The COVID-19 pandemic has attuned citizens toward their local governments in the midst of local outbreaks and city-wide public health orders. However, little research has been done to understand the intersection of local government and COVID-19 from the perspectives of the citizens. This study utilizes Natural Language Processing tools (topic analysis, point mutual information analysis, and sentiment analysis) to understand local discourse on COVID-19 and local government in New York City, Los Angeles, Detroit, and San Diego. New York City emerged as the city discussing COVID-19 in relation to their local government the most followed by San Diego, Los Angeles, then Detroit. Topic Analysis indicated variant reactions toward the pandemic with New York City and Detroit topics having more urgency and specificity (i.e., the Rikers Island outbreak and the Detroit Police Department outbreak) while Los Angeles and San Diego showing more general themes (i.e., testing, face masks, symptoms) in preparation for the virus. Three of the four cities showed a majority of negative leaning sentiments in the local government tweets, with Detroit being the only city with higher rates of positive tweets than negative. Results of this study can be used to inform local governments, researchers, and community members of the themes and sentiments within COVID-19 at the local level.