A space-time analytical approach to tracing contact patterns in movement data
This seminar discusses the use of movement as a marker to study interactions in humans and animals to better understand their collective behaviors. Leveraging the time-geography framework, this seminar introduces a method to model and analyze concurrent and delayed contact patterns in movement data. The seminar presents two different case studies using real GPS tracking data of animals (tigers and leopards) and humans (people of the same and different households) of different resolutions to highlight the significance of measuring delayed interactions. A number of approaches have been developed to analyze direct interaction (i.e. direct contact or concurrent movement in close spatial proximity and at the same time) using movement data sets. However, fewer studies have focused on capturing delayed interaction via indirect contact (i.e. when individuals visit the same location with a time delay). This seminar further highlights the promising capacity of time-geographic approaches in measuring space-time exposures that might have been missed due to data gaps or irregular sampling rates. This is a major problem in the proximity-based approaches which is employed in most existing contact tracing technologies to prevent the spread of infectious diseases.