1 Introduction

As the coronavirus spread in Philadelphia this year, mobility patterns changed. With this shock came fewer commutes to work; we changed where we shopped, where we dined and how we traveled. In order to understand the consequences of these changes, we use GPS data from mobile phones to track travel patterns before and during the pandemic.

To do so, we collect data from SafeGraph, a provider of mobility data from iPhone and Android smartphones. Note that SafeGraph gathers data on a representative sample (10%) of the population across the country, so our indicators are not the true number of visits or journeys, but a sample. The data model is explained in Figure 1.1. The number of visitors is the count of devices arriving at a point of interest (POI) while a connection is an origin-destination line between a Census Block Group and a point of interest. A flow is also a connection, but with a weight measuring the number of visitors traveling between origin and destination.

1.1 Key definitions

Each visit is a mobile device entering into a point of interest; these include parks and museums, restaurants and bars, or offices and hospitals. In Figure 1.2, the distribution of these venues and businesses are mapped. Each point of interest is classified by its type, which SafeGraph provides. 1 We can see that most businesses cluster in Center City or nearby but no businesses cluster more than leisure—which is restaurants and bars.

1.2 Distribution of points of interest