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We investigate the difference in the spread of COVID-19 between the stateswon by Donald Trump (Red) and the states won by Hillary Clinton (Blue) in the2016 presidential election, by mining transportation patterns of US residentsfrom March 2020 to July 2020. To ensure a fair comparison, we first use aK-means clustering method to group the 50 states into five clusters accordingto their population, area and population density. We then characterize dailytransportation patterns of the residents of different states using the meanpercentage of residents traveling and the number of trips per person. For eachstate, we study the correlations between travel patterns and infection rate fora 2-month period before and after the official states reopening dates. Weobserve that during the lock-down, Red and Blue states both displayed strongpositive correlations between their travel patterns and infection rates.However, after states reopened we find that Red states had highertravel-infection correlations than Blue states in all five state clusters. Wefind that the residents of both Red and Blue states displayed similar travelpatterns during the period post the reopening of states, leading us to concludethat, on average, the residents in Red states might be mobilizing less safelythan the residents in Blue states. Furthermore, we use temperature data toattempt to explain the difference in the way residents travel and practicesafety measures.

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