Cell phone mobility data reveals heterogeneity in stay-at-home behavior during the SARS-CoV-2 pandemic

As COVID-19 cases resurge in the United States, understanding the complex interplay between human behavior, disease transmission, and non pharmaceutical interventions during the pandemic could provide valuable insights to focus future public health efforts. Cell-phone mobility data offers a modern measurement instrument to investigate human mobility and behavior at an unprecedented scale. We investigate mobility data collected, aggregated, and anonymized by SafeGraph Inc. which measures how populations at the census block-group geographic scale stayed at home in California, Georgia, Texas, and Washington since the beginning of the pandemic. Using nonlinear dimensionality reduction techniques, we find patterns of mobility behavior that align with stay at-home orders, correlate with socioeconomic factors, cluster geographically, and reveal subpopulations that likely migrated out of urban areas. The analysis and approach provides policy makers a framework for interpreting mobility data and behavior to inform actions aimed at curbing the spread of COVID-19.