Key questions for modelling COVID-19 exit strategies.

Robin N Thompson ORCID logo; T Déirdre Hollingsworth; Valerie Isham; Daniel Arribas-Bel; Ben Ashby; Tom Britton; Peter Challenor; Lauren HK Chappell; Hannah Clapham; Nik J Cunniffe; +33 more... A Philip Dawid; Christl A Donnelly; Rosalind M Eggo ORCID logo; Sebastian Funk ORCID logo; Nigel Gilbert; Paul Glendinning; Julia R Gog; William S Hart; Hans Heesterbeek; Thomas House; Matt Keeling; István Z Kiss; Mirjam E Kretzschmar; Alun L Lloyd; Emma S McBryde; James M McCaw; Trevelyan J McKinley; Joel C Miller; Martina Morris; Philip D O'Neill; Kris V Parag; Carl AB Pearson ORCID logo; Lorenzo Pellis; Juliet RC Pulliam; Joshua V Ross; Gianpaolo Scalia Tomba; Bernard W Silverman; Claudio J Struchiner; Michael J Tildesley; Pieter Trapman; Cerian R Webb; Denis Mollison; Olivier Restif; (2020) Key questions for modelling COVID-19 exit strategies. PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 287 (1932). 20201405-. ISSN 0962-8452 DOI: 10.1098/rspb.2020.1405
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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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