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New York has become one of the worst-affected COVID-19 hotspots and apandemic epicenter due to the ongoing crisis. This paper identifies the impactof the pandemic and the effectiveness of government policies on human mobilityby analyzing multiple datasets available at both macro and micro levels for theNew York City. Using data sources related to population density, aggregatedpopulation mobility, public rail transit use, vehicle use, hotspot andnon-hotspot movement patterns, and human activity agglomeration, we analyzedthe inter-borough and intra-borough moment for New York City by aggregating thedata at the borough level. We also assessed the internodal population movementamongst hotspot and non-hotspot points of interest for the month of March andApril 2020. Results indicate a drop of about 80% in people's mobility in thecity, beginning in mid-March. The movement to and from Manhattan showed themost disruption for both public transit and road traffic. The city saw itsfirst case on March 1, 2020, but disruptions in mobility can be seen only afterthe second week of March when the shelter in place orders was put in effect.Owing to people working from home and adhering to stay-at-home orders,Manhattan saw the largest disruption to both inter- and intra-borough movement.But the risk of spread of infection in Manhattan turned out to be high becauseof higher hotspot-linked movements. The stay-at-home restrictions also led toan increased population density in Brooklyn and Queens as people were notcommuting to Manhattan. Insights obtained from this study would helppolicymakers better understand human behavior and their response to the newsand governmental policies.

Revealing Critical Characteristics of Mobility Patterns in New York City during the Onset of COVID-19 Pandemic