  The objective of this paper is to examine population response to COVID-19 and
associated policy interventions through detecting early-warning signals in time
series of visits to points of interest (POIs). Complex systems, such as cities,
demonstrate early-warning signals when they approach phase transitions
responding to external perturbation, including crises, policy changes, and
human behavior changes. In urban systems, population visits to POIs represent a
state in the complex systems that are cities. These states may undergo phase
transitions due to population response to pandemic risks and intervention
policies. In this study, we conducted early-warning signal detection on
population visits to POIs to examine population response to pandemic risks. We
examined two early-warning signals, the increase of autocorrelation at-lag-1
and standard deviation, in time series of population visits to POIs in 17
metropolitan cities in the United States of America. The results show that: (1)
early-warning signals for population response to COVID-19 were detected between
February 14 and March 11, 2020 in 17 cities; (2) detected population response
had started prior to shelter-in-place orders in 17 cities; (3) early-warning
signals detected from the essential POIs visits appeared earlier than those
from non-essential POIs; and 4) longer time lags between detected population
response and shelter-in-place orders led to a less decrease in POI visits. The
results show the importance of detecting early-warning signals during crises in
cities as complex systems. Early-warning signals could provide important
insights regarding the timing and extent of population response to crises to
inform policy makers.
