Modelling and inference for pandemic preparedness
MIP
5 August 2024 to 30 August 2024
Programme theme
The INI and the field responded early and astutely to the covid-19 pandemic by organising a special online programme on Infectious Dynamics of Pandemics (IDP, May-December 2020), providing a focal point for the exchange of ideas and communication between groups ‘old and new’ that was badly needed. Activities continued during 2021, leading among other things to a 2022 special issue - Challenges for Future Pandemics - of the Epidemics journal, devoted entirely to important aspects of pandemic dynamics and response.
The pandemic has shown the importance of epidemic modelling, which has been a corner stone of the scientific advice on pandemic response both in the UK and worldwide. As a result, the field is expanding rapidly, driven by novel interactions with other fields, both within the mathematical and statistical sciences, and with a range of other disciplines such as genomics, virology, behavioural sciences, and economics. There is therefore a unique and timely opportunity to support and shape its future research direction and support the next generation of leaders in the field. Thus, Modelling and Inference for Pandemic Preparedness (MIP) is a follow-on workshop to IDP, an in-person one-month research programme that will combine a Discussion meeting in week 1, with three weeks of collaborative research in groups and exchange of ideas, related to two linked themes:
- Modelling and analysis for policy and decision support: The group will focus on transmission modelling for past and future pandemics and the interface with policy. As a group, we will take stock of the recent experience with COVID19; identify gaps in modelling approaches and datasets for future pandemics; and review success and challenges in translating modelling results into policy. Themes of particular interest include the integration of behavioural responses and genomic surveillance in epidemic models; modelling disease transmission and evolution at the animal-human interface; public health, economic and societal impacts of pandemic; new approaches to model medical and non-medical interventions; population heterogeneities; modelling disease threats in LMIC; how to handle uncertainty at various stages of a pandemic.
- Model-based inference and prediction: the theme will discuss and develop new methodology for conducting statistical inference in and across models of infectious diseases. Areas of particular interest will be in computationally efficient methods, software development, uncertainty quantification, network models, multi-model inference and data fusion/calibration. Synergies with the policy theme will support decision making and evidence synthesis under time constraints and uncertainty, with additional aims to determine when and how noisy data can be reliably used to support pandemic response. Data collection and assimilation from new technologies and surveillance procedures will also be discussed in the dimension of pandemic preparedness and response.
Organisers
- Hans Heesterbeek Universiteit Utrecht
- Deirdre Hollingsworth University of Oxford
- Valerie Isham University College London; University of Warwick
- Denis Mollison Heriot-Watt University
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