Thompson, RN;
Hollingsworth, TD;
Isham, V;
Arribas-Bel, D;
Ashby, B;
Britton, T;
Challenor, P;
... Restif, O; + view all
(2020)
Key questions for modelling COVID-19 exit strategies.
Proceedings of the Royal Society B: Biological Sciences
, 287
(1932)
10.1098/rspb.2020.1405.
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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.
| Type: | Article |
|---|---|
| Title: | Key questions for modelling COVID-19 exit strategies |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1098/rspb.2020.1405 |
| Publisher version: | https://doi.org/10.1098/rspb.2020.1405 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | Science & Technology, Life Sciences & Biomedicine, Biology, Ecology, Evolutionary Biology, Life Sciences & Biomedicine - Other Topics, Environmental Sciences & Ecology, COVID-19, SARS-CoV-2, exit strategy, mathematical modelling, epidemic control, uncertainty, REPRODUCTION NUMBERS, EPIDEMIC SPREAD, SCHOOL CLOSURE, INFLUENZA, IMPACT, TIME, TRANSMISSION, PROBABILITY, HOUSEHOLDS, CHALLENGES |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10110811 |
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