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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
407 Research products, page 1 of 41

  • COVID-19
  • 2017-2021
  • GB
  • Hyper Article en Ligne
  • Hal-Diderot
  • Hyper Article en Ligne - Sciences de l'Homme et de la Société
  • COVID-19

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  • Publication . Article . Preprint . Other literature type . 2021
    Open Access English
    Authors: 
    Gemma C Sharp; Abigail Fraser; Gemma Sawyer; Gabriella Kountourides; Kayleigh E Easey; Gemma Ford; Zuzanna Olszewska; Laura D Howe; Deborah A Lawlor; Alexandra Alvergne; +1 more
    Publisher: HAL CCSD
    Countries: United Kingdom, France, United Kingdom, United Kingdom, United Kingdom, United Kingdom, United Kingdom

    International audience; Since the beginning of the COVID-19 pandemic, discussions on social media and blogs have indicated that women have experienced menstrual changes, including altered menstrual duration, frequency, regularity, and volume (heavier bleeding and clotting), increased dysmenorrhea, and worsened premenstrual syndrome. There have been a small number of scientific studies of variable quality reporting on menstrual cycle features during the pandemic, but it is still unclear whether apparent changes are due to COVID-19 infection/illness itself, or other pandemic-related factors like increased psychological stress and changes in health behaviours. It is also unclear to what degree current findings are explained by reporting bias, recall bias, selection bias and confounding factors. Further research is urgently needed. We provide a list of outstanding research questions and potential approaches to address them. Findings can inform policies to mitigate against gender inequalities in health and society, allowing us to build back better post-COVID.

  • Open Access English
    Authors: 
    Paolo Bosetti; Bich-Tram Huynh; Armiya Youssouf Abdou; Marie Sanchez; Catherine Eisenhauer; Noémie Courtejoie; Jérôme Accardo; Henrik Salje; Didier Guillemot; Mathieu Moslonka-Lefebvre; +4 more
    Publisher: European Centre for Disease Prevention and Control (ECDC)
    Country: France

    Background Many countries implemented national lockdowns to contain the rapid spread of SARS-CoV-2 and avoid overburdening healthcare capacity. Aim We aimed to quantify how the French lockdown impacted population mixing, contact patterns and behaviours. Methods We conducted an online survey using convenience sampling and collected information from participants aged 18 years and older between 10 April and 28 April 2020. Result Among the 42,036 survey participants, 72% normally worked outside their home, and of these, 68% changed to telework during lockdown and 17% reported being unemployed during lockdown. A decrease in public transport use was reported from 37% to 2%. Participants reported increased frequency of hand washing and changes in greeting behaviour. Wearing masks in public was generally limited. A total of 138,934 contacts were reported, with an average of 3.3 contacts per individual per day; 1.7 in the participants aged 65 years and older compared with 3.6 for younger age groups. This represented a 70% reduction compared with previous surveys, consistent with SARS-CoV2 transmission reduction measured during the lockdown. For those who maintained a professional activity outside home, the frequency of contacts at work dropped by 79%. Conclusion The lockdown affected the population's behaviour, work, risk perception and contact patterns. The frequency and heterogeneity of contacts, both of which are critical factors in determining how viruses spread, were affected. Such surveys are essential to evaluate the impact of lockdowns more accurately and anticipate epidemic dynamics in these conditions.

  • Open Access English
    Authors: 
    Laura Di Domenico; Giulia Pullano; Chiara E. Sabbatini; Pierre-Yves Boëlle; Vittoria Colizza;
    Publisher: HAL CCSD
    Country: France
    Project: EC | MOOD (874850), ANR | DataRedux (ANR-19-CE46-0008), ANR | SPHINx (ANR-17-CE36-0008)

    As countries in Europe implement strategies to control the COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Île-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on children’s role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist to keep the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead to up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace is required to keep the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown. The role of children in the spread of COVID-19 is not fully understood, and the circumstances under which schools should be opened are therefore debated. Here, the authors demonstrate protocols by which schools in France can be safely opened without overwhelming the healthcare system.

  • Open Access English
    Authors: 
    Hannah E.J. Yong; Shiao-Yng Chan; Amlan Chakraborty; Gayathri Rajaraman; Sharon D. Ricardo; Mohamed Benharouga; Nadia Alfaidy; Frantisek Staud; Padma Murthi;
    Publisher: HAL CCSD
    Countries: France, France, France, France, United Kingdom

    The placenta provides a significant physical and physiological barrier to prevent fetal infection during pregnancy. Nevertheless, it is at times breached by pathogens and leads to vertical transmission of infection from mother to fetus. This review will focus specifically on the Zika flavivirus, the HIV retrovirus and the emerging SARS-CoV2 coronavirus, which have affected pregnant women and their offspring in recent epidemics. In particular, we will address how viral infections affect the immune response at the maternal-fetal interface and how the placental barrier is physically breached and discuss the consequences of infection on various aspects of placental function to support fetal growth and development. Improved understanding of how the placenta responds to viral infections will lay the foundation for developing therapeutics to these and emergent viruses, to minimise the harms of infection to the offspring.

  • Open Access English
    Authors: 
    Mariana Galvão Ferrarini; Avantika Lal; Rita Rebollo; Andreas J. Gruber; Andrea Guarracino; Itziar Martinez Gonzalez; Taylor Floyd; Daniel Siqueira de Oliveira; Justin Shanklin; Ethan Beausoleil; +3 more
    Countries: France, Germany, Germany

    The novel betacoronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a worldwide pandemic (COVID-19) after emerging in Wuhan, China. Here we analyzed public host and viral RNA sequencing data to better understand how SARS-CoV-2 interacts with human respiratory cells. We identified genes, isoforms and transposable element families that are specifically altered in SARS-CoV-2-infected respiratory cells. Well-known immunoregulatory genes including CSF2, IL32, IL-6 and SERPINA3 were differentially expressed, while immunoregulatory transposable element families were upregulated. We predicted conserved interactions between the SARS-CoV-2 genome and human RNA-binding proteins such as the heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1) and eukaryotic initiation factor 4 (eIF4b). We also identified a viral sequence variant with a statistically significant skew associated with age of infection, that may contribute to intracellular host–pathogen interactions. These findings can help identify host mechanisms that can be targeted by prophylactics and/or therapeutics to reduce the severity of COVID-19. Ferrarini & Lal et al. developed a novel bioinformatic pipeline to explore how SARS-CoV-2 interacts with human respiratory cells using public available host gene expression and viral genome sequence data. Several human genes and proteins were predicted to play a role in the viral life cycle and the host response to SARS-CoV-2 infection.

  • Open Access English
    Authors: 
    Costas I. Karageorghis; Jonathan M. Bird; Jasmin C. Hutchinson; Mark Hamer; Yvonne Delevoye-Turrell; Ségolène M. R. Guérin; Elizabeth M. Mullin; Kathleen T. Mellano; Renée L. Parsons-Smith; Victoria R. Terry; +1 more
    Publisher: BMC
    Countries: France, France, France, United Kingdom, France, France, France

    Abstract Background COVID-19 lockdowns have reduced opportunities for physical activity (PA) and encouraged more sedentary lifestyles. A concomitant of sedentariness is compromised mental health. We investigated the effects of COVID-19 lockdown on PA, sedentary behavior, and mental health across four Western nations (USA, UK, France, and Australia). Methods An online survey was administered in the second quarter of 2020 (N = 2541). We measured planned and unplanned dimensions of PA using the Brunel Lifestyle Physical Activity Questionnaire and mental health using the 12-item General Health Questionnaire. Steps per day were recorded only from participants who used an electronic device for this purpose, and sedentary behavior was reported in hours per day (sitting and screen time). Results In the USA and Australia samples, there was a significant decline in planned PA from pre- to during lockdown. Among young adults, Australians exhibited the lowest planned PA scores, while in middle-aged groups, the UK recorded the highest. Young adults exhibited the largest reduction in unplanned PA. Across nations, there was a reduction of ~ 2000 steps per day. Large increases in sedentary behavior emerged during lockdown, which were most acute in young adults. Lockdown was associated with a decline in mental health that was more pronounced in women. Conclusions The findings illustrate the deleterious effects of lockdown on PA, sedentary behavior, and mental health across four Western nations. Australian young and lower middle-aged adults appeared to fare particularly badly in terms of planned PA. The reduction in steps per day is equivalent to the non-expenditure of ~ 100 kcal. Declines in mental health show how harmful lockdowns can be for women in particular.

  • Open Access English
    Authors: 
    Andronico, Alessio; Tran Kiem, Cécile; Paireau, Juliette; Succo, Tiphanie; Bosetti, Paolo; Lefrancq, Noémie; Nacher, Mathieu; Djossou, Félix; Sanna, Alice; Flamand, Claude; +3 more
    Countries: France, United Kingdom
    Project: ANR | INCEPTION (ANR-16-CONV-0005), EC | RECoVER (101003589)

    Abstract: While general lockdowns have proven effective to control SARS-CoV-2 epidemics, they come with enormous costs for society. It is therefore essential to identify control strategies with lower social and economic impact. Here, we report and evaluate the control strategy implemented during a large SARS-CoV-2 epidemic in June–July 2020 in French Guiana that relied on curfews, targeted lockdowns, and other measures. We find that the combination of these interventions coincided with a reduction in the basic reproduction number of SARS-CoV-2 from 1.7 to 1.1, which was sufficient to avoid hospital saturation. We estimate that thanks to the young demographics, the risk of hospitalisation following infection was 0.3 times that of metropolitan France and that about 20% of the population was infected by July. Our model projections are consistent with a recent seroprevalence study. The study showcases how mathematical modelling can be used to support healthcare planning in a context of high uncertainty. Funder: We acknowledge financial support from the Investissement d'Avenir program, the Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases program (Grant ANR-10-LABX-62-IBEID), Sante Publique France, the INCEPTION project (PIA/ANR-16-CONV-0005) and European Union V.E.O and RECOVER projects.

  • Open Access English
    Authors: 
    W. Waites; M. Cavaliere; V. Danos; R. Datta; R. M. Eggo; T. B. Hallett; D. Manheim; J. Panovska-Griffiths; T. W. Russell; V. I. Zarnitsyna;
    Publisher: HAL CCSD
    Countries: France, United Kingdom, France

    Transmission models for infectious diseases are typically formulated in terms of dynamics between individuals or groups with processes such as disease progression or recovery for each individual captured phenomenologically, without reference to underlying biological processes. Furthermore, the construction of these models is often monolithic: they do not allow one to readily modify the processes involved or include the new ones, or to combine models at different scales. We show how to construct a simple model of immune response to a respiratory virus and a model of transmission using an easily modifiable set of rules allowing further refining and merging the two models together. The immune response model reproduces the expected response curve of PCR testing for COVID-19 and implies a long-tailed distribution of infectiousness reflective of individual heterogeneity. This immune response model, when combined with a transmission model, reproduces the previously reported shift in the population distribution of viral loads along an epidemic trajectory. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.

  • Open Access English
    Authors: 
    Boris Bonaventure; Antoine Rebendenne; Francisco Garcia de Gracia; Joe McKellar; Ségolène Gracias; Emmanuel Labaronne; Marine Tauziet; Ana Luiza Chaves Valadão; Eric Bernard; Laurence Briant; +11 more
    Publisher: HAL CCSD
    Country: France

    AbstractGenome-wide screens are powerful approaches to unravel new regulators of viral infections. Here, we used a CRISPR/Cas9 screen to reveal new HIV-1 inhibitors. This approach led us to identify the RNA helicase DDX42 as an intrinsic antiviral inhibitor. DDX42 was previously described as a non-processive helicase, able to bind RNA secondary structures such as G-quadruplexes, with no clearly defined function ascribed. Our data show that depletion of endogenous DDX42 significantly increased HIV-1 DNA accumulation and infection in cell lines and primary cells. DDX42 overexpression inhibited HIV-1, whereas a dominant-negative mutant increased infection. Importantly, DDX42 also restricted retrotransposition of LINE-1, infection with other retroviruses and positive-strand RNA viruses, including CHIKV and SARS-CoV-2. However, DDX42 did not inhibit infection with three negative-strand RNA viruses, arguing against a general, unspecific effect on target cells, which was confirmed by RNA-seq analysis. DDX42 was found in the vicinity of viral elements by proximity ligation assays, and cross-linking RNA immunoprecipitation confirmed a specific interaction of DDX42 with RNAs from sensitive viruses. This strongly suggested a direct mode of action of DDX42 on viral ribonucleoprotein complexes. Taken together, our results show for the first time a new and important role of DDX42 in intrinsic antiviral immunity.

  • Open Access English
    Authors: 
    Nicolas Shiaelis; Alexander Tometzki; Leon Peto; Andrew P. McMahon; Christof Hepp; Erica Bickerton; Cyril Favard; Delphine Muriaux; Monique Andersson; Sarah Oakley; +6 more
    Publisher: HAL CCSD
    Country: France

    ABSTRACTThe increasing frequency and magnitude of viral outbreaks in recent decades, epitomized by the current COVID-19 pandemic, has resulted in an urgent need for rapid and sensitive diagnostic methods. Here, we present a methodology for virus detection and identification that uses a convolutional neural network to distinguish between microscopy images of single intact particles of different viruses. Our assay achieves labeling, imaging and virus identification in less than five minutes and does not require any lysis, purification or amplification steps. The trained neural network was able to differentiate SARS-CoV-2 from negative clinical samples, as well as from other common respiratory pathogens such as influenza and seasonal human coronaviruses. Additionally, we were able to differentiate closely related strains of influenza, as well as SARS-CoV-2 variants. Single-particle imaging combined with deep learning therefore offers a promising alternative to traditional viral diagnostic and genomic sequencing methods, and has the potential for significant impact.