  The spread of pandemics such as COVID-19 is strongly linked to human
activities. The objective of this paper is to specify and examine early
indicators of disease spread risk in cities during the initial stages of
outbreak based on patterns of human activities obtained from digital trace
data. In this study, the Venables distance (D_v), and the activity density
(D_a) are used to quantify and evaluate human activities for 193 US counties,
whose cumulative number of confirmed cases was greater than 100 as of March 31,
2020. Venables distance provides a measure of the agglomeration of the level of
human activities based on the average distance of human activities across a
city or a county (less distance could lead to a greater contact risk). Activity
density provides a measure of level of overall activity level in a county or a
city (more activity could lead to a greater risk). Accordingly, Pearson
correlation analysis is used to examine the relationship between the two human
activity indicators and the basic reproduction number in the following weeks.
The results show statistically significant correlations between the indicators
of human activities and the basic reproduction number in all counties, as well
as a significant leader-follower relationship (time lag) between them. The
results also show one to two weeks' lag between the change in activity
indicators and the decrease in the basic reproduction number. This result
implies that the human activity indicators provide effective early indicators
for the spread risk of the pandemic during the early stages of the outbreak.
Hence, the results could be used by the authorities to proactively assess the
risk of disease spread by monitoring the daily Venables distance and activity
density in a proactive manner.
