Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe.

Funder: European and Developing Countries Clinical Trials Partnership (EDCTP); doi: https://doi.org/10.13039/501100001713Funder: MRC Centre for Global Infectious Disease Analysis (MR/R015600/1), jointly funded by the U.K. Medical Research Council (MRC) and the U.K. Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO Concordat agreement. Community Jameel. The UK Research and Innovation (MR/V038109/1), the Academy of Medical Sciences Springboard Award (SBF004/1080), The MRC (MR/R015600/1), The BMGF (OPP1197730), Imperial College Healthcare NHS Trust- BRC Funding (RDA02), The Novo Nordisk Young Investigator Award (NNF20OC0059309) and The NIHR Health Protection Research Unit in Modelling Methodology. S. Bhatt thanks Microsoft AI for Health and Amazon AWS for computational credits.Funder: EA FundsFunder: University of Oxford (Oxford University); doi: https://doi.org/10.13039/501100000769Funder: DeepMindFunder: OpenPhilanthropyFunder: UKRI Centre for Doctoral Training in Interactive Artificial Intelligence (EP/S022937/1)Funder: Augustinus Fonden (Augustinus Foundation); doi: https://doi.org/10.13039/501100004954Funder: Knud Højgaards Fond (Knud Højgaard Fund); doi: https://doi.org/10.13039/501100009938Funder: Kai Lange og Gunhild Kai Langes Fond (Kai Lange and Gunhild Kai Lange Foundation); doi: https://doi.org/10.13039/501100008206Funder: Aage og Johanne Louis-Hansens Fond (Aage and Johanne Louis-Hansen Foundation); doi: https://doi.org/10.13039/501100010344Funder: William Demant FoundationFunder: Boehringer Ingelheim Fonds (Stiftung für medizinische Grundlagenforschung); doi: https://doi.org/10.13039/501100001645Funder: Imperial College COVID-19 Research FundFunder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. Business closures, educational institution closures, and gathering bans reduced transmission, but reduced it less than they did in the first wave. This difference is likely due to organisational safety measures and individual protective behaviours-such as distancing-which made various areas of public life safer and thereby reduced the effect of closing them. Specifically, we find smaller effects for closing educational institutions, suggesting that stringent safety measures made schools safer compared to the first wave. Second-wave estimates outperform previous estimates at predicting transmission in Europe's third wave

New Insight into Neutrophil Extracellular Traps: Mechanisms of Formation and Role in Inflammation

Recent data suggest that NETosis plays a crucial role in the innate immune response and disturbs the homeostasis of the immune system. NETosis is a form of neutrophil-specific cell death characterized by the release of large web-like structures referred to as neutrophil extracellular traps (NETs). NETs are composed of DNA strands associated with histones and decorated with about 20 different proteins including neutrophil elastase (NE), myeloperoxidase (MPO), cathepsin G, proteinase 3 (PR3), high mobility group protein B1 (HMGB1), and LL37. Reportedly, NETosis can be induced by several microbes, and particulate matter including sterile stimuli, via distinct cellular mechanisms. Meanwhile, suicidal NETosis and vital NETosis are controversial. As we enter the second decade of research on NETosis, we have partly understood NETs as double-edged swords of innate immunity. In this review we will discuss the mechanisms of NETosis, its antimicrobial action and role in autoimmune diseases, as well as the relatively new field of NET-associated mitochondrial DNA

Seasonal variation in SARS-CoV-2 transmission in temperate climates

# Data for Gavenciak et al.: Seasonal variation in SARS-CoV-2 transmission in temperate climates This is a snapshot of data from the https://github.com/gavento/covid_seasonal_Brauner and https://github.com/gavento/covid_seasonal_Sharma data&code repositories. ## Brauner/ folder Contains a snapshot of the data published in Brauner et al.: Inferring the effectiveness of government interventions against COVID-19 in the https://github.com/epidemics/COVIDNPIs repository under MIT licence. The data narrowed to temperate Europe was published in the https://github.com/gavento/covid_seasonal_Brauner repository inder MIT licence. ## Sharma/ folder Contains a snapshot of the data published in Sharma et al.: Understanding the effectiveness of government interventions in Europe’s second wave of COVID-19 in the https://github.com/MrinankSharma/COVID19NPISecondWave repository under MIT licence

A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe.

During the second half of 2020, many European governments responded to the resurging transmission of SARS-CoV-2 with wide-ranging non-pharmaceutical interventions (NPIs). These efforts were often highly targeted at the regional level and included fine-grained NPIs. This paper describes a new dataset designed for the accurate recording of NPIs in Europe's second wave to allow precise modelling of NPI effectiveness. The dataset includes interventions from 114 regions in 7 European countries during the period from the 1st August 2020 to the 9th January 2021. The paper includes NPI definitions tailored to the second wave following an exploratory data collection. Each entry has been extensively validated by semi-independent double entry, comparison with existing datasets, and, when necessary, discussion with local epidemiologists. The dataset has considerable potential for use in disentangling the effectiveness of NPIs and comparing the impact of interventions across different phases of the pandemic

The coming decade of digital brain research - A vision for neuroscience at the intersection of technology and computing

<p>Brain research has in recent years indisputably entered a new epoch, driven by substantial methodological advances and digitally enabled data integration and modeling at multiple scales – from molecules to the whole system. Major advances are emerging at the intersection of neuroscience with technology and computing. This new science of the brain integrates high-quality basic research, systematic data integration across multiple scales, a new culture of large-scale collaboration and translation into applications. A systematic approach, as pioneered in Europe's Human Brain Project (HBP), will be essential in meeting the pressing medical and technological challenges of the coming decade. The aims of this paper are</p><ul><li>To develop a concept for the coming decade of digital brain research</li><li>To discuss it with the research community at large, with the aim of identifying points of convergence and common goals</li><li>To provide a scientific framework for current and future development of EBRAINS</li><li>To inform and engage stakeholders, funding organizations and research institutions regarding future digital brain research</li><li>To identify and address key ethical and societal issues</li></ul><p>While we do not claim that there is a 'one size fits all' approach to addressing these aspects, we are convinced that discussions around the theme of digital brain research will help drive progress in the broader field of neuroscience.</p><p><strong>As the final version 5 has now been published, comments on this manuscript are now closed. We thank everyone who made a valuable contribution to this paper.</strong></p><p>This manuscript has been developed in a participatory process. The work has been initiated by the Science and Infrastructure Board of the Human Brain Project (HBP), and the entire research community was invited to contribute to shaping the vision by submitting comments. </p><p>All submitted comments were considered and discussed. The final decision on whether edits or additions was made to each version of the manuscript based on an individual comment was made by the Science and Infrastructure Board (SIB) of the Human Brain Project (HBP).</p><p><strong>Supporters of the paper</strong>: Pietro Avanzini, Marc Beyer, Maria Del Vecchio, Jitka Annen, Maurizio Mattia, Steven Laureys, Rosanne Edelenbosch, Rafael Yuste, Jean-Pierre Changeux, Linda Richards, Hye Weon Jessica Kim, Chrysoula Samara, Luis Miguel González de la Garza, Nikoleta Petalidou, Vasudha Kulkarni, Cesar David Rincon, Isabella O'Shea, Munira Tamim Electricwala, Bernd Carsten Stahl, Bahar Hazal Yalcinkaya, Meysam Hashemi, Carola Sales Carbonell, Marcel Carrère, Anthony Randal McIntosh, Hiba Sheheitli, Abolfazl Ziaeemehr, Martin Breyton, Giovanna Ramos Queda, Anirudh NIhalani Vattikonda, Gyorgy Buzsaki, George Ogoh, William Knight, Torbjørn V Ness, Michiel van der Vlag, Marcello Massimini, Thomas Nowontny, Alex Upton, Yaseen Jakhura, Ahmet Nihat Simsek, Michael Hopkins, Addolorata Marasco, Shamim Patel, Jakub Fil, Diego Molinari, Susana Bueno, Lia Domide, Cosimo Lupo, Mu-ming Poo, George Paxinos, Huifang Wang.</p&gt