A register and questionnaire study of long-term general health symptoms following SARS-CoV-2 vaccination in Denmark.

Many individuals who refuse COVID-19 vaccination have concerns about long-term side effects. Here, we report findings on self-reported symptoms from a Danish survey- and register study. The study included 34,868 vaccinated primary course recipients, 95.8% of whom received mRNA vaccines, and 1,568 unvaccinated individuals. Participants had no known history of SARS-CoV-2 infection. Using g-computation on logistic regression, risk differences (RDs) for symptoms between vaccinated and unvaccinated persons were estimated with adjustments for possible confounders. Within six weeks after vaccination, higher risks were observed for physical exhaustion (RD 4.9%, 95% CI 1.1% to 8.4%), fever or chills (RD 4.4%, 95% CI 2.1% to 6.7%), and muscle/joint pain (RD 7.0%, 95% CI 3.1% to 10.7%), compared to unvaccinated individuals. Beyond twenty-six weeks, risks were higher among the vaccinated for sleeping problems (RD 3.0, 95% 0.2 to 5.8), fever or chills (RD 2.0, 95% CI 0.4 to 3.6), reduced/altered taste (RD 1.2, 95% CI 0.2 to 2.3) and shortness of breath (RD 2.6, 95% CI 0.9 to 4.0). However, when examining pre-omicron responses only, the difference for reduced/altered taste was significant. As expected, the risk of experiencing physical exhaustion, fever or chills, and muscle/joint pain was higher among persons who responded within six weeks of completing the primary course. No significant differences were observed for the 7-25-week period after vaccination. Associations for the period beyond 26 weeks must be interpreted with caution and in the context of undetected SARS-CoV-2 infection, wide confidence intervals, and multiple testing. Overall, we observe no concerning signs of long-term self-reported physical, cognitive, or fatigue symptoms after vaccination.

A Danish questionnaire study of acute symptoms of SARS-CoV-2 infection by variant, vaccination status, sex and age.

It is not well-described how the acute symptoms of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) differ by variant, vaccination, sex and age. A cross-sectional questionnaire study linked to national testing- and registry data was conducted among 148,874 SARS-CoV-2 first time reverse transcription polymerase chain reaction (RT-PCR) test-positive individuals and corresponding date-matched symptomatic test-negative controls. Major SARS-CoV-2 variants (Index/wild type, Alpha, Delta and Omicron) were defined using periods of predominance. Risk differences (RDs) were estimated for each of 21 predefined acute symptoms comparing: (1) test-positive and -negative individuals, by variant period, (2) vaccinated and unvaccinated test-positives, by variant period, (3) individuals tested positive during the Omicron and Delta periods, by vaccination status, and (4) vaccinated Omicron test-positive and -negative individuals, by age and sex. Compared to pre-Omicron, RDs between test-positive and test-negative individuals during the Omicron period were lower for most symptoms. RDs for altered sense of smell (dysosmia) and taste (dysgeusia) were highest for Delta (RD = 50.8 (49.4-52.0) and RD = 54.7 (53.4-56.0), respectively) and lowest for Omicron (RD = 12.8 (12.1-13.5) and RD = 11.8 (11.1-12.4), respectively). Across variants, vaccinated individuals reported fewer symptoms. During Omicron, females and 30-59 year-old participants reported more symptoms.

Post-acute symptoms 4 months after SARS-CoV-2 infection during the Omicron period: a nationwide Danish questionnaire study.

Post-acute symptoms are not uncommon after SARS-CoV-2 infection with pre-Omicron variants. How Omicron and COVID-19 booster vaccination influence the risk of post-acute symptoms is less clear. We analyzed data from the nationwide Danish questionnaire study EFTER-COVID comprising 44,553 individuals ≥15 years old, tested between July 2021 and January 2022, in order to evaluate the association of the Omicron variant and COVID-19 booster vaccination with post-acute symptoms and new-onset general health problems, four months after infection with SARS-CoV-2. Risk differences (RDs) were estimated by comparing Omicron -cases to controls, Omicron to Delta -cases, and Omicron vaccinated cases with three to -two doses, adjusted for age, sex, BMI, self-reported chronic diseases, Charlson comorbidity index, healthcare occupation, and vaccination status. Four months after testing for SARS-CoV-2 during the Omicron period, cases experienced substantial post-acute symptoms and new-onset health problems compared to controls; the largest RD was observed for memory issues (RD=7.2%, 95%CI: 6.4 to 8.1). However, risks were generally lower than in the Delta period, particularly for dysosmia (RD=-15.0%, 95%CI: -17.0 to -13.2) and dysgeusia (RD=-11.2%, 95%CI: -13.2 to -9.5). Booster vaccination was associated with fewer post-acute symptoms and new-onset health problems, four months after Omicron infection, compared to two COVID-19 vaccine doses.

A nationwide questionnaire study of post-acute symptoms and health problems after SARS-CoV-2 infection in Denmark.

A considerable number of individuals infected with SARS-CoV-2 continue to experience symptoms after the acute phase. Here, we report findings from a nationwide questionnaire study in Denmark including 61,002 RT-PCR confirmed SARS-CoV-2 cases and 91,878 test-negative controls aged 15-years or older. Six to twelve months after the test, the risks of 18 out of 21 symptoms were elevated among test-positives. The largest adjusted risk differences (RD) were observed for dysosmia (RD = 10.92%, 95% CI 10.68-11.21%), dysgeusia (RD = 8.68%, 95% CI 8.43-8.93%), fatigue/exhaustion (RD = 8.43%, 95%CI 8.14-8.74%), dyspnea (RD = 4.87%, 95% CI 4.65-5.09%) and reduced strength in arms/legs (RD = 4.68%, 95% CI 4.45-4.89%). During the period from the test and until completion of the questionnaire, new diagnoses of anxiety (RD = 1.15%, 95% CI 0.95-1.34%) or depression (RD = 1.00%, 95% CI 0.81-1.19%) were also more common among test-positives. Even in a population where the majority of test-positives were not hospitalized, a considerable proportion experiences symptoms up to 12 months after infection. Being female or middle-aged increases risks.

Personal exposure to radio-frequency electromagnetic fields in Europe: Is there a generation gap?

BACKGROUND: Exposure to radiofrequency electromagnetic fields (RF-EMF) from mobile communication technologies is changing rapidly. To characterize sources and associated variability, we studied the differences and correlations in exposure patterns between children aged 8 to 18 and their parents, over the course of the day, by age, by activity pattern, and for different metrics of exposure. METHODS: Using portable RF-EMF measurement devices, we collected simultaneous real-time personal measurements of RF-EMF over 24 to 72 h in 294 parent-child pairs from Denmark, the Netherlands, Slovenia, Switzerland, and Spain. The devices measured the power flux density (mW/m2) in 16 different frequency bands every 4 s, and activity diary Apps kept by the participants were used to collect time-activity information in real-time. We analyzed their exposures by activity, for the different source constituents of exposure: downlink (radiation emitted from mobile phone base stations), uplink (transmission from phone to base station), broadcast, DECT (digital enhanced cordless telecommunications) and Wi-Fi. We looked at the correlations between parents and children overall, during day (06:00-22.00) and night (22:00-06:00) and while spending time at home. RESULTS: The mean of time-weighted average personal exposures was 0.16 mW/m2 for children and 0.15 mW/m2 for parents, on average predominantly originating from downlink sources (47% for children and 45% for parents), followed by uplink (18% and 27% respectively) and broadcast (25% and 19%). On average, exposure for downlink and uplink were highest during the day, and for Wi-Fi and DECT during the evening. Exposure during activities where most of the time is spent (home, school and work) was relatively low whereas exposure during travel and outside activities was higher. Exposure to uplink increased with age among young people, while DECT decreased slightly. Exposure to downlink, broadcast, and Wi-Fi showed no obvious trend with age. We found that exposure to total RF-EMF is correlated among children and their parents (Rspearman = 0.45), especially while at home (0.62) and during the night (0.60). Correlations were higher for environmental sources such as downlink (0.57) and broadcast (0.62) than for usage-related exposures such as uplink (0.29). CONCLUSION: The generation gap between children and their parents is mostly evident in uplink exposure, due to more and longer uplink and cordless phone calls among parents, and their tendency to spend slightly more time in activities with higher environmental RF-EMF exposure, such as travel. Despite these differences in personal behavior, exposure to RF-EMF is moderately correlated between children and their parents, especially exposures resulting from environmental RF-EMF sources.

Spatial and temporal variability of personal environmental exposure to radio frequency electromagnetic fields in children in Europe.

BACKGROUND: Exposure to radiofrequency electromagnetic fields (RF-EMF) has rapidly increased and little is known about exposure levels in children. This study describes personal RF-EMF environmental exposure levels from handheld devices and fixed site transmitters in European children, the determinants of this, and the day-to-day and year-to-year repeatability of these exposure levels. METHODS: Personal environmental RF-EMF exposure (µW/m2, power flux density) was measured in 529 children (ages 8-18 years) in Denmark, the Netherlands, Slovenia, Switzerland, and Spain using personal portable exposure meters for a period of up to three days between 2014 and 2016, and repeated in a subsample of 28 children one year later. The meters captured 16 frequency bands every 4 s and incorporated a GPS. Activity diaries and questionnaires were used to collect children's location, use of handheld devices, and presence of indoor RF-EMF sources. Six general frequency bands were defined: total, digital enhanced cordless telecommunications (DECT), television and radio antennas (broadcast), mobile phones (uplink), mobile phone base stations (downlink), and Wireless Fidelity (WiFi). We used adjusted mixed effects models with region random effects to estimate associations of handheld device use habits and indoor RF-EMF sources with personal RF-EMF exposure. Day-to-day and year-to-year repeatability of personal RF-EMF exposure were calculated through intraclass correlations (ICC). RESULTS: Median total personal RF-EMF exposure was 75.5 µW/m2. Downlink was the largest contributor to total exposure (median: 27.2 µW/m2) followed by broadcast (9.9 µW/m2). Exposure from uplink (4.7 µW/m2) was lower. WiFi and DECT contributed very little to exposure levels. Exposure was higher during day (94.2 µW/m2) than night (23.0 µW/m2), and slightly higher during weekends than weekdays, although varying across regions. Median exposures were highest while children were outside (157.0 µW/m2) or traveling (171.3 µW/m2), and much lower at home (33.0 µW/m2) or in school (35.1 µW/m2). Children living in urban environments had higher exposure than children in rural environments. Older children and users of mobile phones had higher uplink exposure but not total exposure, compared to younger children and those that did not use mobile phones. Day-to-day repeatability was moderate to high for most of the general frequency bands (ICCs between 0.43 and 0.85), as well as for total, broadcast, and downlink for the year-to-year repeatability (ICCs between 0.49 and 0.80) in a small subsample. CONCLUSION: The largest contributors to total personal environmental RF-EMF exposure were downlink and broadcast, and these exposures showed high repeatability. Urbanicity was the most important determinant of total exposure and mobile phone use was the most important determinant of uplink exposure. It is important to continue evaluating RF-EMF exposure in children as device use habits, exposure levels, and main contributing sources may change.