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Key questions for modelling COVID-19 exit strategies.
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 M; Funk, Sebastian; Gilbert, Nigel; Glendinning, Paul; Gog, Julia R; Hart, William S; Heesterbeek, Hans; House, Thomas; Keeling, Matt; Kiss, István Z; Kretzschmar, Mirjam E; Lloyd, Alun L; McBryde, Emma S; McCaw, James M; McKinley, Trevelyan J; Miller, Joel C; Morris, Martina; O'Neill, Philip D; Parag, Kris V; Pearson, Carl A B; Pellis, Lorenzo; Pulliam, Juliet R C; Ross, Joshua V; Tomba, Gianpaolo Scalia; Silverman, Bernard W; Struchiner, Claudio J; Tildesley, Michael J; Trapman, Pieter; Webb, Cerian R; Mollison, Denis; Restif, Olivier.
  • Thompson RN; Mathematical Institute, University of Oxford, Woodstock Road, Oxford OX2 6GG, UK.
  • Hollingsworth TD; Christ Church, University of Oxford, St Aldates, Oxford OX1 1DP, UK.
  • Isham V; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
  • Arribas-Bel D; Big Data Institute, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
  • Ashby B; Department of Statistical Science, University College London, Gower Street, London WC1E 6BT, UK.
  • Britton T; School of Environmental Sciences, University of Liverpool, Brownlow Street, Liverpool L3 5DA, UK.
  • Challenor P; The Alan Turing Institute, British Library, 96 Euston Road, London NW1 2DB, UK.
  • Chappell LHK; Department of Mathematical Sciences, University of Bath, North Road, Bath BA2 7AY, UK.
  • Clapham H; Department of Mathematics, Stockholm University, Kräftriket, 106 91 Stockholm, Sweden.
  • Cunniffe NJ; College of Engineering, Mathematical and Physical Sciences, University of Exeter, Exeter EX4 4QE, UK.
  • Dawid AP; Department of Plant Sciences, University of Oxford, South Parks Road, Oxford OX1 3RB, UK.
  • Donnelly CA; Saw Swee Hock School of Public Health, National University of Singapore, 12 Science Drive, Singapore 117549, Singapore.
  • Eggo RM; Department of Plant Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EA, UK.
  • Funk S; Statistical Laboratory, University of Cambridge, Wilberforce Road, Cambridge CB3 0WB, UK.
  • Gilbert N; Department of Statistics, University of Oxford, St Giles', Oxford OX1 3LB, UK.
  • Glendinning P; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London W2 1PG, UK.
  • Gog JR; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
  • Hart WS; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
  • Heesterbeek H; Department of Sociology, University of Surrey, Stag Hill, Guildford GU2 7XH, UK.
  • House T; Department of Mathematics, University of Manchester, Oxford Road, Manchester M13 9PL, UK.
  • Keeling M; Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK.
  • Kiss IZ; Mathematical Institute, University of Oxford, Woodstock Road, Oxford OX2 6GG, UK.
  • Kretzschmar ME; Department of Population Health Sciences, Utrecht University, Yalelaan, 3584 CL Utrecht, The Netherlands.
  • Lloyd AL; IBM Research, The Hartree Centre, Daresbury, Warrington WA4 4AD, UK.
  • McBryde ES; Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
  • McCaw JM; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK.
  • McKinley TJ; School of Mathematical and Physical Sciences, University of Sussex, Falmer, Brighton BN1 9QH, UK.
  • Miller JC; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584CX Utrecht, The Netherlands.
  • Morris M; Biomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA.
  • O'Neill PD; Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Queensland 4811, Australia.
  • Parag KV; School of Mathematics and Statistics, University of Melbourne, Carlton, Victoria 3010, Australia.
  • Pearson CAB; College of Medicine and Health, University of Exeter, Barrack Road, Exeter EX2 5DW, UK.
  • Pellis L; Department of Mathematics and Statistics, La Trobe University, Bundoora, Victoria 3086, Australia.
  • Pulliam JRC; Department of Sociology, University of Washington, Savery Hall, Seattle, WA 98195, USA.
  • Ross JV; School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, UK.
  • Tomba GS; MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, Norfolk Place, London W2 1PG, UK.
  • Silverman BW; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
  • Struchiner CJ; South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Jonkershoek Road, Stellenbosch 7600, South Africa.
  • Tildesley MJ; Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, UK.
  • Trapman P; South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Jonkershoek Road, Stellenbosch 7600, South Africa.
  • Webb CR; School of Mathematical Sciences, University of Adelaide, South Australia 5005, Australia.
  • Mollison D; Department of Mathematics, University of Rome Tor Vergata, 00133 Rome, Italy.
  • Restif O; Department of Statistics, University of Oxford, St Giles', Oxford OX1 3LB, UK.
Proc Biol Sci ; 287(1932): 20201405, 2020 08 12.
Article in English | MEDLINE | ID: covidwho-711780
ABSTRACT
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions 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, would 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. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Immunity, Herd / Models, Theoretical Type of study: Observational study / Prognostic study / Qualitative research / Reviews Limits: Child / Humans Language: English Journal: Proc Biol Sci Journal subject: Biology Year: 2020 Document Type: Article Affiliation country: Rspb.2020.1405

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Immunity, Herd / Models, Theoretical Type of study: Observational study / Prognostic study / Qualitative research / Reviews Limits: Child / Humans Language: English Journal: Proc Biol Sci Journal subject: Biology Year: 2020 Document Type: Article Affiliation country: Rspb.2020.1405