Speaker
Description
Understanding social interactions and the structure that arises from them is central to developing realistic epidemic models of many human pathogens. Surveys are often limited in size and limited in the information they can collect. Contact tracing, where contacts of cases are themselves traced and information collected, represents an idea way to collect social mixing information, but is generally restricted to small outbreaks with limited generalisability. The ubiquity of infection and the unprecedented scale and detail of information collected through contact tracing during the COVID-19 pandemic provides a unique opportunity to quantitatively describe in-person social interactions. Here, we investigate patterns of social interactions over space and demography as recorded in the extensive contract tracing data, which includes almost half of the residents of England. We find evidence that interactions were associated with the age, ethnicity and geographical proximity of individuals, but that the importance of these attributes and the pattern of mixing changed during the pandemic. These dynamics were conserved for many parts of the pandemic, however, we observed significant departures during specific time points, indicating a compensatory effect following a release from lockdown. We also explore the utility of mixing patterns information collected a priori in predicting and explaining social interaction dynamics.
