Throughout the Covid-19 pandemic digital data on human mobility has played crucial roles in response efforts ranging from monitoring non-pharmaceutical interventions like physical distancing, evaluating different types of testing and seroprevalence strategies, and assisting with targeted re-opening efforts to maximize health and reduce economic harm. But persistent questions remain about the degree to which these datasets accurately reflect the full scope of human mobility, including representativeness across occupation, demographic, and neighborhood divides. Aggregated data from signals collected by personal digital devices may or may not, in different times and places, be relevant to predicting infection rates, and risk mitigation or health-seeking behaviors like testing.
One set of answers to these questions emerges by combining modeling and mobility data with detailed individual travel surveys, which explore dimensions of human mobility, which device-derived data on its own struggle to capture. Dr. Pamela Martinez (University of Illinois) and Dr. Amy Wesolowski (Johns Hopkins University), both of whom actively participated in the Covid-19 Mobility Data Network, deployed travel surveys in Chile and in parts of the United States to extend and deepen what may be knowable about human mobility during the pandemic.
In the panel we explore how travel surveys help to “ground truth” large-scale mobility patterns so that interventions based in part on this type of data are fully mindful of social and behavioral complexity. The work of Drs Martinez and Wesolowski opens up crucial new, comparative perspectives on what mobility data both can, and cannot, tell us about behavioral factors, health policies and effective responses to future health emergencies.
Dr. Pamela Martinez Assistant Professor of Microbiology, School of Molecular & Cellular Biology, University of Illinois
Dr. Amy Wesolowski Assistant Professor, Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health