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Understanding which factors informed pandemic response can help create a morenuanced perspective on how each state of the United States handled the crisis.To this end, we create various networks linking states together based on theirsimilarity in mitigation policies, politics, geographic proximity and COVID-19case data. We use these networks to analyze the correlation between pandemicpolicies and politics, location and case-load from January 2020 through March2022. We show that the best predictors of a state's response is an aggregatepolitical affiliation rather than solely governor affiliation as others haveshown. Further, we illustrate that political affiliation is heavily correlatedwith policy intensity from June 2020 through June 2021, but has little impacton policy after June 2021. In contrast, geographic proximity and dailyincidence are not consistently correlated with state's having similarmitigation policies.

What Motivated Mitigation Policies? A Network-Based Longitudinal Analysis of State-Level Mitigation Strategies