Pandemic Resilience
Overview
COVID-19 exposed weaknesses in the UK’s pandemic resilience. A combination of collective intelligence and AI can help us do better next time. Data crucial for managing novel pandemics are inherently fragmented, arising from communities of medics, public health professionals and analysts to describe the spread of the disease, characterise its phenotype, and, with appropriate modelling, inform appropriate policies nationally and locally.
National spatio-temporal datasets describing SARS-CoV-2 hospital testing and community testing, and the extent and effects of the mitigations put in place against it, can be exploited in order to build new AI/machine learning tools for future pandemics—and potentially for mitigating seasonal outbreaks of endemic disease.
Case study
This theme has two research strands:
Improving decision making
First, a suite of machine learning models fuelled by national SARS-CoV-2 pandemic data will demonstrate how the integration of multiple population level indicators could have improved decision making during the pandemic.
Due to the urgency of the need for response, developing and validating the required analytical infrastructure was not possible. With it in place, however, challenges associated with imperfect data can be addressed.
Interventions and responses
Detailed local data can be used to understand localised interventions and spontaneous behavioural responses. Here, relevant AI challenges include:
- establishing the relative value of diverse data streams, at different stages of the pandemic, and their consistency across spatial scales
- the use of anomaly and change point detection to identify meaningful discontinuities
- robust data imputation, pattern completion, bias detection and correction
- evaluating the impact of both vaccination and behavioural change resulting from, for example non-pharmaceutical interventions (and their interactions)
- coping with delay and bias in data capture and clinical outcome results during the exponential growth phase of a new variant
One particular focus is the impact of contact tracing apps on the behaviour of individuals and the public-health messaging around their use.
Two major challenges cut across both strands: quality assurance within a privacy protecting framework and managing the regional heterogeneity of pandemic impact and associated behavioural change.
If these can be overcome, there is the potential to deliver a suite of tools (sensitive to local population properties) that inform policy. By working in collaboration with key stakeholders in government, a set of interactive portals can be developed that effectively inform policy decisions and/or guide individual behaviour.