COVID-19: Optimal Lockdown

Lead Research Organisation: University of Warwick
Department Name: Statistics

Abstract

The current COVID-19 pandemic has caused whole countries to lockdown, with a huge effect on people's lives and in the economy. Naturally, there are questions about how efficient this lockdown is, and increasing interest in how our country will reduce social distancing measures and eventually go back to normal. We propose to answer some of these questions by using cutting edge epidemiological models for the spread of COVID-19 in the UK using census data to model the typical behaviour of the UK population accurately and then combining this with the increasingly available data from the NHS, PHE and the ONS, which will help us model the spread of COVID-19 in our communities. These models will then be explored in order to design an optimal mitigation strategy based on closing public and commercial venues, or shutting down transport links, and an exit strategy from our lockdown, which will be achieved by reopening such venues or gradually restoring public transports. These strategies will be adapted frequently in response to daily data. Our resulting models and control strategy will be publicly available on a dedicated website, which will be updated frequently as new data becomes available.

Publications

10 25 50
 
Description Our main goal in this project is to develop an epidemiological model, which (a) can utilize mobility information available from tracking devices (e.g.. Google mobility, telephone locations etc.), (b) can provide a data-driven way to decide what should be optimal lock down strategy for a country to combat an on-going pandemic and finally (c) can be updated dynamically with the availability of more up-to-date data.

At the first stage of our work, we have achieved all of these goals by developing an epidemiological model for a nation as a whole which uses Google Mobility data, illustrated its excellent performance in prediction of ongoing COVID-19 pandemic in England and France, provided a dynamic way of deciding optimal lock down strategies. This work is presently under review in PLOS Computational Biology. Further a talk titled "Optimal lock down with Google mobility" illustrating the main findings was given in "Mathematics of Big Data: Lessons from COVID-19" seminar of The Institute of Mathematics and its Applications (IMA), UK on December 15, 2020. This can be found here: https://www.youtube.com/watch?v=vmjy33VkObQ

On the second stage of our work, we are presently working on developing a model which further utilizes commuting information between local authorities in the UK and can provide a dynamic data-driven means to decide optimal lock down strategies for each local authorities specifically.
Exploitation Route The present work provides a way to provide optimal lock down strategy for a country using publicly available dataset. Further development using new sources of datasets can be achieved (e.g.. using data from tracking locations of telephones). Any government decision making bodies can utilize the methodology and results which can help them making decisions in a data-driven manner.
Sectors Communities and Social Services/Policy,Healthcare,Government, Democracy and Justice,Security and Diplomacy

URL https://optimallockdown.github.io/Covid19inEngland/
 
Title Omptimal Lockdown 
Description A Github organization encompassing all the optimal lockdown related works done under this funding. 
Type Of Material Computer model/algorithm 
Year Produced 2021 
Provided To Others? Yes  
Impact Have been used for modelling optimal lockdown. 
URL https://github.com/OptimalLockdown/