How individual mobility affects COVID-19 risk exposure: A study using a spatial network framework

Keywords: COVID-19, Spatial network, mobility
Abstract Type: Paper Abstract

Abstract

The transmission risk of infectious diseases is highly heterogeneous across space and time. Most studies to date focused on human movement and COVID-19 at highly aggregated levels, which may overestimate or underestimate individual activity-related exposures. This study seeks to examine the underlying mechanisms through which individual mobility affects COVID-19 exposure using a spatial network framework, and compare the results with that using a density-based approach. First, we construct a spatial network of COVID-19 transmission during the 1st-4th waves in Hong Kong using individual contact tracing data. Risk level of each node is characterized by interaction intensity between the node and other nodes in the network. Then, by using 2-day individual GPS trajectory data and travel diaries collected from 221 participants in two communities in Hong Kong (one is located in an inner-city urban area and the other is located in a suburban area), we analyze individual mobility patterns and quantify its influence on individual exposure to COVID-19 transmission risk in these two communities. We further examine the COVID-19 risk associated with individual movement from multiple dimensions, including individual socioeconomic characteristics, trip purposes, and mobility flexibility. The findings of this study demonstrate the power of a spatial network framework in greatly enhancing our understanding of the risk of individual exposure to infectious diseases and in helping reduce social inequalities in exposure to COVID-19.