Infectious Dynamics of Pandemics: Mathematical and statistical challenges in understanding the dynamics of infectious disease pandemics

Created: 2020-05-11 10:35
Institution: Isaac Newton Institute for Mathematical Sciences
Description: Organisers:
Deirdre Hollingsworth University of Oxford
Julia Gog University of Cambridge
Hans Heesterbeek Universiteit Utrecht
Valerie Isham University College London, University of Warwick
Denis Mollison Heriot-Watt University
Phil O'Neill University of Nottingham
Sylvia Richardson University of Cambridge
Nigel Shadbolt University of Oxford
Caroline Trotter University of Cambridge
Alan Wilson The Alan Turing Institute

Due to current events, this is a virtualised programme

Programme Description

Mathematical modelling has played an unprecedented role in informing public health policy on the control of the current COVID19 pandemic. Infectious disease modelling groups in the UK and globally have necessarily been working in ‘response’ mode to provide real-time modelling of the pandemic as it unfolds. However, this has left limited time for longer-term thinking about the challenges of understanding the dynamics of this particular pandemic. There is therefore an additional need for experts to discuss, explore and analyse surrounding issues including model assumptions, strategies for surveillance, contact tracing, use of diagnostics, and social distancing. A key aim of this programme is to address this need for longer-term thinking.

This programme will support the activities of the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) programme through additional capacity to provide rapid assessment of strategies of immediate policy relevance. Furthermore, programme participants will provide critical assessment of extant models, considering alternatives and identifying improvements. This is vital to avoid duplication of effort and the potential for analyses which misinterpret key aspects of the epidemiology or make incorrect assumptions regarding underlying data. Finally, this programme will provide the space for considered, collaborative thinking, providing new ideas and directions, forging novel interdisciplinary links as well as reflecting on lessons learned for future pandemics with regard to planning, prevention and control.

Through a range of virtual events this programme will bring together researchers from a broad range of disciplines, from applied epidemiology to fundamental mathematics. Events will include virtual study groups and webinars. It is hoped that this programme will provide a community of researchers to support the mathematical modelling work to address this current pandemic globally.


Details of Workshops 1 and 2 are given below. Details for subsequent workshops will be posted in due course.

Workshop 1: Models for an exit strategy, 11-15 May

Following the successful reduction in transmission in many countries, questions of how and when to lift interventions are being asked. In this workshop we will address the models and underlying assumptions which would be used to inform these discussion by evaluating assumptions underlying possible exit strategies. This will include measurement and modelling of contacts, immunity, surveillance, and transmission route, and will include participants from both infectious disease modelling and other fields. This workshop will branch out into a number of different work streams over the following weeks.

Models old and new, 18-22 May

This workshop will examine, compare and discuss the approaches being currently used for modelling the pandemic with potential new approaches. Participants from outside the traditional epidemiological modelling field can bring experience of modelling, for example, behaviour, movement and social structure, as well as of computational optimisation and data visualisation.


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