Waves, Lock-Downs, and Vaccines - Decision Support and Model with Superb Geographical and Sociological Resolution

Lead Research Organisation: Durham University
Department Name: Physics

Abstract

This proposal aims at further developing, validating, and deploying the JUNE model for the simulation of the spread of COVID-19 in the United Kingdom and the impact of medical and non-medical mitigation strategies. Recently constructed, JUNE combines superb geographical and sociological resolution in its virtual population model with a detailed, flexible and adjustable simulation of daily activities and the ability to include mitigation strategies and other interventions, to asses their effect. JUNE is already being used by NHS England to gain insights into the nature of the disease and the dynamics of its spreading, thereby informing operational planning and supporting decisions.

In this proposal we will
1. continue to provide valuable insights for the NHS, PHE, and the UK government, for example the impact of further complete or partial lock-downs, of the tier system and possible extensions and modifications, and of different vaccination protocols. This includes, in particular, the application of cutting-edge Bayesian methods for uncertainty quantification in projections of possible futures, and the development of robust data assimilation protocols to improve short-term predictions.
2. further refine the population model, with special emphasis on the transmission dynamics and conditions in minorities and on the effect of socio-economic factors on infection and fatality rates. We will also include models for multiple infectious diseases affecting the population concurrently, to quantify the impact of seasonal flu the resulting demands on the health care system.

As a by-product we will fully document the code and produce a convenient user-interface, to facilitate its use in future epidemics, thereby turning it into an enduring national asset.
 
Description We have updated our agent-based model to include various (COVID) variants as quasi independent infections, which interact differently with newly included flexible vaccination strategies. This allowed us to continue providing high-quality projections of future epidemic dynamics to the NHS and has led to a collaboration with PHE/UKHSA who want to use our model for ongoing and future epidemics. We also started to investigate various scenarios for why vaccine efficacy is waning.
Most of the objectives charted in the timeline of the proposal have been met, so the project was, by far and large, successful.
Our code being open-source will allow its application to a wide rang of settings; in a parallel project we collaborate with WHO and UN to roll it out for refugee camps.
Exploitation Route Open-source code can be rolled out in a wide range of settings.
Sectors Communities and Social Services/Policy

Healthcare

 
Description Operational planning by NHS England for the ongoing COVID epidemic and its various waves. Emerging collaboration with UKHSA (formerly PHE) to re-purpose our code for other, human-to-human transmitted diseases such as seasonal flu etc., and to support their planning and forecasting. The code has also been used by the UN and WHO to investigate the impact of COVID on refugee camps. In an ongoing project it is being utilised to optimise the design of such settlements to enhance resilience to epidemics.
First Year Of Impact 2021
Sector Healthcare
Impact Types Societal

 
Description Providing projections on Delta and Omicron for the NHS through Kevin Fong
Geographic Reach National 
Policy Influence Type Participation in a guidance/advisory committee
 
Title JUNE code 
Description Simulation model and code for epidemics with human-to-human transmission dynamics. 
Type Of Material Improvements to research infrastructure 
Year Produced 2021 
Provided To Others? Yes  
Impact Can be repurposed for any human-to-human transmissible disease in any large-scale population. 
URL https://github.com/IDAS-Durham/JUNE
 
Description United Nations / Cox's Bazaar 
Organisation United Nations (UN)
Country United States 
Sector Public 
PI Contribution Provision of JUNE model and adaptation to Cox's Bazaar (Bangladesh)
Collaborator Contribution Data insights: Population/demographics of Cox's Bazaar, COVID infection and impact.
Impact Ongoing analysis; some first publication submitted to BMJ (and accepted, but doi still missing).
Start Year 2021
 
Title JUNE 
Description JUNE model to simulate epidemics with human-to-human transmission dynamics, in large-scale populations 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
Impact Decision support fror NHS etc. 
 
Description bi-weekly collaboration meetings with PHE/UKHSA 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact bi-weekly collaboration meetings with PHE/UKHSA, to turn JUNE into one of their central simulation tools
Year(s) Of Engagement Activity 2021,2022