• Publicationsclose
• 2018-2022close
• Preprint close
• English close
• Hyper Article en Ligne close
• Hyper Article en Ligne - Sciences de l'Homme et de la Société close
• COVID-19 close

Online ahead of print.; International audience; We analysed the influenza epidemic that occurred in Australia during the 2022 winter using an age-structured dynamic transmission model, which accounts for past epidemics to estimate the population susceptibility to an influenza infection. We applied the same model to five European countries. Our analysis suggests Europe might experience an early and moderately large influenza epidemic. Also, differences may arise between countries, with Germany and Spain experiencing larger epidemics, than France, Italy and the United Kingdom, especially in children.

AbstractInvestigating the role of host genetic factors in COVID-19 severity and susceptibility can inform our understanding of the underlying biological mechanisms that influence adverse outcomes and drug development1,2. Here we present a second updated genome-wide association study (GWAS) on COVID-19 severity and infection susceptibility to SARS-CoV-2 from the COVID-19 Host Genetic Initiative (data release 7). We performed a meta-analysis of up to 219,692 cases and over 3 million controls, identifying 51 distinct genome-wide significant loci—adding 28 loci from the previous data release2. The increased number of candidate genes at the identified loci helped to map three major biological pathways involved in susceptibility and severity: viral entry, airway defense in mucus, and type I interferon.

By considering the recently introduced SIRU model, in this paper we study the dynamic of COVID-19 pandemic under the temporally varying public intervention in the Chilean context. More precisely, we propose a method to forecast cumulative daily reported cases $CR(t)$, and a systematic way to identify the unreported daily cases given $CR(t)$ data. We firstly base on the recently introduced epidemic model SIRU (Susceptible, asymptomatic Infected, Reported infected, Unreported infected), and focus on the transmission rate parameter $\tau$. To understand the dynamic of the data, we extend the scalar $\tau$ to an unknown function $\tau(t)$ in the SIRU system, which is then inferred directly from the historical $CR(t)$ data, based on nonparametric estimation. The estimation of $\tau(t)$ leads to the estimation of other unobserved functions in the system, including the daily unreported cases. Furthermore, the estimation of $\tau(t)$ allows us to build links between the pandemic evolution and the public intervention, which is modeled by logistic regression. We then employ polynomial approximation to construct a predicted curve which evolves with the latest trend of $CR(t)$. In addition, we regularize the evolution of the forecast in such a way that it corresponds to the future intervention plan based on the previously obtained link knowledge. We test the proposed predictor on different time windows. The promising results show the effectiveness of the proposed methods.

ABSTRACTIn response to the COVID-19 epidemic, Egypt established a unique care model based on quarantine hospitals where only externally-referred confirmed COVID-19 patients were admitted, and healthcare workers resided continuously over 1-to 2-week working shifts. While the COVID-19 risk for HCWs has been widely reported in standard healthcare settings, it has not been evaluated yet in quarantine hospitals.Here, we relied on longitudinal data, including results of routine RT-PCR tests, collected within three quarantine hospitals located in Cairo and Fayoum, Egypt. Using a model-based approach that accounts for the time-since-exposure variation in false-negative rates of RT-PCR tests, we computed the incidence of SARS-CoV-2 infection among HCWs. Over a total follow-up of 6,064 person-days (PD), we estimated an incidence rate (per 100 PD) of 1.05 (95% CrI: 0.58–1.65) at Hospital 1, 1.92 (95% CrI: 0.93–3.28) at Hospital 2 and 7.62 (95% CrI: 3.47–13.70) at Hospital 3. The probability for an HCW to be infected at the end of a shift was 13.7% (95% CrI: 7.8%–20.8%) and 23.8% (95% CrI: 12.2%–37.3%) for a 2-week shift at Hospital 1 and Hospital 2, respectively, which lies within the range of risk levels previously documented in standard healthcare settings, whereas it was >3-fold higher for a 7-day shift at Hospital 2 (42.6%, 95%CrI: 21.9%–64.4%). Our model-based estimates unveil a proportion of undiagnosed infections among HCWs of 46.4% (95% CrI: 18.8%–66.7%), 45.0% (95% CrI: 5.6%–70.8%) and 59.2% (95% CrI: 34.8%–78.8%), for Hospitals 1 to 3, respectively.The large variation in SARS-CoV-2 incidence we document here suggests that HCWs from quarantine hospitals may face a high occupational risk of infection, but that, with sufficient anticipation and infection control measures, this risk can be brought down to levels similar to those observed in standard healthcare settings.WHAT THIS PAPER ADDSWhat is already known on this topicPrevious studies conducted in standard care settings have documented that frontline healthcare workers (HCWs) face high risk of COVID-19. Whether risk levels differ in alternative care models, such as COVID-19 quarantine hospitals in Egypt where HCWs resided in the hospital days and nights for various durations, is unknown.What this study addsCOVID-19 risk for HCWs in quarantine hospitals varies substantially between facilities, from risk levels that are in the range of those documented in standard healthcare settings to levels that were approximatively 3 times higher.How this study might affect research, practice or policyWith sufficient anticipation and infection control measures, occupational COVID-19 risk for HCWs working in quarantine hospitals can be brought down to levels similar to those observed in standard healthcare settings.

Abstract Background SARS-CoV-2 is a rapidly spreading disease affecting human life and the economy on a global scale. The disease has caused so far more then 5.5 million deaths. The omicron outbreak that emerged in Botswana in the south of Africa spread around the globe at further increased rates, and caused unprecedented SARS-CoV-2 infection incidences in several countries. At the start of December 2021 the first omicron cases were reported in France. Methods In this paper we investigate the spreading potential of this novel variant relatively to the delta variant that was also in circulation in France at that time. Using a dynamic multi-variant model accounting for cross-immunity through a status-based approach, we analyze screening data reported by Santé Publique France over 13 metropolitan French regions between 1st of December 2021 and the 30th of January 2022. During the investigated period, the delta variant was replaced by omicron in all metropolitan regions in approximately three weeks. The analysis conducted retrospectively allows us to consider the whole replacement time window and compare regions with different times of omicron introduction and baseline levels of variants’ transmission potential. As large uncertainties regarding cross-immunity among variants persist, uncertainty analyses were carried out to assess its impact on our estimations. Results Assuming that 80% of the population was immunized against delta, a cross delta/omicron cross-immunity of 25% and an omicron generation time of 3.5 days, the relative strength of omicron to delta, expressed as the ratio of their respective reproduction rates, $$\frac{\hat{R}_{\textrm{omicron}}}{\hat{R}_{\textrm{delta}}}$$ R ^ omicron R ^ delta , was found to range between 1.51 and 1.86 across regions. Uncertainty analysis on epidemiological parameters led to $$\frac{\hat{R}_{\textrm{omicron}}}{\hat{R}_{\textrm{delta}}}$$ R ^ omicron R ^ delta ranging from 1.57 to 2.34 on average over the metropolitan French regions, weighted by population size. Conclusions Upon introduction, omicron spread rapidly through the French territory and showed a high fitness relative to delta. We documented considerable geographical heterogeneities on the spreading dynamics. The historical reconstruction of variant emergence dynamics provide valuable ground knowledge to face future variant emergence events.

AbstractThe binding of the SARS-CoV-2 spike to angiotensin-converting enzyme 2 (ACE2) promotes virus entry into the cell. Targeting this interaction represents a promising strategy to generate antivirals. By screening a phage-display library of biosynthetic protein sequences build on a rigid alpha-helicoidal HEAT-like scaffold (named αReps), we selected candidates recognizing the spike receptor binding domain (RBD). Two of them (F9 and C2) bind the RBD with affinities in the nM range, displaying neutralisation activity in vitro and recognizing distinct sites, F9 overlapping the ACE2 binding motif. The F9-C2 fusion protein and a trivalent αRep form (C2-foldon) display 0.1 nM affinities and EC50 of 8-18 nM for neutralization of SARS-CoV-2. In hamsters, F9-C2 instillation in the nasal cavity before or during infections effectively reduced the replication of a SARS-CoV-2 strain harbouring the D614G mutation in the nasal epithelium. Furthermore, F9-C2 and/or C2-foldon effectively neutralized SARS-CoV-2 variants (including delta and omicron variants) with EC50 values ranging from 13 to 32 nM. With their high stability and their high potency against SARS-CoV-2 variants, αReps provide a promising tool for SARS-CoV-2 therapeutics to target the nasal cavity and mitigate virus dissemination in the proximal environment.Author SummaryThe entry of SARS-CoV-2 in permissive cells is mediated by the binding of its spike to angiotensin-converting enzyme 2 (ACE2) on the cell surface. To select ligands able to block this interaction, we screened a library of phages encoding artificial proteins (named αReps) for binding to its receptor binding domain (RBD). Two of them were able to bind the RBD with high affinity and block efficiently the virus entry in cultured cells. Assembled αReps through covalent or non-covalent linkages blocked virus entry at lower concentration than their precursors (with around 20-fold activity increase for a trimeric αRep). These αReps derivates neutralize efficiently SARS-CoV-2 β, γ, δ and Omicron virus variants. Instillation of an αRep dimer in the nasal cavity effectively reduced virus replication in the hamster model of SARS-CoV-2 and pathogenicity.

SummaryDuring the current COVID-19 pandemic, governments must make decisions based on a variety of information including estimations of infection spread, health care capacity, economic and psychosocial considerations. The disparate validity of current short-term forecasts of these factors is a major challenge to governments. By causally linking an established epidemiological spread model with dynamically evolving psychosocial variables, using Bayesian inference we estimate the strength and direction of these interactions for German and Danish data of disease spread, human mobility, and psychosocial factors based on the serial cross-sectional COVID-19 Snapshot Monitoring (COSMO;N= 16,981). We demonstrate that the strength of cumulative influence of psychosocial variables on infection rates is of a similar magnitude as the influence of physical distancing. We further show that the efficacy of political interventions to contain the disease strongly depends on societal diversity, in particular group-specific sensitivity to affective risk perception. As a consequence, the model may assist in quantifying the effect and timing of interventions, forecasting future scenarios, and differentiating the impact on diverse groups as a function of their societal organization. Importantly, the careful handling of societal factors, including support to the more vulnerable groups, adds another direct instrument to the battery of political interventions fighting epidemic spread.

The year 2020 will be remembered as the year of COVID-19 and its subsequent lockdowns. This pandemic has profoundly changed the way we teach by forcing many institutions to offer their courses online. The time to come back to face-to-face teaching has arrived, but the shadow of the disease still hangs over teachers, students and society more generally. Disruption in teaching can still occur for students, or even teachers, if they are either diagnosed COVID-19 positive or contact case and forced to self-isolate. In order to limit the impact of self-isolation on learning, hybrid teaching (i.e. teaching face-to-face to students in a classroom and to online students at the same time) was successfully implemented owing to the combination of a videoconference software and a large interactive touchscreen. The set-up presented in this paper allows to broadcast courses to at-home students (i.e. voice, visual pedagogic support and, more interestingly, indications handwritten by the teacher) while simultaneously teaching face-to-face to students in the classroom. It also allows to self-isolated teacher to teach tutorial from home to students in the classroom. This paper focuses on the use of large interactive touchscreens for hybrid teaching. In order to evaluate this pedagogical approach, a questionnaire was completed by students and results discussed.

When the threat of COVID-19 became widely acknowledged, many hoped that this epidemic would squash "the anti-vaccine movement". However, when vaccines started arriving in rich countries at the end of 2020, it appeared that vaccine hesitancy might be an issue even in the context of this major epidemic. Does it mean that the mobilization of vaccine-critical activists on social media is one of the main causes of this reticence to vaccinate against COVID-19? In this paper, we wish to contribute to current work on vaccine hesitancy during the COVID-19 epidemic by looking at one of the many mechanisms which can cause reticence towards vaccines: the capacity of vaccine-critical activists to influence a wider public on social media. We analyze the evolution of debates over the COVID-19 vaccine on the French Twittosphere, during two first years of the pandemic, with a particular attention to the spreading capacity of vaccine-critical websites. We address two main questions: 1) Did vaccine-critical contents gain ground during this period? 2) Who were the central actors in the diffusion of these contents? While debates over vaccines experienced a tremendous surge during this period, the share of vaccine-critical contents in these debates remains stable except for a limited number of short periods associated with specific events. Secondly, analyzing the community structure of the re-tweets hyper-graph, we reconstruct the mesoscale structure of the information flows, identifying and characterizing the major communities of users. We analyze their role in the information ecosystem: the largest right-wing community has a typical echo-chamber behavior collecting all the vaccine-critical tweets from outside and recirculating it inside the community. The smaller left-wing community is less permeable to vaccine-critical contents but, has a large capacity to spread it once adopted. 18 pages, 7 figures and 2 tables

AbstractWe report serological surveillance for exposure to SARS-CoV-2 in 1,237 wild rodents and other small mammals across Europe. All samples were negative with the possible exception of one. Given the ongoing circulation of this virus in humans and potential host jumps, we suggest such surveillance be continued.