Interplay between intra-urban population density and mobility in determining the spread of epidemics

Abstract

In this work, we address the connection between population density centers in urban areas, and the nature of human flows between such centers, in shaping the vulnerability to the onset of contagious diseases. A study of 163 cities, chosen from four different continents reveals a universal trend, whereby the risk induced by human mobility increases in those cities where mobility flows are predominantly between high population density centers. We apply our formalism to the spread of SARS-COV-2 in the United States, providing a plausible explanation for the observed heterogeneity in the spreading process across cities. Armed with this insight, we propose realistic mitigation strategies (less severe than lockdowns), based on modifying the mobility in cities. Our results suggest that an optimal control strategy involves an asymmetric policy that restricts flows entering the most vulnerable areas but allowing residents to continue their usual mobility patterns.

Analysis of Spatial and Spatiotemporal Anomalies Using Persistent Homology: Case Studies with COVID-19 Data

“…1 It is important to examine such anomalies, as COVID-19 spreads with significant spatial heterogeneity and thus has heterogeneous effects on different areas. 2 Many factors (such as mobility, population density, socioeconomic differences, and racial demographics) play a role in how COVID-19 affects regions differently [9,19,20]. In our case study of COVID-19 case rates in LA, we construct a vineyard that (1) identifies which anomalies are most persistent in time and (2) reveals how the anomalies move geographically over time.…”