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The CALorimetric Electron Telescope (CALET) on the International Space Station: Results from the First Two Years On Orbit

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Journal of Physics: Conference Series 2019年第1期1181卷

作者： Y Asaoka O Adriani Y Akaike K Asano M G Bagliesi E Berti G Bigongiari W R Binns S Bonechi M Bongi A Bruno P Brogi J H Buckley N Cannady G Castellini C Checchia M L Cherry G Collazuol V Di Felice K Ebisawa H Fuke T G Guzik T Hams N Hasebe K Hibino M Ichimura K Ioka W Ishizaki M H Israel K Kasahara J Kataoka R Kataoka Y Katayose C Kato N Kawanaka Y Kawakubo K Kohri H S Krawczynski J F Krizmanic T Lomtadze P Maestro P S Marrocchesi A M Messineo J W Mitchell S Miyake A A Moiseev K Mori M Mori N Mori H M Motz K Munakata H Murakami S Nakahira J Nishimura G A De Nolfo S Okuno J F Ormes S Ozawa L Pacini F Palma V Pal'shin P Papini A V Penacchioni B F Rauch S B Ricciarini K Sakai T Sakamoto M Sasaki Y Shimizu A Shiomi R Sparvoli P Spillantini F Stolzi S Sugita J E Suh A Sulaj I Takahashi M Takayanagi M Takita T Tamura N Tateyama T Terasawa H Tomida S Torii Y Tsunesada Y Uchihori S Ueno E Vannuccini J P Wefel K Yamaoka S Yanagita A Yoshida K Yoshida Waseda Research Institute for Science and Engineering Waseda University Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency Japan Department of Physics University of Florence Italy INFN Sezione di Florence Italy Department of Physics University of Maryland USA Astroparticle Physics Laboratory NASA/GSFC USA Institute for Cosmic Ray Research The University of Tokyo Japan Department of Physical Sciences Earth and Environment University of Siena Italy INFN Sezione di Pisa Italy Department of Physics Washington University USA Heliospheric Physics Laboratory NASA/GSFC USA Department of Physics and Astronomy Louisiana State University USA Institute of Applied Physics (IFAC) National Research Council (CNR) Italy Department of Physics and Astronomy University of Padova Italy INFN Sezione di Padova Italy University of Rome 'Tor Vergata' Italy INFN Sezione di Rome 'Tor Vergata' Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Japan CRESST and Astroparticle Physics Laboratory NASA/GSFC USA Kanagawa University Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University Japan Yukawa Institute for Theoretical Physics Kyoto University Japan National Institute of Polar Research Japan Faculty of Engineering Division of Intelligent Systems Engineering Yokohama National University Japan Faculty of Science Shinshu University Japan Hakubi Center Kyoto University Japan Department of Astronomy Graduate School of Science Kyoto University Japan College of Science and Engineering Department of Physics and Mathematics Aoyama Gakuin University Japan High Energy Accelerator Research Organization Japan University of Pisa Italy Department of Electrical and Electronic Systems Engineering National Institute of Technology Ibaraki College Japan Department of Astronomy University of Maryland College Park Maryland 20742 USA Department of Physical Sciences Co

The CALorimetric Electron Telescope (CALET) is a high-energy astroparticle physics space experiment installed on the International Space Station (ISS), developed and operated by Japan in collaboration with Italy and the United States. The CALET mission goals include the investigation of possible nearby sources of high-energy electrons, of the details of galactic particle acceleration and propagation, and of potential signatures of dark matter. CALET measures the cosmic-ray electron+positron flux up to 20 TeV, gamma-rays up to 10 TeV, and nuclei with Z=1 to 40 up to 1, 000 TeV for the more abundant elements during a long-term observation aboard the ISS. Starting science operation in mid-October 2015, CALET performed continuous observation without major interruption with close to 20 million triggered events over 10 GeV per month. Based on the data taken during the first two-years, we present an overview of CALET observations: 1) Electron+positron energy spectrum, 2) Nuclei analysis, 3) Gamma-ray observation including a characterization of on-orbit performance. Results of the electromagnetic counterpart search for LIGO/Virgo gravitational wave events are discussed as well.

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Advances in understanding high-mass X-ray binaries with INTEGRAL and Future Directions

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arXiv 2020年

作者： Kretschmar, Peter Fürst, Felix Sidoli, Lara Bozzo, Enrico Alfonso-Garzón, Julia Bodaghee, Arash Chaty, Sylvain Chernyakova, Masha Ferrigno, Carlo Manousakis, Antonios Negueruela, Ignacio Postnov, Konstantin Paizis, Adamantia Reig, Pablo Rodes-Roca, José Joaquín Tsygankov, Sergey Bird, Antony J. né Kühnel, Matthias Bissinger Blay, Pere Caballero, Isabel Coe, Malcolm J. Domingo, Albert Doroshenko, Victor Ducci, Lorenzo Falanga, Maurizio Grebenev, Sergei A. Grinberg, Victoria Hemphill, Paul Kreykenbohm, Ingo née Fritz, Sonja Kreykenbohm Li, Jian Lutovinov, Alexander A. Martínez-Núñez, Silvia Mas-Hesse, J. Miguel Masetti, Nicola McBride, Vanessa A. Neronov, Andrii Pottschmidt, Katja Rodriguez, Jérôme Romano, Patrizia Rothschild, Richard E. Santangelo, Andrea Sguera, Vito Staubert, Rüdiger Tomsick, John A. Torrejón, José Miguel Torres, Diego F. Walter, Roland Wilms, Jörn Wilson-Hodge, Colleen A. Zhang, Shu E-28692 Spain E-28692 Spain INAF - IASF Istituto di Astrofisica Spaziale e Fisica Cosmica Via A. Corti 12 MilanoI-20133 Italy Department of Astronomy ISDC University of Geneva Chemin d'Ecogia 16 VersoixCH-1290 Switzerland E-28692 Spain Department of Chemistry Physics and Astronomy Georgia College and State University MilledgevilleGA31061 United States AIM CEA CNRS Université Paris-Saclay Université de Paris Gif-sur-YvetteF-91191 France Université de Paris CNRS Astroparticule et Cosmologie ParisF-75006 France School of Physical Sciences and CfAR Dublin City University Dublin 9 Ireland Dublin Institute for Advanced Studies 31 Fitzwilliam Place Dublin 2 Ireland Department of Applied Physics & Astronomy University of Sharjah Sharjah United Arab Emirates Sharjah United Arab Emirates Department of Applied Physics University of Alicante AlicanteE-03080 Spain Sternberg Astronomical Institute Moscow State University Moscow119234 Russia Kazan Federal University Kazan Russia Institute of Astrophysics Foundation for Research and Technology-Hellas Heraklion Crete71110 Greece University of Crete Physics Department Institute of Theoretical & Computational Physics Heraklion Crete70013 Greece Department of Physics Systems Engineering and Signal Theory University of Alicante AlicanteE-03690 Spain University Institute of Physics Applied to Sciences and Technologies University of Alicante AlicanteE-03690 Spain Department of Physics and Astronomy University of Turku FI-20014 Finland Space Research Institute The Russian Academy of Sciences Profsoyuznaya Str. 84/32 Moscow117997 Russia School of Physics and Astronomy Faculty of Physical Sciences and Engineering University of Southampton SouthamptonSO17 1BJ United Kingdom Erwin-Rommel-Strae 1 Erlangen91058 Germany Universidad Internacional de Valencia - VIU C/Pintor Sorolla 21 Valencia46002 Spain E-28692 Spain Institut für Astronomie und Astrophysik Universität Tübingen Sand 1 Tübingen

High mass X-ray binaries are among the brightest X-ray sources in the Milky Way, as well as in nearby Galaxies. Thanks to their highly variable emissions and complex phenomenology, they have attracted the interest of the high energy astrophysical community since the dawn of X-ray Astronomy. In more recent years, they have challenged our comprehension of physical processes in many more energy bands, ranging from the infrared to very high energies. In this review, we provide a broad but concise summary of the physical processes dominating the emission from high mass X-ray binaries across virtually the whole electromagnetic spectrum. These comprise the interaction of stellar winds with the high gravitational and magnetic fields of compact objects, the behaviour of matter under extreme magnetic and gravity conditions, and the perturbation of the massive star evolutionary processes by presence in a binary system. We highlight the role of the INTEGRAL mission in the discovery of many of the most interesting objects in the high mass X-ray binary class and its contribution in reviving the interest for these sources over the past two decades. We show how the INTEGRAL discoveries have not only contributed to significantly increase the number of high mass X-ray binaries known, thus advancing our understanding of the population as a whole, but also have opened new windows of investigation that stimulated the multi-wavelength approach nowadays common in most astrophysical research fields. We conclude the review by providing an overview of future facilities being planned from the X-ray to the very high energy domain that will hopefully help us in finding an answer to the many questions left open after more than 18 years of INTEGRAL scientific observations. Copyright © 2020, The Authors. All rights reserved.

关键词： Galaxies

Is the winner really the best? A critical analysis of common research practice in biomedical image analysis competitions

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arXiv 2018年

作者： Maier-Hein, Lena Eisenmann, Matthias Reinke, Annika Onogur, Sinan Stankovic, Marko Scholz, Patrick Arbel, Tal Bogunovic, Hrvoje Bradley, Andrew P. Carass, Aaron Carolin Feldmann Frangi, Alejandro F. Ful, Peter M. van Ginneken, Bram Hanbury, Allan Honauer, Katrin Kozubek, Michal Landman, Bennett A. Marz, Keno Maier, Oskar Maier-Hein, Klaus Menze, Bjoern H. Müller, Henning Neher, Peter F. Niessen, Wiro Rajpoot, Nasir Sharp, Gregory C. Sirinukunwattana, Korsuk Speidel, Stefanie Stock, Christian Stoyanov, Danail Taha, Abdel Aziz van der Sommen, Fons Wang, Ching-Wei Weber, Marc-André Zheng, Guoyan Jannin, Pierre Kopp-Schneider, Annette Heidelberg Germany Centre for Intelligent Machines McGill University MontrealQC Canada Christian Doppler Laboratory for Ophthalmic Image Analysis Department of Ophthalmology Medical University Vienna Vienna Austria Science and Engineering Faculty Queensland University of Technology BrisbaneQLD Australia Department of Electrical and Computer Engineering Department of Computer Science Johns Hopkins University Baltimore United States CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine University of Sheffield Sheffield United Kingdom Department of Radiology and Nuclear Medicine Medical Image Analysis Radboud University Center Nijmegen Netherlands Institute of Information Systems Engineering TU Wien Vienna Austria Heidelberg University Heidelberg Germany Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Electrical Engineering Vanderbilt University NashvilleTN United States Institute of Medical Informatics Universität zu Lübeck Lübeck Germany Heidelberg Germany Institute for Advanced Studies Department of Informatics Technical University of Munich Munich Germany Information System Institute HES-SO Sierre Switzerland Departments of Radiology Nuclear Medicine and Medical Informatics Erasmus MC Rotterdam Netherlands Department of Computer Science University of Warwick Coventry United Kingdom Department of Radiation Oncology Massachusetts General Hospital BostonMA United States Institute of Biomedical Engineering University of Oxford Oxford United Kingdom National Center for Tumor Diseases Dresden Dresden Germany Heidelberg Germany Department of Computer Science University College London London United Kingdom Data Science Studio Research Studios Austria FG Vienna Austria Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands AIExplore NTUST Center of Computer Vision and Medical Imaging Graduate Institute of Biomedical Engineering National Ta

International challenges have become the standard for validation of biomedical image analysis methods. Given their scientific impact, it is surprising that a critical analysis of common practices related to the organization of challenges has not yet been performed. In this paper, we present a comprehensive analysis of biomedical image analysis challenges conducted up to now. We demonstrate the importance of challenges and show that the lack of quality control has critical consequences. First, reproducibility and interpretation of the results is often hampered as only a fraction of relevant information is typically provided. Second, the rank of an algorithm is generally not robust to a number of variables such as the test data used for validation, the ranking scheme applied and the observers that make the reference annotations. To overcome these problems, we recommend best practice guidelines and define open research questions to be addressed in the future. Copyright © 2018, The Authors. All rights reserved.

关键词： Quality control

Consistency guarantees for greedy permutation-based causal inference algorithms

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arXiv 2017年

作者： Solus, Liam Wang, Yuhao Uhler, Caroline Institutionen för Matematik KTH StockholmSE-100 44 Sweden Institute for Interdisciplinary Information Sciences Tsinghua University Beijing China Shanghai Qi Zhi Institute Shanghai China Department of Electrical Engineering and Computer Science Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA United States

Directed acyclic graphical models, or DAG models, are widely used to represent complex causal systems. Since the basic task of learning such a model from data is NP-hard, a standard approach is greedy search over the space of directed acyclic graphs or Markov equivalence classes of directed acyclic graphs. As the space of directed acyclic graphs on p nodes and the associated space of Markov equivalence classes are both much larger than the space of permutations, it is desirable to consider permutation-based greedy searches. Here, we provide the first consistency guarantees, both uniform and high-dimensional, of a greedy permutation-based search. This search corresponds to a simplex-like algorithm operating over the edge-graph of a sub-polytope of the permutohedron, called a DAG associahedron. Every vertex in this polytope is associated with a directed acyclic graph, and hence with a collection of permutations that are consistent with the directed acyclic graph ordering. A walk is performed on the edges of the polytope maximizing the sparsity of the associated directed acyclic graphs. We show via simulated and real data that this permutation search is competitive with current approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： Bayesian networks

Direct evidence for shock-powered optical emission in a nova

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arXiv 2020年

作者： Aydi, Elias Sokolovsky, Kirill V. Chomiuk, Laura Steinberg, Elad Li, Kwan Lok Vurm, Indrek Metzger, Brian D. Strader, Jay Mukai, Koji Pejcha, Ondřej Shen, Ken J. Wade, Gregg A. Kuschnig, Rainer Moffat, Anthony F.J. Pablo, Herbert Pigulski, Andrzej Popowicz, Adam Weiss, Werner Zwintz, Konstanze Izzo, Luca Pollard, Karen R. Handler, Gerald Ryder, Stuart D. Filipović, Miroslav D. Alsaberi, Rami Z.E. Manojlović, Perica de Oliveira, Raimundo Lopes Walter, Frederick M. Vallely, Patrick J. Buckley, David A.H. Brown, Michael J.I. Harvey, Eamonn J. Kawash, Adam Kniazev, Alexei Kochanek, Christopher S. Linford, Justin Mikolajewska, Joanna Molaro, Paolo Orio, Marina Page, Kim L. Shappee, Benjamin J. Sokoloski, Jennifer L. Center for Data Intensive and Time Domain Astronomy Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Sternberg Astronomical Institute Moscow State University Universitetskii pr. 13 Moscow119992 Russia Astro Space Center of Lebedev Physical Institute Profsoyuznaya St. 84/32 Moscow117997 Russia Columbia Astrophysics Laboratory Department of Physics Columbia University New YorkNY10027 United States Racah Institute of Physics Hebrew University Jerusalem91904 Israel Department of Physics UNIST Ulsan44919 Korea Republic of Institute of Astronomy National Tsing Hua University Hsinchu30013 Taiwan Tartu Observatory University of Tartu Tõravere Tartumaa61602 Estonia CRESST X-ray Astrophysics Laboratory NASA GSFC GreenbeltMD20771 United States Department of Physics University of Maryland Baltimore County 1000 Hilltop Circle BaltimoreMD21250 United States Institute of Theoretical Physics Faculty of Mathematics and Physics Charles University Prague Czech Republic Department of Astronomy Theoretical Astrophysics Center University of California BerkeleyCA94720 United States Department of Physics and Space Science Royal Military College of Canada PO Box 17000 Station Forces KingstonONK7K 7B4 Canada Institute of Communication Networks and Satellite Communications Graz University of Technology Infeldgasse 12 Graz8010 Austria Dépt. de Physique Univ. De Montréal C.P. 6128 Succ. Centre-Ville Centre de Recherche en Astrophysique du Quéebec MontréealQCH3C 3J7 Canada AAVSO 49 Bay State Rd CambridgeMA02138 United States Instytut Astronomiczny Uniwersytet Wroclawski Kopernika 11 Wroclaw51-622 Poland Silesian University of Technology Institute of Electronics Akademicka 16 Gliwice44-100 Poland Institute for Astrophysics University of Vienna Tuerkenschanzstrasse 17 ViennaA-1180 Austria Universität Innsbruck Institut für Astro- und Teilchenphysik Technikerstrasse 25 InnsbruckA-6020 Austria D

Classical novae are thermonuclear explosions that occur on the surfaces of white dwarf stars in interacting binary systems1. It has long been thought that the luminosity of classical novae is powered by continued nuclear burning on the surface of the white dwarf after the initial runaway2. However, recent observations of GeV γrays from classical novae have hinted that shocks internal to the nova ejecta may dominate the nova emission. Shocks have also been suggested to power the luminosity of events as diverse as stellar mergers3, supernovae4, and tidal disruption events5, but observational confirmation has been lacking. Here we report simultaneous space-based optical and γ-ray observations of the 2018 nova V906 Carinae (ASASSN-18fv), revealing a remarkable series of distinct correlated flares in both bands. The optical and γ-ray flares occur simultaneously, implying a common origin in shocks. During the flares, the nova luminosity doubles, implying that the bulk of the luminosity is shock-powered. Furthermore, we detect concurrent but weak X-ray emission from deeply embedded shocks, confirming that the shock power does not appear in the X-ray band and supporting its emergence at longer wavelengths. Our data, spanning the spectrum from radio to γ-ray, provide direct evidence that shocks can power substantial luminosity in classical novae and other optical transients. Copyright © 2020, The Authors. All rights reserved.

关键词： Luminance

On benefits of selection diversity via bilevel exclusive sparsity

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On benefits of selection diversity via bilevel exclusive spa...

2016 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2016

作者： Yang, Haichuan Huang, Yijun Tran, Lam Liu, Ji Huang, Shuai Department of Computer Science University of Rochester United States Goergen Institute for Data Science University of Rochester United States Department of Industrial and Systems Engineering University of Washington United States

ISBN: (纸本)9781467388511

Sparse feature (dictionary) selection is critical for various tasks in computer vision, machine learning, and pattern recognition to avoid overfitting. While extensive research efforts have been conducted on feature selection using sparsity and group sparsity, we note that there has been a lack of development on applications where there is a particular preference on diversity. That is, the selected features are expected to come from different groups or categories. This diversity preference is motivated from many real-world applications such as advertisement recommendation, privacy image classification, and design of survey. In this paper, we proposed a general bilevel exclusive sparsity formulation to pursue the diversity by restricting the overall sparsity and the sparsity in each group. To solve the proposed formulation that is NP hard in general, a heuristic procedure is proposed. The main contributions in this paper include: 1) A linear convergence rate is established for the proposed algorithm; 2) The provided theoretical error bound improves the approaches such as L1norm and L0types methods which only use the overall sparsity and the quantitative benefits of using the diversity sparsity is provided. To the best of our knowledge, this is the first work to show the theoretical benefits of using the diversity sparsity; 3) Extensive empirical studies are provided to validate the proposed formulation, algorithm, and theory.

关键词： Feature extraction

Authorship Correction: International Changes in COVID-19 Clinical Trajectories Across 315 Hospitals and 6 Countries: Retrospective Cohort Study

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Journal of medical Internet research 2021年第11期23卷 e34625页

作者： Griffin M Weber Harrison G Zhang Sehi L'Yi Clara-Lea Bonzel Chuan Hong Paul Avillach Alba Gutiérrez-Sacristán Nathan P Palmer Amelia Li Min Tan Xuan Wang William Yuan Nils Gehlenborg Anna Alloni Danilo F Amendola Antonio Bellasi Riccardo Bellazzi Michele Beraghi Mauro Bucalo Luca Chiovato Kelly Cho Arianna Dagliati Hossein Estiri Robert W Follett Noelia García Barrio David A Hanauer Darren W Henderson Yuk-Lam Ho John H Holmes Meghan R Hutch Ramakanth Kavuluru Katie Kirchoff Jeffrey G Klann Ashok K Krishnamurthy Trang T Le Molei Liu Ne Hooi Will Loh Sara Lozano-Zahonero Yuan Luo Sarah Maidlow Adeline Makoudjou Alberto Malovini Marcelo Roberto Martins Bertrand Moal Michele Morris Danielle L Mowery Shawn N Murphy Antoine Neuraz Kee Yuan Ngiam Marina P Okoshi Gilbert S Omenn Lav P Patel Miguel Pedrera Jiménez Robson A Prudente Malarkodi Jebathilagam Samayamuthu Fernando J Sanz Vidorreta Emily R Schriver Petra Schubert Pablo Serrano Balazote Byorn Wl Tan Suzana E Tanni Valentina Tibollo Shyam Visweswaran Kavishwar B Wagholikar Zongqi Xia Daniela Zöller Isaac S Kohane Tianxi Cai Andrew M South Gabriel A Brat Department of Biomedical Informatics Harvard Medical School Boston MA United States. BIOMERIS (BIOMedical Research Informatics Solutions) Pavia Italy. Clinical Research Unit Botucatu Medical School São Paulo State University Botucatu Brazil. Division of Nephrology Department of Medicine Ente Ospedaliero Cantonale Lugano Switzerland. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Information Technology Department Azienda Socio-Sanitaria Territoriale di Pavia Pavia Italy. Unit of Internal Medicine and Endocrinology Istituti Clinici Scientifici Maugeri SpA SB IRCCS Pavia Italy. Massachusetts Veterans Epidemiology Research and Information Center Veterans Affairs Boston Healthcare System Boston MA United States. Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy. Department of Medicine Massachusetts General Hospital Boston MA United States. Department of Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles CA United States. Health Informatics Hospital Universitario 12 de Octubre Madrid Spain. Department of Learning Health Sciences University of Michigan Medical School Ann Arbor MI United States. Department of Biomedical Informatics University of Kentucky Lexington KY United States. Department of Biostatistics Epidemiology and Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Institute for Biomedical Informatics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States. Department of Preventive Medicine Northwestern University Chicago IL United States. Institute for Biomedical Informatics University of Kentucky Lexington KY United States. Medical University of South Carolina Charleston SC United States. Department of Computer Science Renaissance Computing Institute University of North Carolina at Chapel Hill Chapel Hill NC United States. Departm

[This corrects the article DOI: 10.2196/31400.].

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Fundamental limits and tradeoffs in autocatalytic pathways

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arXiv 2017年

作者： Siami, Milad Motee, Nader Buzi, Gentian Bamieh, Bassam Khammash, Mustafa Doyle, John C. Institute for Data Systems and Society Massachusetts Institute of Technology CambridgeMA02319 United States Department of Mechanical Engineering and Mechanics Packard Laboratory Lehigh University BethlehemPA18015 United States State University of New York at Fredonia Department of Mechanical Engineering University of California Santa BarbaraCA93106 United States Department of Biosystems Science and Engineering Eth Zurich Mattenstrasse 26 Basel4058 Switzerland Control and Dynamical Systems California Institute of Technology PasadenaCA91125 United States

This paper develops some basic principles to study au-tocatalytic networks and exploit their structural properties in order to characterize their inherent fundamental limits and tradeoffs. In a dynamical system with autocatalytic structure, the system's output is necessary to catalyze its own production. We consider a simplified model of Glycolysis pathway as our motivating application. First, the properties of these class of pathways are investigated through a simplified two-state model, which is obtained by lumping all the intermediate reactions into a single intermediate reaction. Then, we generalize our results to autocatalytic pathways that are composed of a chain of enzymatically catalyzed intermediate reactions. We explicitly derive a hard limit on the minimum achievable L2-gain disturbance attenuation and a hard limit on its minimum required output energy. Finally, we show how these resulting hard limits lead to some fundamental tradeoffs between transient and steady-state behavior of the network and its net production. Copyright © 2017, The Authors. All rights reserved.

关键词： Dynamical systems

Key questions for modelling covid-19 exit strategies

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arXiv 2020年

作者： Thompson, Robin N. Hollingsworth, T. Déirdre Isham, Valerie Arribas-Bel, Daniel Ashby, Ben Britton, Tom Challenor, Peter Chappell, Lauren H.K. Clapham, Hannah Cunniffe, Nik J. Dawid, A. Philip Donnelly, Christl A. Eggo, Rosalind Funk, Sebastian Gilbert, Nigel Gog, Julia R. Glendinning, Paul Hart, William S. Heesterbeek, Hans House, Thomas Keeling, Matt Kiss, Istvan Z. Kretzschmar, Mirjam Lloyd, Alun L. McBryde, Emma S. McCaw, James M. Miller, Joel C. McKinley, Trevelyan J. Morris, Martina O’Neill, Philip D. Pearson, Carl A.B. Parag, Kris V. Pellis, Lorenzo Pulliam, Juliet R.C. Ross, Joshua V. Tildesley, Michael J. Tomba, Gianpaolo Scalia Silverman, Bernard W. Struchiner, Claudio J. Trapman, Pieter Webb, Cerian R. Mollison, Denis Restif, Olivier Mathematical Institute University of Oxford Woodstock Road OxfordOX2 6GG United Kingdom University of Oxford St Aldates OxfordOX1 1DP United Kingdom Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine Keppel Street LondonWC1E 7HT United Kingdom Big Data Institute University of Oxford Old Road Campus OxfordOX3 7LF United Kingdom Department of Statistical Science University College London Gower Street LondonWC1E 6BT United Kingdom School of Environmental Sciences University of Liverpool Brownlow Street LiverpoolL3 5DA United Kingdom Alan Turing Institute British Library 96 Euston Road LondonNW1 2DB United Kingdom Department of Mathematical Sciences University of Bath North Road BathBA2 7AY United Kingdom Department of Mathematics Stockholm University Kräftriket Stockholm106 91 Sweden College of Engineering Mathematical and Physical Sciences University of Exeter ExeterEX4 4QE United Kingdom Department of Plant Sciences University of Oxford South Parks Road OxfordOX1 3RB United Kingdom Saw Swee Hock School of Public Health National University of Singapore 12 Science Drive Singapore117549 Singapore Department of Plant Sciences University of Cambridge Downing Street CambridgeCB2 3EA United Kingdom Statistical Laboratory University of Cambridge Wilberforce Road CambridgeCB3 0WB United Kingdom Department of Statistics University of Oxford St Giles’ OxfordOX1 3LB United Kingdom Department of Infectious Disease Epidemiology Imperial College Norfolk Place LondonW2 1PG United Kingdom Department of Sociology University of Surrey Stag Hill GuildfordGU2 7XH United Kingdom Centre for Mathematical Sciences University of Cambridge Wilberforce Road CambridgeCB3 0WA United Kingdom Department of Mathematics University of Manchester Oxford Road ManchesterM13 9PL United Kingdom Department of Population Health Sciences Utrecht University Yalelaan Utrecht3584 CL Netherlands IBM Research Hartree Centre Daresbury

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement lockdown exit strategies that allow restrictions to be relaxed while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton institute "Models for an exit strategy" workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, will allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. The roadmap requires a global collaborative effort from the scientific community and policy-makers, and is made up of three parts: i) improve estimation of key epidemiological parameters;ii) understand sources of heterogeneity in populations;iii) focus on requirements for data collection, particularly in Low-to-Middle-Income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health. Copyright © 2020, The Authors. All rights reserved.

关键词： SARS