“Shelter in place.” “Social distance.”
These simple phrases express something deeply
profound: human behavior to defend against a deadly
infection. Their inverses, “human movement” and
“social contact,” convey equally weighty concepts: the
likely route and speed of viral transmission.
Mapping that route and measuring its speed are the objectives of an ongoing
project by former Institute visiting scholars Jonathan Dingel of the University
of Chicago and Kevin Williams from Yale, along with three colleagues.
In a recent Institute working paper, they describe a rich data set they’ve created
expressly for measuring human movement and social contact in the United
States. And they make their data and analytical tools publicly available so
that other researchers can readily use them for pandemic-related research.
The new database and indexes have major potential as real-time roadmaps of the American pandemic.
The data are pinpointed, time-stamped pings emitted by smartphones,
the highly personal devices that most Americans carry, almost always and everywhere. By geolocating and
clocking each ping, the researchers
determine each phone’s whereabouts:
Where is it? What time is it? Is it in a different
location than when it last pinged?
(A rigorous research protocol protects
phone user privacy.)
A phone that doesn’t move for days
on end suggests an owner sheltering
in place, by chance or intention. But
pings that leave a trail show, like breadcrumbs,
that its owner was on the move.
The scholars also gauge each phone’s
proximity to other phones, yielding evidence
of potential human interaction.
Movement and proximity are summarized
by separate indexes, and the
paper traces the paths of each index to
paint a portrait of the nation’s population
during the first months of the pandemic.
Where and when did we move,
and were we close to others?
VICTOR COUTURE, Assistant Professor of Economics, University of British Columbia; JONATHAN I. DINGEL, Associate Professor of Economics, University of Chicago Booth School of Business; ALLISON GREEN, Ph.D. Candidate, Princeton University; JESSIE HANDBURY, Assistant Professor of Real Estate, Wharton School, University of Pennsylvania; KEVIN R. WILLIAMS, Associate Professor of Economics, Yale School of Management
In brief: Both indexes show major
declines in travel and personal visits
in March and April 2020, but regions
varied significantly. Travel from New
York County to other counties collapsed
in March, but not from Houston (Harris
County) to elsewhere in the South
and Southwest. Phone owners from
areas with highly educated residents
decreased travel and social contact at
disproportionately high levels.
These and other preliminary findings
in the paper are intriguing in themselves,
but even more so as indicators
of the database’s power. For epidemiologists,
economists, other researchers,
and policymakers who seek information
about how people are moving in relation to one another and, therefore
how the virus may spread, the new
database and indexes provide real-time
roadmaps of the American pandemic.
Do the data represent U.S.?
The paper begins by describing database
details—data sources and how
they create the indexes, for example.
The researchers are meticulous in
excluding extraneous or unreliable data,
and in reporting limitations and selection
criteria. They’re also careful to protect
user privacy and ensure anonymity.
Because phones are not people, there’s
reasonable concern that their pings don’t
accurately represent where their owners
really are and with whom they share
space. Moreover, not all Americans own
a smartphone, and some demographic
groups are more likely to have them.
By comparing their data with Census
and other standard sources, the scholars
document that, despite these limitations,
their database is broadly representative
of the American population.
Introducing the indexes
The researchers then create two indexes.
The “location exposure index” (LEX)
maps phone location over time: where
a phone is, county by county, state by
state. The “device exposure index” (DEX)
tracks proximity to other phones—are
they in the same commercial or public
venue as another phone?
Both LEX and DEX are defined with
the pandemic in mind. LEX describes
the share of phones in a given location
that pinged from elsewhere during the
prior 14 days, the virus incubation period.
In short, it’s the fraction of potentially
infectious people who have moved
between counties (or states). And DEX
captures overlapping visits to venues on
the same day. (Not same hour, since the
virus can remain viable in the air and on
surfaces for a considerable period.)
They then describe how these indexes
evolved during the first months of the
pandemic. It’s a fascinating picture: the
evolution of social response to ongoing
For instance, on four national maps,
dated at the end of February, March,
April, and May, the scholars plot the fraction
of phones that had pinged during
the previous 14 days in Manhattan, an
early COVID-19 epicenter. The February
29, 2020, map documents substantial
nationwide exposure to incoming New
York County visitors. By the end of April,
the map reveals dramatic decline in
travel from Manhattan.
They then describe how these indexes evolved during the first months of the pandemic. It’s a fascinating picture: the evolution of social response to ongoing biological threat.
The DEX maps tell a similar story.
By late March, overlapping visits in U.S.
counties declined across the nation to
just one-third the levels seen in early
February. By late April, visits had
increased somewhat across the country,
but even through late May, they
remained lower than in early February,
particularly to New York City, California,
A living database
Ultimately, the paper serves as an introduction
to a powerful living database
that reveals how we’re responding to
the threat of contagious disease and
death, whether by limiting our travel
and visits with others or returning to
life as we once knew it. By building and
sharing this database, maintained with
daily updates, the scholars have provided
a valuable tool for others to adapt for
their own research and policy aims.