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Post COVID-19 condition (PCC) is defined as ongoing symptoms at ≥1 month after acute COVID-19. We investigated the risk of PCC in an international cohort according to viral variants. We included 7699 hospitalized patients in six centers (January 2020-June 2023); a subset of participants with ≥1 visit over the year after clinical recovery were analyzed. Variants were observed or estimated using Global Data Science Initiative (GISAID) data. Because patients returning for a post COVID-19 visit may have a higher PCC risk, and because the variant could be associated with the probability of returning, we used weighted logistic regressions. We estimated the proportion of the effect of wild-type (WT) virus vs. Omicron on PCC, which was mediated by Intensive Care Unit (ICU) admission, through a mediation analysis. In total, 1317 patients returned for a post COVID visit at a median of 2.6 (IQR 1.84-3.97) months after clinical recovery. WT was present in 69.6% of participants, followed by the Alpha (14.4%), Delta (8.9%), Gamma (3.9%) and Omicron strains (3.3%). Among patients with PCC, the most common manifestations were fatigue (51.7%), brain fog (32.7%) and respiratory symptoms (37.2%). Omicron vs. WT was associated with a reduced risk of PCC and PCC clusters; conversely, we observed a higher risk with the Delta and Alpha variants vs. WT. In total, 42% of the WT effect vs. Omicron on PCC risk appeared to be mediated by ICU admission. A reduced PCC risk was observed after Omicron infection, suggesting a possible reduction in the PCC burden over time. A non-negligible proportion of the variant effect on PCC risk seems mediated by increased disease severity during the acute disease.

Objectives: We investigated the impact of school reopening on SARS-CoV-2 transmission in Italy, Germany, and Portugal in autumn 2022 when the Omicron variant was prevalent., Methods: A prospective international study was conducted using the case reproduction number (R c ) calculated with the time parametrization of Omicron. For Germany and Italy, staggered difference-in-differences analysis was employed to explore the causal relationship between school reopening and R c changes, accounting for varying reopening dates. In Portugal, interrupted time series analysis was used due to simultaneous school reopenings. Multivariable models were adopted to adjust for confounders., Results: In Italy and Germany, post-reopening R c estimates were significantly lower compared to those from regions/states that had not yet reopened at the same time points, both in the student population (overall average treatment effect for the treated subpopulation [O-ATT]: -0.80 [95% CI: -0.94;-0.66] for Italy; O-ATT-0.30 [95% CI: -0.36;-0.23] for Germany) and the adult population (O-ATT: -0.04 [95% CI: -0.07;-0.01] for Italy; O-ATT: -0.07 [95% CI: -0.11;-0.03] for Germany). In Portugal, there was a significant decreasing trend in R c following school reopenings compared to the pre-reopening period (sustained effect: -0.03 [95% CI: -0.04; -0.03] in students; -0.02 [95% CI: -0.03; -0.02] in adults)., Conclusions: We found no evidence of a causal relationship between school reopenings in autumn 2022 and Omicron SARS-CoV-2 transmission., Competing Interests: Declaration of competing interest The authors have no competing interests to declare., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), the virus responsible for coronavirus disease 2019 (COVID-19), can lead to hospitalisation, particularly in elderly, immunocompromised, and non-vaccinated or partially vaccinated individuals. Although vaccination provides protection, the duration of this protection wanes over time. Additional doses can restore immunity, but the influence of viral variants, specific sequences, and vaccine-induced immune responses on disease severity remains unclear. Moreover, the efficacy of therapeutic interventions during hospitalisation requires further investigation. The study aims to analyse the clinical course of COVID-19 in hospitalised patients, taking into account SARS-CoV-2 variants, viral sequences, and the impact of different vaccines. The primary outcome is all-cause in-hospital mortality, while secondary outcomes include admission to intensive care unit and length of stay, duration of hospitalisation, and the level of respiratory support required., Methods: This ongoing multicentre study observes hospitalised adult patients with confirmed SARS-CoV-2 infection, utilising a combination of retrospective and prospective data collection. It aims to gather clinical and laboratory variables from around 35,000 patients, with potential for a larger sample size. Data analysis will involve biostatistical and machine-learning techniques. Selected patients will provide biological material. The study started on October 14, 2021 and is scheduled to end on October 13, 2026., Discussion: The analysis of a large sample of retrospective and prospective data about the acute phase of SARS CoV-2 infection in hospitalised patients, viral variants and vaccination in several European and non-European countries will help us to better understand risk factors for disease severity and the interplay between SARS CoV-2 variants, immune responses and vaccine efficacy. The main strengths of this study are the large sample size, the long study duration covering different waves of COVID-19 and the collection of biological samples that allows future research., Trial Registration: The trial has been registered on ClinicalTrials.gov. The unique identifier assigned to this trial is NCT05463380., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Post-COVID-19 condition refers to persistent or new onset symptoms occurring three months after acute COVID-19, which are unrelated to alternative diagnoses. Symptoms include fatigue, breathlessness, palpitations, pain, concentration difficulties ("brain fog"), sleep disorders, and anxiety/depression. The prevalence of post-COVID-19 condition ranges widely across studies, affecting 10-20% of patients and reaching 50-60% in certain cohorts, while the associated risk factors remain poorly understood., Methods: This multicentre cohort study, both retrospective and prospective, aims to assess the incidence and risk factors of post-COVID-19 condition in a cohort of recovered patients. Secondary objectives include evaluating the association between circulating SARS-CoV-2 variants and the risk of post-COVID-19 condition, as well as assessing long-term residual organ damage (lung, heart, central nervous system, peripheral nervous system) in relation to patient characteristics and virology (variant and viral load during the acute phase). Participants will include hospitalised and outpatient COVID-19 patients diagnosed between 01/03/2020 and 01/02/2025 from 8 participating centres. A control group will consist of hospitalised patients with respiratory infections other than COVID-19 during the same period. Patients will be followed up at the post-COVID-19 clinic of each centre at 2-3, 6-9, and 12-15 months after clinical recovery. Routine blood exams will be conducted, and patients will complete questionnaires to assess persisting symptoms, fatigue, dyspnoea, quality of life, disability, anxiety and depression, and post-traumatic stress disorders., Discussion: This study aims to understand post-COVID-19 syndrome's incidence and predictors by comparing pandemic waves, utilising retrospective and prospective data. Gender association, especially the potential higher prevalence in females, will be investigated. Symptom tracking via questionnaires and scales will monitor duration and evolution. Questionnaires will also collect data on vaccination, reinfections, and new health issues. Biological samples will enable future studies on post-COVID-19 sequelae mechanisms, including inflammation, immune dysregulation, and viral reservoirs., Trial Registration: This study has been registered with ClinicalTrials.gov under the identifier NCT05531773., (© 2023. BioMed Central Ltd., part of Springer Nature.)

The EuResist cohort was established in 2006 with the purpose of developing a clinical decision-support tool predicting the most effective antiretroviral therapy (ART) for persons living with HIV (PLWH), based on their clinical and virological data. Further to continuous extensive data collection from several European countries, the EuResist cohort later widened its activity to the more general area of antiretroviral treatment resistance with a focus on virus evolution. The EuResist cohort has retrospectively enrolled PLWH, both treatment-naïve and treatment-experienced, under clinical follow-up from 1998, in nine national cohorts across Europe and beyond, and this article is an overview of its achievement. A clinically oriented treatment-response prediction system was released and made available online in 2008. Clinical and virological data have been collected from more than one hundred thousand PLWH, allowing for a number of studies on the response to treatment, selection and spread of resistance-associated mutations and the circulation of viral subtypes. Drawing from its interdisciplinary vocation, EuResist will continue to investigate clinical response to antiretroviral treatment against HIV and monitor the development and circulation of HIV drug resistance in clinical settings, along with the development of novel drugs and the introduction of new treatment strategies. The support of artificial intelligence in these activities is essential.