Food insufficiency and Twitter emotions during a pandemic.

The COVID-19 pandemic initially caused worldwide concerns about food insecurity. Tweets analyzed in real-time may help food assistance providers target food supplies to where they are most urgently needed. In this exploratory study, we use natural language processing to extract sentiments and emotions expressed in food security-related tweets early in the pandemic in U.S. states. The emotion joy dominated in these tweets nationally, but only anger, disgust, and fear were also statistically correlated with contemporaneous food insufficiency rates reported in the Household Pulse Survey; more nuanced and statistically stronger correlations are detected within states, including a negative correlation with joy.

Politics, preparedness, or resources Examining state responsiveness to the COVID-19 pandemic.

U.S. states are often the primary decision makers during a public health crisis. The COVID-19 pandemic led to several different reopening processes across states based on their unique characteristics. We analyze whether states' reopening policy decisions were driven by their public health preparedness, resources, COVID-19 impact, or state politics and political culture. To do so, we summarized state characteristics and compared them across three categories of reopening scores in a bivariate analysis using the chi-square or Fisher exact test for the categorical variables and a one-way analysis of variance (ANOVA) for the continuous variables. A cumulative logit model was used to assess the primary research question. A significant factor in a state's reopening decision was the party of the governor, regardless of the party in control of the legislature, state political culture, public health preparedness, cumulative number of deaths per 100,000, and Opportunity Index score.

Vaccination rates and COVID outcomes across U.S. states.

Rates of COVID deaths, hospitalizations, and cases differ markedly across U.S. states, as do rates of vaccination. This study uses cross-state regressions to assess impacts of vaccinations on COVID outcomes. A number of familiar issues arise concerning cross-sectional regressions, including omitted variables, behavioral responses to vaccination, and reverse causation. The benefits from a field context and from the broad range of observed variations suggest the value from dealing with these issues. Results reveal sizable negative effects of vaccination on deaths, hospitalizations, and cases up to early December 2021, although vaccine efficacy seems to wane over time. The findings for deaths apply to all-cause excess mortality as well as COVID-related mortality. The estimates imply that one expected life saved requires 248 additional doses, with a marginal cost around $55000, far below typical estimates of the value of a statistical life. Results since December 2021 suggest smaller effects of vaccinations on deaths and, especially, hospitalizations and cases, possibly because of diminished effectiveness of vaccines against new forms of the virus, notably the omicron variant. A further possibility is that confidence engendered by vaccinations motivated individuals and governments to lessen non-pharmaceutical interventions, such as masking and social distancing.

Excess Mortality Versus COVID-19 Death Rates: A Spatial Analysis of Socioeconomic Disparities and Political Allegiance Across U.S. States.

Excess mortality is a more robust measure than the counts of COVID-19 deaths typically used in epidemiological and spatial studies. Measurement issues around excess mortality, considering data quality and comparability both internationally and within the U.S., are surveyed. This paper is the first state-level spatial analysis of cumulative excess mortality for the U.S. in the first full year of the pandemic. There is strong evidence that, given appropriate controls, states with higher Democrat vote shares experienced lower excess mortality (consistent with county-level studies of COVID-19 deaths). Important demographic and socio-economic controls from a broad set tested were racial composition, age structure, population density, poverty, income, temperature, and timing of arrival of the pandemic. Interaction effects suggest the Democrat vote share effect of reducing mortality was even greater in states where the pandemic arrived early. Omitting political allegiance leads to a significant underestimation of the mortality disparities for minority populations.

Attention to the COVID-19 Pandemic on Twitter: Partisan Differences Among U.S. State Legislators

Subnational governments in the United States have taken the lead on many aspects of the response to the COVID-19 pandemic. Variation in government activity across states offers the opportunity to analyze responses in comparable settings. We study a common and informative activity among state officials?state legislators? attention to the pandemic on Twitter. We find that legislators? attention to the pandemic strongly correlates with the number of cases in the legislator?s state, the national count of new deaths, and the number of pandemic-related public policies passed within the legislator?s state. Furthermore, we find that the degree of responsiveness to pandemic indicators differs significantly across political parties, with Republicans exhibiting weaker responses, on average. Lastly, we find significant differences in the content of tweets about the pandemic by Democratic and Republican legislators, with Democrats focused on health indicators and impacts, and Republicans focused on business impacts and opening the economy.