An Interstate Trips Analysis during COVID-19 in the United States

TL;DR

This study analyzes how COVID-19 affected interstate mobility in the US using mobile phone data, revealing temporal and spatial patterns, correlations with pandemic severity, and implications for predicting imported cases.

Contribution

It provides a detailed analysis of state-to-state mobility changes during COVID-19 using large-scale mobile data, a topic previously underexplored.

Findings

Significant reduction in interstate flow during pandemic peaks

Correlation between mobility reduction and pandemic severity

Variation in flow patterns based on different policies

Abstract

The worldwide outbreak of COVID-19 has posed a dire threat to the public. Human mobility has changed in various ways over the course of the pandemic. Despite current studies on common mobility metrics, research specifically on state-to-state mobility is very limited. By leveraging the mobile phone location data from over 100 million anonymous devices, we estimate the population flow between all states in the United States. We first analyze the temporal pattern and spatial differences of between-state flow from January 1, 2020 to May 15, 2020. Then, with repeated measures ANOVA and post-hoc analysis, we discern different time-course patterns of between-state population flow by pandemic severity groups. A further analysis shows moderate to high correlation between the flow reduction and the pandemic severity, the strength of which varies with different policies. This paper is promising in predicting imported cases.