JUNIPER Partnership

Lead Research Organisation: University of Cambridge
Department Name: Applied Maths and Theoretical Physics

Abstract

The COVID-19 pandemic placed public health and epidemiology in the public and political spotlight. During the pandemic, a range of models and analysis were called upon to help understand the changing patterns of disease and the likely implications of changes to control measures. This led to major scientific advances that have expanded our ideas of what epidemic models can achieve. The existing JUNIPER consortium was instrumental in many of these advances, with developments in identifying and understanding the spread of new variants, the optimal deployment of vaccines, modelling infection dynamics within schools and universities, and making longer-term projections assessing behavioural uncertainties, vaccination and the relaxation of controls.

We now have an opportunity to build on these developments, bringing the ideas that were developed as emergency responses into the mainstream discipline, so that the lessons learned and scientific developments can have the widest benefit. The award will grow the existing JUNIPER consortium into a nationwide resource, with seminars, meetings and collaborative workshops. We will also continue to develop the international aspects of the programme, learning from the best in the world and exporting our knowledge and experience.

This award will also build on the successes and reputation of the existing JUNIPER consortium to enable researchers in a wide number of related disciplines to bring their expertise into predictive models. Our focused interdisciplinary workshops will enable researchers to address key questions such as "how should behaviour be incorporated into epidemiological predictions and what are the key data sources on changing behaviour?" and "how do we make the most of new data sources, such as rapid genomics or environmental sampling, to generate more reliable predictions?"

The science of infectious disease dynamics will be at its most powerful when model development, data sources and policy demands are all aligned. The JUNIPER partnership will ensure that the UK remains a leading force in using pandemic models to address the challenges posed by new outbreaks. Through focused meetings with policy advisors and public health experts, we will ensure that models and data are in place to address key questions that will arise during any novel outbreak, such as "do we need to close schools to protect children or the wider community?" and "who should we target for vaccination to minimise the scale of the outbreak?".

Technical Summary

The JUNIPER partnership will build on UKRI-MRC investments during the COVID-19 pandemic, expanding into a resource for the entire UK infectious disease modelling community. It will provide key activities that could not be achieved by any single group in isolation. The partnership will leverage additional collaborative and interdisciplinary funding to generate the scientific step-change required to address the demands of our field.

The partnership will expand our programme of talks, seminars and workshops to reach more of our research community. The informal workshops and talks have proved an ideal vehicle for presentation by early career researchers, highlighting novel advances in the field, and developing considered approaches to new challenges and opportunities.

Other smaller meetings and workshops will focus on addressing knowledge gaps highlighted by the pandemic, building links with adjacent subject areas and strengthening interactions with policy teams and data providers. The scale of the JUNIPER partnership means we can provide linkage opportunities to a range of experts across institutions. We aim to leverage additional funding, focused towards exploiting the latest scientific insights and addressing knowledge gaps. This will help to sustain JUNIPER over the longer-term and has allowed us to taper our requested support.

In addition, the partnership will support three further on-going activities that will benefit the modelling community:
(i) support for good coding practice and open release of software across institutions through a dedicated Research Software Engineer (with a strong background in epidemiological modelling)
(ii) short-term travel funds for early career researchers to visit other institutions with the principle aims of combining expertise to enable strong fellowship and grant applications
(iii) strength in public engagement by working alongside science writers with ability to communicate complex science to a general audience

Publications

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