Literature DB >> 32781946

Key questions for modelling COVID-19 exit strategies.

Robin N Thompson1,2,3, T Déirdre Hollingsworth4, Valerie Isham5, Daniel Arribas-Bel6,7, Ben Ashby8, Tom Britton9, Peter Challenor10, Lauren H K Chappell11, Hannah Clapham12, Nik J Cunniffe13, A Philip Dawid14, Christl A Donnelly15,16, Rosalind M Eggo3, Sebastian Funk3, Nigel Gilbert17, Paul Glendinning18, Julia R Gog19, William S Hart1, Hans Heesterbeek20, Thomas House21,22, Matt Keeling23, István Z Kiss24, Mirjam E Kretzschmar25, Alun L Lloyd26, Emma S McBryde27, James M McCaw28, Trevelyan J McKinley29, Joel C Miller30, Martina Morris31, Philip D O'Neill32, Kris V Parag16, Carl A B Pearson3,33, Lorenzo Pellis19, Juliet R C Pulliam33, Joshua V Ross34, Gianpaolo Scalia Tomba35, Bernard W Silverman15,36, Claudio J Struchiner37, Michael J Tildesley23, Pieter Trapman9, Cerian R Webb13, Denis Mollison38, Olivier Restif39.   

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.

Entities:  

Keywords:  COVID-19; SARS-CoV-2; epidemic control; exit strategy; mathematical modelling; uncertainty

Mesh:

Year:  2020        PMID: 32781946      PMCID: PMC7575516          DOI: 10.1098/rspb.2020.1405

Source DB:  PubMed          Journal:  Proc Biol Sci        ISSN: 0962-8452            Impact factor:   5.349


  114 in total

1.  Estimating in real time the efficacy of measures to control emerging communicable diseases.

Authors:  Simon Cauchemez; Pierre-Yves Boëlle; Guy Thomas; Alain-Jacques Valleron
Journal:  Am J Epidemiol       Date:  2006-08-03       Impact factor: 4.897

2.  Network frailty and the geometry of herd immunity.

Authors:  Matthew J Ferrari; Shweta Bansal; Lauren A Meyers; Ottar N Bjørnstad
Journal:  Proc Biol Sci       Date:  2006-11-07       Impact factor: 5.349

3.  Modelling the impact of testing, contact tracing and household quarantine on second waves of COVID-19.

Authors:  Alberto Aleta; David Martín-Corral; Ana Pastore Y Piontti; Marco Ajelli; Maria Litvinova; Matteo Chinazzi; Natalie E Dean; M Elizabeth Halloran; Ira M Longini; Stefano Merler; Alex Pentland; Alessandro Vespignani; Esteban Moro; Yamir Moreno
Journal:  Nat Hum Behav       Date:  2020-08-05

4.  The Ongoing Ebola Epidemic in the Democratic Republic of Congo, 2018-2019.

Authors:  Oly Ilunga Kalenga; Matshidiso Moeti; Annie Sparrow; Vinh-Kim Nguyen; Daniel Lucey; Tedros A Ghebreyesus
Journal:  N Engl J Med       Date:  2019-05-29       Impact factor: 91.245

5.  A mathematical model reveals the influence of population heterogeneity on herd immunity to SARS-CoV-2.

Authors:  Tom Britton; Frank Ball; Pieter Trapman
Journal:  Science       Date:  2020-06-23       Impact factor: 47.728

6.  Management of invading pathogens should be informed by epidemiology rather than administrative boundaries.

Authors:  Robin N Thompson; Richard C Cobb; Christopher A Gilligan; Nik J Cunniffe
Journal:  Ecol Modell       Date:  2016-03-24       Impact factor: 2.974

7.  An appeal for practical social justice in the COVID-19 global response in low-income and middle-income countries.

Authors:  Maureen Kelley; Rashida A Ferrand; Kui Muraya; Simukai Chigudu; Sassy Molyneux; Madhukar Pai; Edwine Barasa
Journal:  Lancet Glob Health       Date:  2020-05-14       Impact factor: 26.763

8.  The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study.

Authors:  Kiesha Prem; Yang Liu; Timothy W Russell; Adam J Kucharski; Rosalind M Eggo; Nicholas Davies; Mark Jit; Petra Klepac
Journal:  Lancet Public Health       Date:  2020-03-25

9.  Temperature and precipitation associate with Covid-19 new daily cases: A correlation study between weather and Covid-19 pandemic in Oslo, Norway.

Authors:  Mesay Moges Menebo
Journal:  Sci Total Environ       Date:  2020-05-29       Impact factor: 10.753

10.  Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020.

Authors:  Tapiwa Ganyani; Cécile Kremer; Dongxuan Chen; Andrea Torneri; Christel Faes; Jacco Wallinga; Niel Hens
Journal:  Euro Surveill       Date:  2020-04
View more
  32 in total

1.  Proceedings B 2020: the year in review.

Authors:  Spencer C H Barrett
Journal:  Proc Biol Sci       Date:  2021-01-06       Impact factor: 5.349

2.  Inference of the SARS-CoV-2 generation time using UK household data.

Authors:  Sebastian Funk; Robin N Thompson; William S Hart; Sam Abbott; Akira Endo; Joel Hellewell; Elizabeth Miller; Nick Andrews; Philip K Maini
Journal:  Elife       Date:  2022-02-09       Impact factor: 8.713

Review 3.  Non-pharmaceutical interventions during the COVID-19 pandemic: A review.

Authors:  Nicola Perra
Journal:  Phys Rep       Date:  2021-02-13       Impact factor: 25.600

4.  Trend Analysis and Forecasting the Spread of COVID-19 Pandemic in Ethiopia Using Box-Jenkins Modeling Procedure.

Authors:  Yemane Asmelash Gebretensae; Daniel Asmelash
Journal:  Int J Gen Med       Date:  2021-04-21

5.  Three pre-vaccine responses to Covid-like epidemics.

Authors:  Lai-Sang Young; Zach Danial
Journal:  PLoS One       Date:  2021-05-13       Impact factor: 3.240

6.  Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020.

Authors:  Martin Rypdal; Kristoffer Rypdal; Ola Løvsletten; Sigrunn Holbek Sørbye; Elinor Ytterstad; Filippo Maria Bianchi
Journal:  Int J Environ Res Public Health       Date:  2021-04-08       Impact factor: 3.390

7.  Analytical approximation for invasion and endemic thresholds, and the optimal control of epidemics in spatially explicit individual-based models.

Authors:  Yevhen F Suprunenko; Stephen J Cornell; Christopher A Gilligan
Journal:  J R Soc Interface       Date:  2021-03-31       Impact factor: 4.118

8.  Sensitivity analysis of the infection transmissibility in the UK during the COVID-19 pandemic.

Authors:  Pardis Biglarbeigi; Kok Yew Ng; Dewar Finlay; Raymond Bond; Min Jing; James McLaughlin
Journal:  PeerJ       Date:  2021-02-25       Impact factor: 2.984

9.  Understanding small Chinese cities as COVID-19 hotspots with an urban epidemic hazard index.

Authors:  Tianyi Li; Jiawen Luo; Cunrui Huang
Journal:  Sci Rep       Date:  2021-07-19       Impact factor: 4.379

10.  Strategy to reduce adverse health outcomes in subjects highly vulnerable to COVID-19: results from a population-based study in Northern Italy.

Authors:  Antonio Giampiero Russo; Marino Faccini; Walter Bergamaschi; Antonio Riussi
Journal:  BMJ Open       Date:  2021-03-10       Impact factor: 2.692

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.