Joana Pinto Costa

Purpose: To estimate the time to resolution of COVID-19 symptoms and identify associated factors among COVID-19 patients. Methods : A prospective study was conducted with 2777 adults identified with SARS-CoV-2 infection between March and December 2020 at the Centro Hospitalar Universitário de São João. Data collected between November 2020 and April 2021 included sociodemographic, clinical, and infection-related variables. We used survival analysis to estimate the time until symptom resolution, and Cox regression identified associated factors using crude (HR) and adjusted hazard ratios (aHR). Results : Symptom resolution was not experienced by 36.5% of participants within the study period. Higher hazards of symptom resolution were observed among males [aHR:1.55, 95% Confidence Interval (CI):1.41–1.70], those with master/doctoral education (aHR:1.29, 95% CI:1.08–1.54), and better income perception. Lower hazards were seen in adults aged 40–49 (HR:0.79, 95% CI:0.68–0.93) and 50–59 (HR:0.76, 95% CI:0.65–0.90), individuals with comorbidities (aHR:0.83, 95% CI:0.74–0.92), and those hospitalised during the acute phase (aHR:0.71, 95% CI:0.61–0.82). Conclusions : Over one-third of COVID-19 patients had unresolved symptoms months post-infection. Middle age, female sex, lower education, poor income perception, comorbidities, and hospitalisation in the acute phase were the most significant predictors for non-resolving symptoms, underscoring the need for targeted interventions.

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.

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.

Repeated serosurveys in the same population provide more accurate estimates of the frequency of SARS-CoV-2 infection and more comparable data over time than notified cases. We aimed to estimate the...

Introduction Incidence based on notified cases of SARS-CoV-2 infection underestimates the real extension of the infection. We aimed to quantify SARS-CoV-2 specific antibodies’ seroprevalence among University students in Porto. Methods A rapid point of care testing for SARS-CoV-2 specific immunoglobulin (Ig) M and IgG antibodies was performed, and a questionnaire was applied to the 6512 voluntary students from September to December 2020. We computed the apparent IgM, IgG and IgM or IgG prevalence, and the true prevalence and 95% credible intervals (95% CI) using Bayesian inference. Results We found an apparent prevalence (IgM or IgG) of 9.7%, the true prevalence being 7.9% (95% CI 4.9-11.1). Prevalence was significantly higher among males (10.9% vs 9.2%), international students (18.1% vs 10.4% local vs 8.8% nationally displaced) and increased with age. Those with a known risk contact, that experienced quarantine, had symptoms, or a previous negative molecular test had a higher seroprevalence. Of the 91 (1.4%) students who reported a molecular diagnosis, 86.7% were reactive for IgM or IgG. Conclusion Based on immunological evidence infection was 5.6 times more frequent than if based on a molecular diagnosis. The higher seroprevalence among male, older, and international students emphasizes the importance of identifying particular groups.

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.

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.