ABSTRACT
BACKGROUND The aim of this multinational study was to assess the development of adverse mental health symptoms among individuals diagnosed with COVID-19 in the general population by acute infection severity up to 16 months after diagnosis. METHODS Participants consisted of 247 249 individuals from seven cohorts across six countries (Denmark, Estonia, Iceland, Norway, Scotland, and Sweden) recruited from April 2020 through August 2021. We used multivariable Poisson regression to contrast symptom-prevalence of depression, anxiety, COVID-19 related distress, and poor sleep quality among individuals with and without a diagnosis of COVID-19 at entry to respective cohorts by time (0-16 months) from diagnosis. We also applied generalised estimating equations (GEE) analysis to test differences in repeated measures of mental health symptoms before and after COVID-19 diagnosis among individuals ever diagnosed with COVID-19 over time. FINDINGS A total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1.18, 95% confidence interval [95% CI] 1.03-1.36) and poorer sleep quality (1.13, 1.03-1.24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0.83, 95% CI 0.75-0.91 and 0.77, 0.63-0.94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1.61, 95% CI 1.27-2.05 and 1.43, 1.26-1.63, respectively) throughout the 16-month study period. CONCLUSION Acute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.
Subject(s)
COVID-19 , Acute Disease , Anxiety Disorders , Depressive DisorderABSTRACT
Background: The pandemic due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has tremendous consequences for our societies. Knowledge of the seroprevalence of SARS-CoV-2 is needed to accurately monitor the spread of the epidemic and also to calculate the infection fatality rate (IFR). These measures may help the authorities to make informed decisions and adjust the current societal interventions. Blood donors comprise approximately 4.7% of the similarly aged population of Denmark and blood is donated in all areas of the country. The objective of this study was to perform real-time seroprevalence surveying among blood donors as a tool to estimate previous SARS-CoV-2 infections and the population based IFR. Methods: All Danish blood donors aged 17-69 years giving blood April 6 to 17 were tested for SARS-CoV-2 immunoglobulin M and G antibodies using a commercial lateral flow test. Antibody status was compared between areas and an estimate of the IFR was calculated. The seroprevalence was adjusted for assay sensitivity and specificity taking the uncertainties of the test validation into account when reporting the 95% confidence intervals (CI). Results: The first 9,496 blood donors were tested and a combined adjusted seroprevalence of 1.7% (CI: 0.9-2.3) was calculated. The seroprevalence differed across areas. Using available data on fatalities and population numbers a combined IFR in patients younger than 70 is estimated at 82 per 100,000 (CI: 59-154) infections. Conclusions: The IFR was estimated to be slightly lower than previously reported from other countries not using seroprevalence data. The IFR, including only individuals with no comorbidity, is likely several fold lower than the current estimate. This may have implications for risk mitigation. We have initiated real-time nationwide anti-SARS-CoV-2 seroprevalence surveying of blood donations as a tool in monitoring the epidemic.