Key questions for modelling COVID-19 exit strategies.

Robin N Thompson ,Julia R Gog,Pieter Trapman,Tom Britton,Denis Mollison,Emma S Mcbryde,Peter Challenor,Bernard W Silverman,Thomas House,Valerie Isham,Lorenzo Pellis,Trevelyan J Mckinley,Martina Morris,Alun L Lloyd,István Z Kiss,Paul Glendinning,Ben Ashby,T Déirdre Hollingsworth,Lauren H K Chappell,Gianpaolo Scalia Tomba,Joshua V Ross,Carl A B Pearson,Sebastian Funk,Michael J Tildesley,Christl A Donnelly,James M Mccaw,Joel C Miller,Nigel Gilbert,Nik J Cunniffe,Olivier Restif,J.a.p Heesterbeek ,Cerian Ruth Webb ,Rosalind M Eggo ,A P Dawid ,Kris V Parag ,Mirjam Kretzschmar ,Philip D O’neill ,William S Hart ,Daniel Arribas‐Bel ,Matthew James Keeling ,Juliet Pulliam ,Cláudio J Struchiner ,Hannah E Clapham

doi:10.1098/rspb.2020.1405

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.

Highlights

As of 3 August 2020, the coronavirus disease 2019 (COVID-19) pandemic has been responsible for more than 18 million reported cases worldwide, including over 692 000 deaths
We have identified three key challenges for epidemic modellers to help guide exit strategies in data-limited settings: (i) explore policy responses that are robust to missing information; (ii) conduct value-of-information analyses to prioritize additional data collection; and (iii) develop methods that use metadata to interpret epidemiological patterns
SARS-CoV-2 transmission models have played a crucial role in shaping policies in different countries, and their predictions have been a regular feature of media coverage of the pandemic [135,152]

Summary

Introduction

As of 3 August 2020, the coronavirus disease 2019 (COVID-19) pandemic has been responsible for more than 18 million reported cases worldwide, including over 692 000 deaths. This has led to the development of household models [67,88,89,90,91], multilayer networks [92], bipartite networks [93,94] and networks that are geographically and socially embedded to reflect location and travel habits [95] These tools can play a key role in understanding and monitoring transmission, and exploring scenarios, at the point of exiting a lockdown: in particular, they can inform whether or not, and how quickly, households or local networks merge to form larger and possibly denser contact networks in which local outbreaks can emerge. If these are addressed they will aid the planning of future exit strategies

Data needs and communicating uncertainty 8

Summary and discussion

31. Vollmer MAC et al 2020 Report 20

Findings

57. Winter AK et al 2018 Benefits and challenges in