Francesca Incardona

Background: The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to pose significant public health challenges globally. This study focuses on the surveillance and discovery of SARS-CoV-2 variants in schools in Portugal and Italy, emphasizing the importance of monitoring variant spread in educational settings. Methods: We used a non-invasive, Lolli-Method for pooled saliva sampling and RT-qPCR among students across various educational settings, between November 2022 and March 2024. Pooled sampling was performed twice a week as part of routine school activities without medical personnel. In case a class tested positive, a round of individual Lolli testing was carried out in that class on the following day. Sequencing was performed through Sanger and NGS sequencing. Sequencing data analysis was performed using SeqMan, Nextclade, MAFFT alignment, comparison with GISAID sequences, and IQ-TREE 2 for phylogenetic analysis. Findings: A total of 5·191 samples were collected, including 2·171 (41·8%) from Portugal and 3·020 (58·2%) from Italy. Portugal showed higher positivity rates for both individual (8·85%) and pooled samples (5·47%). Of the 73 sequenced samples, 23 were from Portugal and 50 from Italy. Twelve distinct variants were detected, with XBB.1.5 (36%) and CH.1.1 (20%) being the most prevalent. Variants FL.14 and HU.1.1 were detected specifically in children in our study. Variant JN.1 was detected circulating in schools two months earlier than it was first reported in Denmark.Interpretation: The Lolli-Method proved effective for school-based surveillance and early detection of emerging variants and other infectious threats.

Background: Although coronavirus disease 2019 (COVID-19) is no longer a public health emergency, it remains the most prevalent circulating infectious-like illness in Europe. Whether immunocompromising conditions (ICCs) still carry increased mortality risk during the Omicron era is unclear. Methods: We conducted a cohort study across EuCARE sites in 8 countries among adults admitted to hospital with COVID-19 between 2020 and 2023. ICCs and COVID-19 pneumonia at hospitalization were defined using clinical information and ICD-10 codes. Logistic regression and counterfactual mediation analysis was used to compare 28-day in-hospital mortality risk associated with ICCs using COVID-19 pneumonia and vaccination at hospital entry as intermediates. Proportion of the total effect of ICCs mediated and the controlled direct effects (CDEs) were calculated. We also formally tested for interaction between SARS-CoV-2 variants and ICCs for mortality risk. Results: A total of 42 488 individuals were included, of whom 1675 (3.9%) had an ICC. Fifty-five percent were male, and the median age was 67 (IQR, 52–79) years. Overall, 4344 (10.2%) individuals died in hospital. ICCs were associated with increased mortality (OR, 1.49 [95% CI, 1.25–1.79]), with no evidence for an attenuation during the Omicron phase (P value for interaction = .60). Mediation analyses showed that the total effect of ICCs was mediated by vaccination but only weakly by pneumonia. With Omicron, the excess mortality associated with ICC was higher under the scenario that everyone in the cohort was to develop COVID-19 pneumonia (CDE, 1.22 [95% CI, .09–1.65]). Conclusions: ICC remains a significant risk factor for in-hospital death, even during the Omicron era, particularly if the infection led to the development of pneumonia.

Background: Limited evidence exists on how bacterial and viral coinfections have developed since the SARS-CoV-2 Omicron variant emerged. We investigated whether community-onset coinfections in adult patients hospitalized with COVID-19 differed during the wild type, Alpha, Delta, and Omicron periods and whether such coinfections were associated with an increased risk of mortality. Methods: We conducted a multinational cohort study including COVID-19 hospitalizations until 30 April 2023 in 5 European countries. The outcome was bacterial and viral coinfections based on 5 test modalities. Variant periods were compared with regard to occurrences of coinfections and risk ratios for coinfections (Omicron vs pre-Omicron), as well as association with in-hospital mortality (Omicron vs pre-Omicron). Results: A total of 29 564 cases were included: 12 601 wild type, 5256 Alpha, 2433 Delta, and 9274 Omicron. The coinfection rate was 2.6% (327/12 601) for wild type, 2.0% (105/5256) for Alpha, 3.2% (77/2433) for Delta, and 7.9% (737/9274) for Omicron. Omicron had a significantly increased risk ratio of coinfection when compared with preceding variants (1.88 [95% CI, 1.53–2.32], P < .001). These results were consistent across several subgroup analyses. An increased occurrence (19% [232/1246] vs 11% [3042/28 318]) and adjusted risk (1.69 [95% CI, 1.49–1.91], P < .001) of in-hospital mortality were observed in patients with a verified coinfection as compared with patients without a coinfection. Conclusions: Bacterial and viral coinfections were more prevalent during the Omicron period as compared with preceding variants. Such coinfections were associated with an increased risk of in-hospital mortality, calling for sustained monitoring and clinical vigilance.

Introduction: Few data are currently available on the nonnucleoside reverse transcriptase (RT) inhibitors (NNRTI) resistance mutations selected in persons living with HIV-1 (PLWH) who develop virological failure while receiving rilpivirine (RPV). Methods: We analyzed pooled HIV-1 RT genotypic data from 280 PLWH in the multicenter EuResist database and 115 PLWH in the Stanford HIV Drug Resistance Database (HIVDB) who received RPV as their only NNRTI. Results: Among the 395 PLWH receiving RPV, 180 (45.6%) had one or more NNRTI-associated DRMs. Overall, 44 NNRTI-associated DRMs were identified, including 26 that occurred in two or more PLWHs. Seven mutations had a prevalence ≥10% among the 180 PLWH with one or more NNRTI-associated DRM: E138K (32.2%), V90I (25.0%), K101E (17.8%), Y181C (17.2%), E138A (13.9%), H221Y (12.2%), and K103N (10.6%). Y181C was significantly more likely to co-occur with K101E, V179F, H221Y, and M230L. Ten novel non-polymorphic mutations at known NNRTI-associated mutation positions were also identified, usually in just one PLWH: L100F, V108A, T139I, P225S, M230V, Y232C, and T240A/I/M/S. Conclusions: Our analysis extends the spectrum of mutations emerging in PLWH receiving RPV. Additional phenotypic characterization of RPV-selected mutations is necessary to better understand their biological and possible clinical significance.

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.

Background: Investigating the role of late presenters (LPs) in HIV-1 transmission is important, as they can contribute to the onward spread of HIV-1 virus before diagnosis, when they are not aware of their HIV status. Objective: To characterize individuals living with HIV-1 followed up in Europe infected with subtypes A, B, and G and to compare transmission clusters (TC) in LP vs. non-late presenter (NLP) populations. Methods: Information from a convenience sample of 2679 individuals living with HIV-1 was collected from the EuResist Integrated Database between 2008 and 2019. Maximum likelihood (ML) phylogenies were constructed using FastTree. Transmission clusters were identified using Cluster Picker. Statistical analyses were performed using R. Results: 2437 (91.0%) sequences were from subtype B, 168 (6.3%) from subtype A, and 74 (2.8%) from subtype G. The median age was 39 y/o (IQR: 31.0–47.0) and 85.2% of individuals were males. The main transmission route was via homosexual (MSM) contact (60.1%) and 85.0% originated from Western Europe. In total, 54.7% of individuals were classified as LPs and 41.7% of individuals were inside TCs. In subtype A, individuals in TCs were more frequently males and natives with a recent infection. For subtype B, individuals in TCs were more frequently individuals with MSM transmission route and with a recent infection. For subtype G, individuals in TCs were those with a recent infection. When analyzing cluster size, we found that LPs more frequently belonged to small clusters (<8 individuals), particularly dual clusters (2 individuals). Conclusion: LP individuals are more present either outside or in small clusters, indicating a limited role of late presentation to HIV-1 transmission.

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.