The changing nature of the COVID-19 pandemic has highlighted the importance
of comprehensively considering its impacts and considering changes over time.
Most COVID-19 related research addresses narrowly focused research questions
and is therefore limited in addressing the complexities created by the
interrelated impacts of the pandemic. Such research generally makes use of only
one of either 1) actively collected data such as surveys, or 2) passively
collected data. While a few studies make use of both actively and passively
collected data, only one other study collects it longitudinally. Here we
describe a rich panel dataset of active and passive data from U.S. residents
collected between August 2020 and July 2021. Active data includes a repeated
survey measuring travel behavior, compliance with COVID-19 mandates, physical
health, economic well-being, vaccination status, and other factors. Passively
collected data consists of all locations visited by study participants, taken
from smartphone GPS data. We also closely tracked COVID-19 policies across
counties of residence throughout the study period. Such a dataset allows
important research questions to be answered; for example, to determine the
factors underlying the heterogeneous behavioral responses to COVID-19
restrictions imposed by local governments. Better information about such
responses is critical to our ability to understand the societal and economic
impacts of this and future pandemics. The development of this data
infrastructure can also help researchers explore new frontiers in behavioral
science. The article explains how this approach fills gaps in COVID-19 related
data collection; describes the study design and data collection procedures;
presents key demographic characteristics of study participants; and shows how
fusing different data streams helps uncover behavioral insights