Rapid Assistance in Modelling the Pandemic (RAMP - Edinburgh central admin)

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Physics and Astronomy

Abstract

Since the pandemic began, many thousands of researchers have had their work interrupted, with no access to laboratory equipment or travel. They stand willing and to contribute to COVID modelling effort. RAMP addresses the need to coordinate and focus the efforts across the UK. Computer modelling is perhaps unique as an area where capacity is actually enhanced by the lockdown, although we will continue to coordinate projects with new or repurposed funding once restrictions are relaxed until the crisis is truly over.

The unique situation of lockdown and unprecidented importance of COVID has meant that the generation of new knowledge has advanced apace without direct funding. Thousands of apparently COViD related preprints have appeared across medarXiV, arXiV and other preprint servers, and in the inboxes of all prominent scientists in the field. However this body of work is unfocussed, hugely repetitive and often lacks the specificity to deal with the details of the actual crisis we face. The central aim of this project is to provide focus to this effort, and facilitate the knowledge transfer to policy-making.

In addition, we are and will continue to act as a channel for addressing policy questions to the community and escalating promising avenues of work to decision-makers, with co-membership of RAMP and the government's SPI-M and SAGE committees.

RAMP provides a mechanism by which useful work which does not require direct funding can get underway immediately.

Publications

10 25 50

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Ackland GJ (2022) Fitting the reproduction number from UK coronavirus case data and why it is close to 1. in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

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Ackland GJ (2022) The Royal Society RAMP modelling initiative. in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

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Panovska-Griffiths J (2022) Technical challenges of modelling real-life epidemics and examples of overcoming these. in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

 
Description The award continued the efforts of the RAMP initiative to enlist volunteer non-specialists in helping with the epidemic modelling efforts as applied to the coronavirus epidemic. This included coordination and allocation of volunteers to existing groups, discovery, review and validation of of key papers published on archives. New codes were developed in various types of modelling, notably the individual based JUNE code developed at Durham, the compartment PyRoss code developed in Cambridge, and the data driven nowcast, scenario and prediction WSS model in Edinburgh.

The highest profile review work was replicating the projections of the Imperial code widely regarded as the model which introduced the lockdown. We showed that although there were issues with the software quality, the original code nevertheless was completely reliable in reproducing the model

WSS was developed entirely within this project. It is tightly interfaced with UK datastreams to take in the latest case data and make predictions of the short term trajectory of the epidemic. It is the only new model adopted by the Joint Biosecurity Centre to form part of the UK weekly consensus report, alongside the models from members of the SPI-M committee. As it turned out, the WSS projections are rather similar to those from pre-existing models, but being developed outside the existing UK epidemiology community, WSS provides an important bulwark against "groupthink".

In addition, we have worked with microsoft research to develop and deploy the covidUI system which allows policymakers and scientists to run a suite of major codes and compare their outputs for customised scenarios.

https://github.com/gjackland/WSS
https://covid-policy-modelling.github.io/
https://royalsociety.org/topics-policy/Health%20and%20wellbeing/ramp/
https://ramp-forums.epcc.ed.ac.uk/
https://gateway.newton.ac.uk/news/2021-02-10/10378
Exploitation Route The WSS code developed in this project is currently part of the weekly SPI_MO coronavirus modelling status report for R-number and medium term predictions. It will remain part of the official Joint Biosecurity Centre modelling suite until the pandemic ends.
The COVID-UI interface is being adopted by microsoft within their "Project premonition" https://www.microsoft.com/en-us/research/project/project-premonition/
Sectors Healthcare

URL https://github.com/gjackland/WSS
 
Description Discovery that the Imperial covid model predicted that school closures would lad to more deaths in the long term was widely reported in the press, including Today programme and front page of Daily Telegraph. We are not in a position to know what impact this had on policy, but school closures were subsequently de-prioritised as a measure. Via a complete rewrite we demonstrated that the Imperial code correctly reproduces the model it was intended to. Via red-teaming we found a number of minor bugs - one of which was reported by David Davis MP in the House of Commons! Nevertheless, the bugs did not affect the overall conclusions drawn from the paper, or the averaged behaviour of the model. Our WSS model has been incorporated in the SPI-MO and Joint Biosecurity Council weekly reports since October 2021.
First Year Of Impact 2020
Sector Healthcare