Summary
The interaction study focuses on how the movements, activities, and interactions of healthcare workers and patients influence patterns of nosocomial transmission of COVID-19. By analysing and predicting these patterns of activity, we will be able advise on policies and practices that might reduce transmission, and identify ways of changing hospital environments to reduce opportunities for infection. We aim to achieve this through two interconnected parts of the study:
Movement Data Analysis: In this study, we combine fine-grained movement data collected on individual healthcare workers with testing data, to establish points of interaction between staff and patients, and potential transmission pathways. The movement datasets we use are derived from existing data sources (e.g., card access doors, healthcare records) and new forms of mobility data (e.g., Bluetooth, Wi-Fi polling). We aim to derive a comprehensive picture of interactions and transmissions within the hospital settings in which we work.
Transmission Modelling: Building on our empirical studies, our modelling work looks at simulating patterns of healthcare worker movement and interaction, and the conditions under which different transmission patterns emerge. Using an agent-based modelling environment, we will test different assumptions and policies for their effect on transmission rates, with a view to ‘road testing’ interventions before implementation. These models will build on theoretical models of human behaviour and decision making, and on the empirical findings from our analysis research.
Interaction and Movement Team