A hybrid register and questionnaire study of Covid-19 and post-acute sick leave in Denmark

Exploring the dynamics of COVID-19 in a Greenlandic cohort: Mild acute illness and moderate risk of long COVID

Objectives

This study aimed to explore how the Greenlandic population experienced the course of both acute and long-term COVID-19. It was motivated by the unique epidemiologic situation in Greenland, with delayed community transmission of SARS-CoV-2 relative to the rest of the world.

Methods

In a survey among 310 Greenlandic adults, we assessed the association between previous SARS-CoV-2 infection and overall health outcomes by administering three repeated questionnaires over 12 months after infection, with a response rate of 41% at the 12-month follow-up. The study included 128 individuals with confirmed SARS-CoV-2 infection from January/February 2022 and 182 test-negative controls. Participants were recruited through personal approaches, phone calls, and social media platforms.

Results

A total of 53.7% of 162 participants who were test-positive recovered within 4 weeks and 2.5% were hospitalized due to SARS-CoV-2. The most common symptoms were fatigue and signs of mild upper respiratory tract infection. Less than 5% reported sick leave above 2 weeks after infection. Compared with participants who were test-negative, there was an increased risk of reporting fatigue (risk differences 25.4%, 95% confidence interval 8.8-44.0) and mental exhaustion (risk differences 23.4%, 95% confidence interval 4.8-42.2) up to 12 months after a positive test.

Conclusions

Our results indicate that during a period dominated by the Omicron variant, Greenlanders experienced a mild acute course of COVID-19, with quick recovery, minimizing the impact on sick leave. Long COVID may be present in Greenlanders, with symptoms persisting up to 12 months after infection. However, it is important to consider the small sample size and modest response rate as limitations when interpreting the results.

Cohort profile: EFTER-COVID - a Danish nationwide cohort for assessing the long-term health effects of the COVID-19 pandemic

PURPOSE

To follow SARS-CoV-2-infected persons up to 18 months after a positive test in order to assess the burden and nature of post acute symptoms and health problems.

PARTICIPANTS

Persons in Denmark above 15 years of age, who were tested positive for SARS-CoV-2 during 1 September 2020 to 21 February 2023 using a RT-PCR test. As a reference group, three test-negative individuals were selected for every two test-positive individuals by matching on test date.

FINDINGS TO DATE

In total, 2 427 913 invitations to baseline questionnaires have been sent out and 839 528 baseline questionnaires (34.5%) have been completed. Females, the age group 50-69 years, Danish-born and persons, who had received at least one SARS-CoV-2 vaccination booster dose were more likely to participate. Follow-up questionnaires were sent at 2, 4, 6, 9, 12 and 18 months after the test, with response rates at 42%-54%.

FUTURE PLANS

New participants have been recruited on a daily basis from 1 August 2021 to 23 March 2023. Data collection will continue until the last follow-up questionnaires (at 18 months after test) have been distributed in August 2024.

Machine learning identifies risk factors associated with long-term sick leave following COVID-19 in Danish population

BACKGROUND

Post COVID-19 condition (PCC) can lead to considerable morbidity, including prolonged sick-leave. Identifying risk groups is important for informing interventions. We investigated heterogeneity in the effect of SARS-CoV-2 infection on long-term sick-leave and identified subgroups at higher risk.

METHODS

We conducted a hybrid survey and register-based retrospective cohort study of Danish residents who tested positive for SARS-CoV-2 between November 2020 and February 2021 and a control group who tested negative, with no known history of SARS-CoV-2. We estimated the causal risk difference (RD) of long-term sick-leave due to PCC and used the causal forest method to identify individual-level heterogeneity in the effect of infection on sick-leave. Sick-leave was defined as >4 weeks of full-time sick-leave from 4 weeks to 9 months after the test.

RESULTS

Here, in a cohort of 88,818 individuals, including 37,482 with a confirmed SARS-CoV-2 infection, the RD of long-term sick-leave is 3.3% (95% CI 3.1% to 3.6%). We observe a high degree of effect heterogeneity, with conditional RDs ranging from -3.4% to 13.7%. Age, high BMI, depression, and sex are the most important variables explaining heterogeneity. Among three-way interactions considered, females with high BMI and depression and persons aged 36-45 years with high BMI and depression have an absolute increase in risk of long-term sick-leave above 10%.

CONCLUSIONS

Our study supports significant individual-level heterogeneity in the effect of SARS-CoV-2 infection on long-term sick-leave, with age, sex, high BMI, and depression identified as key factors. Efforts to curb the PCC burden should consider multimorbidity and individual-level risk.