How Political is the Spread of COVID-19 in the United States? An Analysis using Transportation and Weather Data

TL;DR

This study analyzes how political affiliations influence COVID-19 spread in the US by examining transportation patterns and weather data, revealing higher post-reopening travel-infection correlations in Republican-leaning states.

Contribution

It introduces a comparative analysis of transportation and weather data to understand political differences in COVID-19 spread dynamics across US states.

Findings

Red states show higher travel-infection correlations after reopening.

Both Red and Blue states had similar travel patterns post-reopening.

Temperature data partially explains differences in travel and safety practices.

Abstract

We investigate the difference in the spread of COVID-19 between the states won by Donald Trump (Red) and the states won by Hillary Clinton (Blue) in the 2016 presidential election, by mining transportation patterns of US residents from March 2020 to July 2020. To ensure a fair comparison, we first use a K-means clustering method to group the 50 states into five clusters according to their population, area and population density. We then characterize daily transportation patterns of the residents of different states using the mean percentage of residents traveling and the number of trips per person. For each state, we study the correlations between travel patterns and infection rate for a 2-month period before and after the official states reopening dates. We observe that during the lock-down, Red and Blue states both displayed strong positive correlations between their travel patterns and infection rates. However, after states reopened we find that Red states had higher travel-infection correlations than Blue states in all five state clusters. We find that the residents of both Red and Blue states displayed similar travel patterns during the period post the reopening of states, leading us to conclude that, on average, the residents in Red states might be mobilizing less safely than the residents in Blue states. Furthermore, we use temperature data to attempt to explain the difference in the way residents travel and practice safety measures.