The impact of wildtype SARS-CoV-2 on fatigue and quality of life: prevalence of post COVID-19 condition in a Dutch population-based serosurveillance cohort. (preprint)

Background: Our aim was to assess the relationship between (time since) wild-type SARS-CoV-2 infection and health-related quality of life (HRQoL) and fatigue as endpoints linked to Post COVID-19 condition (PCC). Methods: Participants [≥]15 years were selected from the February 2021 round of the population-based PIENTER Corona study. We investigated the association between (time since) SARS-COV-2 infection and health outcomes: HRQoL (health utility (SF-6D); physical health and mental health (both SF-12)) and fatigue (CIS-fatigue) using multivariable logistic regression analyses adjusted for age, sex, educational level, number of comorbidities, COVID-19 vaccination status, and the intensity of restrictions. For each outcome, multivariable logistic regression models were fitted at cut-off points selected based on the cumulative distribution of those uninfected. Results: Results shown correspond to the cut-off point related to the worst off 15% of each outcome. Significant differences between those uninfected (n=4,614) and cases infected [≤]4 months ago (n=368) were observed for health utility (OR [95%CI]: 1.6 [1.2-2.2]), physical health (OR [95%CI]: 1.7 [1.3-2.3]) and fatigue (OR [95%CI]: 1.6 [1.2-2.0]), but not for mental health. There were no significant differences between uninfected and cases infected >4 months ago (n=345) for all outcomes. Conclusions: In a Dutch population-based cohort of seroconverted individuals, those infected with wild-type SARS-CoV-2 [≤]4 months ago more often reported poor health utility and physical health and were more often severely fatigued compared to those uninfected (at the 15% cut-off). HRQoL and fatigue remained below the detection limit for those infected >4 months ago, suggesting a relatively low prevalence of PCC.

Lower prevalence of Post-Covid-19 Condition following Omicron SARS-CoV-2 infection. (preprint)

Background: Different SARS-CoV-2 variants can differentially affect the prevalence of Post Covid-19 Condition (PCC). This prospective study assesses prevalence and severity of symptoms three months after an Omicron infection, compared to Delta, test-negative and population controls. This study also assesses symptomology after reinfection and breakthrough infections . Methods: After a positive SARS-CoV-2 test, cases were classified as Omicron or Delta based on [≥] 85% surveillance prevalence. Population controls were representatively invited and symptomatic test-negative controls enrolled after a negative SARS-CoV-2 test. Three months after enrolment, participants indicated point prevalence for 41 symptoms and severity of four symptoms. Permutation tests identified significantly elevated symptoms in cases compared to controls. PCC prevalence was estimated as the difference in prevalence of at least one elevated symptom in cases compared to population controls. Findings: At three months follow-up, five symptoms and severe dyspnea were significantly elevated in Omicron cases (n = 4138) compared to test-negative (n= 1672) and population controls (n= 2762). PCC prevalence was 10.4% for Omicron cases and 17.7% for Delta cases (n = 6855). Prevalence of severe fatigue and dyspnea were higher in reinfected compared to primary infected Omicron cases, while severity of symptoms did not significantly differ between Omicron cases with a booster or primary vaccination course. Interpretation: Three months after Omicron, prevalence of PCC is 41% lower than after Delta. Reinfection seems associated with more prevalent severe long-term symptoms compared to a first infection. A booster prior to infection does not seem to improve the outcome of long-term symptoms. Funding: The study is executed by the National Institute for Public Health and the Environment by order of the Ministry of Health, Welfare and Sport.

Prevalence and severity of symptoms 3 months after infection with SARS-CoV-2 compared to test-negative and population controls in the Netherlands (preprint)

Background: More information is needed on prevalence of long-term symptoms after SARS-CoV-2-infection. This prospective study assesses symptoms three months after SARS-CoV-2-infection compared to test-negative and population controls, and the effect of vaccination prior to infection. Methods: Participants enrolled after a positive (cases) or negative (test-negative controls) SARS-CoV-2-test, or after invitation from the general population (population controls). After three months, participants indicated presence of 41 symptoms, and severity of four symptoms. Permutation tests were used to select symptoms significantly elevated in cases compared to controls and to compare symptoms between cases that were vaccinated or unvaccinated prior to infection. Findings: Between May 19th and December 13th 2021 9166 cases, 1698 symptomatic but test-negative controls, and 3708 population controls enrolled. At three months, 13 symptoms, and severity of fatigue, cognitive impairment and dyspnoea, were significantly elevated between cases and controls. Of cases, 48.5% reported [≥]1 significantly elevated symptom, compared to 29.8% of test-negative controls and 26.0% of population controls. Effect of vaccination could only be determined for cases <65yrs, and was found to be significantly protective for loss of smell and taste but not for other symptoms. Interpretation: Three months after SARS-CoV-2 infection, almost half of the cases still report symptoms, which is higher than the background prevalence and prevalence in test-negative controls. Vaccination prior to infection was protective against loss of smell and taste as assessed in cases aged <65.

Prevalence and determinants of persistent symptoms after infection with SARS-CoV-2: Protocol for an observational cohort study (LongCOVID-study) (preprint)

Background: A substantial proportion of individuals infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) report persisting symptoms weeks and months following acute infection. Estimates on prevalence vary due to differences in study designs, populations, heterogeneity of symptoms and the way symptoms are measured. Common symptoms include fatigue, cognitive impairment and dyspnea. However, knowledge regarding the nature and risk factors for developing persisting symptoms is still limited. Hence in this study we aim to determine the prevalence, severity, risk factors and impact on quality of life of persisting symptoms in the first year following acute SARS-CoV-2 infection. Methods: The LongCOVID-study is both a prospective and retrospective cohort study with a one year follow up. Participants aged 5 years and above with self-reported positive or negative tests for SARS-CoV-2 will be included in the study. The primary outcome is the prevalence and severity of persistent symptoms in participants that tested positive for SARS-CoV-2 compared to controls. Symptom severity will be assessed for fatigue using the Checklist Individual Strength (CIS subscale fatigue severity), pain (Rand-36/SF-36 subscale bodily pain), dyspnea (Medical Research Council (mMRC)) and cognitive impairment using the Cognitive Failure Questionnaire (CFQ). Secondary outcomes include loss of health-related quality of life (HRQoL) and risk factors for persisting symptoms following infection with SARS-CoV-2. Discussion: A better understanding regarding the nature of persisting symptoms following SARS-CoV-2 infection will enable better diagnosis, management and will consequently minimize negative consequences on quality of life. Keywords: SARS-CoV-2, post COVID-19 condition, LongCovid, prevalence, HRQoL, risk factors

Testing behaviour and positivity for SARS-CoV-2 infection: Insights from web-based participatory surveillance (preprint)

BackgroundVoluntary testing for SARS-CoV-2 infection is an integral component of an effective response to the COVID-19 pandemic. It is essential to identify populations at a high risk for infection but who are less likely to present for testing. Here, we use internet-based participatory surveillance data from the Netherlands to identify sociodemographic and household factors that are associated with a lower propensity to be tested and, if tested, with a higher risk of a positive test result.MethodsMultivariable analyses using generalised estimating equations for binomial outcomes were conducted to estimate the adjusted odds ratios of testing and of positivity associated with participant and household characteristics.ResultsBased on five months (17 November 2020 to 18 April 2021) of weekly surveys obtained from 12,026 participants, males (adjusted odds ratio for testing (ORt): 0.92; adjusted odds ratio for positivity (ORp): 1.30, age-groups <20 (ORt: 0.89; ORp: 1.27) 50-64 years (ORt: 0.94; ORp: 1.06) and 65+ years (ORt: 0.78; ORp: 1.24), diabetics (ORt: 0.97; ORp: 1.06), and sales/administrative employees (ORt: 0.93; ORp: 1.90) were distinguished as lower propensity/higher positivity factors.ConclusionsThe factors identified using this approach can help identify potential target groups for improving communication and encouraging testing among those with symptoms and thus increase the effectiveness of testing, which is essential for the response to the COVID-19 pandemic and for public health strategies in the longer term.