In 2020, the COVID-19 pandemic exhausted healthcare systems around the world, including European Union countries, with healthcare workers at the frontline. Therefore, new health laws and policies have been introduced at the national level in order to offer greater legal protection for health workers. Since the introduction of COVID-19 vaccination, it has led to the development of specific laws to define the compulsoriness for particular categories. This review aimed to evaluate the system of medical liability, focusing on the ten countries of the European Union with the highest rate of vaccination coverage against SARS-CoV-2. A country-by-country analysis was conducted on the different medical liability systems of individual professionals, in general, and with specific focus on the vaccinating doctors. Additional search was conducted to investigate which European states have introduced specific policies in this field, to identify the implementation of any new laws alongside the COVID-19 vaccination campaigns, and to assess which countries have adopted the European Digital COVID Certificate and funded specific compensation programs for COVID-19 vaccination. Our results highlight an extremely fragmented European scenario; therefore, this work could be a starting point to define a common approach for medical liability and related policies in the COVID-19 pandemic.

Summary: The long‐term effects of severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) infection on sleep remain poorly known. We evaluated the association between probable post‐COVID‐19 condition and changes in sleep quality and quantity before and after SARS‐CoV‐2 infection in a consecutive sample of non‐hospitalized adults. Individuals were identified with SARS‐CoV‐2 infection in 2020 at the central laboratory of a tertiary hospital in Porto and followed as outpatients. We included patients diagnosed with SARS‐CoV‐2 infection ≥3 months before this evaluation, with no missing data on key variables (n = 2445). Participants completed a questionnaire that included sociodemographic, clinical, and infection‐related questions. We computed changes in sleep‐related parameters referred to 1 month before diagnosis and 1 week before the questionnaire. Multinomial logistic regression models were fitted to compute crude and adjusted odds ratios and 95% confidence intervals (95% CIs). Compared to the pre‐infection period, those with probable post‐COVID‐19 condition reported a greater decrease in hours of sleep, had a 2.60 (95% CI 2.02–3.34) higher adjusted odds of perceiving their sleep quality as worsened and experienced a significant increase in number of days with sleeping disturbances as defined according to multiple items. The association between post‐COVID‐19 condition and indicators of poor sleep health requires special attention from healthcare professionals and services. It is essential that appropriate multidisciplinary care is provided to mitigate the physical, psychological, social, and professional impact of sleeping problems in these already burdened patients.

Assessing the accuracy of serological tests for SARS-CoV-2 was challenging due to the lack of a gold standard. This study aimed to estimate the accuracy of SARS-CoV-2-specific serological tests using Bayesian latent class models (BLCM) and compare methods with and without a gold standard. In this study, we analyzed 356 samples-254 positives, ie, from individuals with a previous SARS-CoV-2 infection diagnosis, and 102 negatives, ie, prepandemic samples-using six different rapid serological tests and one laboratory assay. A BLCM was employed to concurrently estimate the sensitivity and specificity of all serological tests for the immunoglobulin (Ig) M and IgG antibodies specific for SARS-CoV-2. Noninformative priors were used. A sensitivity analysis was conducted considering three methods: 1) reverse transcription-polymerase chain reaction test (RT-PCR) as the gold standard, 2) BLCM with RT-PCR as an imperfect gold standard, and 3) frequentist latent class model (LCM). All analyses used software R version 4.3.0, and BLCM were fitted using package runjags using the software JAGS (Just Another Gibbs Sampler). The BLCM-derived sensitivity for IgM varied from 10.7% [95% credibility interval (CrI):1.9-24.6] to 96.9% (95% CrI: 91.0-100.0), with specificities ranging from 48.3% (95% CrI: 39.0-57.6) to 98.9% (95% CrI: 96.2-100.0). Sensitivity for IgG varied between 76.9% (95% CrI: 68.2-84.7) and 99.1% (95% CrI: 96.1-100.0), and specificity ranged from 49.9% (95% CrI: 19.4-95.8) to 99.3% (95% CrI: 97.2-100.0). LCM results were comparable to BLCM. Considering the RT-PCR as a gold standard underestimated the tests' sensitivity, particularly for IgM. BLCM-derived results deviated from those using a gold standard, which underestimated the tests' characteristics, particularly sensitivity. Although Bayesian and frequentist LCM approaches yielded comparable results, BLCM had the benefit of enabling credibility interval computation even when sample power is limited.

Objectives To assess the prevalence of SARS-CoV-2 specific immunoglobulin (Ig) M and IgG antibodies among workers of the three public higher education institutions of Porto, Portugal, up to July 2020. Methods A rapid point of care test for specific IgM and IgG antibodies of SARS-CoV-2 was offered to all workers. Testing was performed to and a questionnaire was completed by 4592 workers on a voluntary basis. We computed the apparent IgM, IgG, and combined IgM or IgG prevalence, along with the true prevalence and 95% credible intervals (95% CI) using Bayesian inference. Results We found an apparent prevalence of 3.1% for IgM, 1.0% for IgG, and 3.9% for either antibody class. The estimated true prevalence was 2.0% (95% CI 0.1-4.3) for IgM, 0.6% (95% CI 0.0-1.3) for IgG and 2.5% (95% CI 0.1-5.3) for IgM or IgG. A SARS-CoV-2 molecular diagnosis was reported by 21 (0.5%) workers, and of these, 90.5% had a reactive IgG result. Seroprevalence was higher among those reporting known contacts with confirmed cases, having been quarantined, having a previous molecular negative test, or having had symptoms. Conclusions The seroprevalence among workers from the three public higher education institutions of Porto after the first wave of the SARS-CoV-2 infection was relatively low. However, the estimated true seroprevalence was approximately five times higher than the reported SARS-CoV-2 infection based on a molecular test result.

Caloric restriction has been associated with improved cardiometabolic health. Available data in humans are commonly based on short follow-up periods, specific diets, or population groups. We hypothesized that participants of a population-based cohort (Epidemiological Health Investigation of Teenagers in Porto) with a dietary pattern characterized by a lower energy intake during adolescence have a better cardiometabolic profile in adolescence and young adulthood than other dietary patterns. At aged 13 and 21 year evaluations, diet, anthropometric, and cardiometabolic measures were assessed. Diet was assessed through a food frequency questionnaire and, at 13 years, summarized in dietary patterns identified by cluster analysis. The lower intake dietary pattern included 40% of the participants. The energy intake misreport was estimated using the Goldberg method. Analysis of variance and analysis of covariance were used to compare cardiometabolic risk factors according to dietary patterns. The mean energy intake was 2394 and 2242 Kcal/d for the total sample at aged 13 years (n = 962) and 21 years (n = 862), respectively. Those belonging to the lower intake dietary pattern showed a 25% and 5% lower energy intake, respectively. In the cross-sectional analysis at aged 13, adolescents belonging to the lower intake dietary pattern presented lower glucose, insulin, triglycerides, and blood pressure values after adjusting for body mass index and parents' education level. Among the plausible reporters, differences were only statistically significant for glucose and systolic blood pressure. Our data support that a dietary pattern characterized by a lower energy intake may contribute to a better cardiometabolic profile in adolescents. However, no significant effect was found in young adulthood.

Background Repeated serosurveys in the same population provide more accurate estimates of the frequency of SARS-CoV-2 infection and more comparable data than notified cases. We aimed to estimate the incidence of SARS-CoV-2 infection, identify associated risk factors, and assess time trends in the ratio of serological/molecular diagnosis in a cohort of university workers. Methods Participants had a serological rapid test for SARS-CoV-2 Immunoglobulins M and G, and completed a questionnaire, in May-July 2020 (n=3628) and November 2020–January 2021 (n=2661); 1960 participated in both evaluations and provided data to compute the incidence proportion and the incident rate. Crude and adjusted incidence rate ratios (aIRR) and 95% confidence intervals (CI) were computed using generalised linear models with Poisson regression. Results The incidence rate was 1.8/100 person-month (95%CI 1.6-2.1), and the 6 months’ cumulative incidence was 10.7%. The serological/molecular diagnosis ratio was 10:1 in the first evaluation and 3:1 in the second. Considering newly identified seropositive cases at the first (n=69) and second evaluation (n=202), 29.0% and 9.4% never reported symptoms, respectively, 14.5% and 33.3% reported contact with a confirmed case and 82.6%, and 46.0% never had a molecular test. Males (aIRR: 0.59; 95%CI: 0.42-0.83) and “high-skilled white-collar” workers (aIRR: 0.73, 95%CI: 0.52-1.02) had lower incidence of infection. Conclusion University workers presented a high SARS-CoV-2 incidence while restrictive measures were in place. The time decrease in the proportion of undiagnosed cases reflected the increased access to testing, but opportunities continued to be missed, even in the presence of COVID-19 like symptoms. What is already known on this subject The median ratio of seroprevalence to the corresponding cumulative incidence is 18, however, there is great variability between studies. Seroprevalence studies are essential to estimate the true burden of the infection. Few cohort studies focused on essential non-healthcare workers, such as university workers. What this study adds This longitudinal seroprevalence study among university workers found a SARS-CoV-2-specific IgM or IgG incidence rate of 1.8/100 person-month, and a 6 months’ cumulative incidence of 10.7%. The undiagnosed fraction was 3:1 in the second evaluation, representing a decrease from a 10:1 in the first evaluation in the same population showing that a gap to test-trace-isolate remained in this highly educated working population. Seropositive participants were mostly pauci- or symptomatic with no known contact with a COVID-19 confirmed case; “high-skilled white-collar” workers were at lower risk of being an incident seropositive case.