12 weeks.

Our inclusion criteria required participation in the mental health questionnaire in early 2021 [15]. Out of 1 257 278 million app users at the time, 715 324 (56.8%) participated; whether participation was affected by presence/absence of a prior mental health diagnosis cannot be determined. However, censoring for mental health survey participation only significantly affected the male/female ratio (females more likely to participate; data not shown).

We considered the impact of stringent logging frequency possibly precluding individuals with longer and/or more severe illness. However, our sensitivity analysis with loosened stringency did not change our results significantly (supplementary figures S5–S7).

Lastly, we cannot exclude an effect of app participation per se on symptom reporting (regardless of disease duration), noting that use of symptom tracking apps can inflate symptom reporting in some individu