Context

After observing many naive conversations about COVID-19, claiming that the pandemic can be blamed on just a few factors, I decided to create a data set, to map a number of different data points to every U.S. state (including D.C. and Puerto Rico).

Content

This data set contains basic COVID-19 information about each state, such as total population, total COVID-19 cases, cases per capita, COVID-19 deaths and death rate, Mask mandate start, and end dates, mask mandate duration (in days), and vaccination rates.

However, when evaluating a pandemic (specifically a respiratory virus) it would be wise to also explore the population density of each state, which is also included. For those interested, I also included political party affiliation for each state ("D" for Democrat, "R" for Republican, and "I" for Puerto Rico). Vaccination rates are split into 1-dose and 2-dose rates.

Also included is data ranking the Well-Being Index and Social Determinantes of Health Index for each state (2019). There are also several other columns that "rank" states, such as ranking total cases per state (ascending), total cases per capita per state (ascending), population density rank (ascending), and 2-dose vaccine rate rank (ascending). There are also columns that compare deviation between columns: case count rank vs population density rank (negative numbers indicate that a state has more COVID-19 cases, despite being lower in population density, while positive numbers indicate the opposite), as well as per-capita case count vs density.

Acknowledgements

Several Statista Sources: * COVID-19 Cases in the US * Population Density of US States * COVID-19 Cases in the US per-capita * COVID-19 Vaccination Rates by State

Other sources I'd like to acknowledge: * Ballotpedia * DC Policy Center * Sharecare Well-Being Index * USA Facts * World Population Overview

Inspiration

I would like to see if any new insights could be made about this pandemic, where states failed, or if these case numbers are 100% expected for each state.

As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

The COVID-19 pandemic has upended every aspect of American life. State governments responded quickly to protect public health and stabilize overwhelmed hospital systems. The most restrictive policy, the stay-at-home order, was seen by public health officials as a cornerstone of successful state mitigation strategies. But like many aspects of contemporary politics, support for these efforts took on a distinctly partisan hue. In this paper, I argue that party politics significantly affected state policy responses to COVID-19, which in turn limited mitigation efforts. To this point, I first demonstrate that Democratic governors were faster and more likely to adopt stay-at-home orders than Republicans. Next, using a synthetic control approach, I show that these orders caused residents to practice greater social distancing. Finally, I find that greater social distancing worked to "flattened the curve" by limiting the growth of COVID-19 cases. Together these findings show how party politics affected state pandemic responses and have important long-term implications as states begin lifting restrictions.

Timeline of COVID-19 policies and mandates that affect finances.

The data were collected in the research project "Political cohesion under conditions of fiscal scarcity - German federalism in the time of COVID-19" (funded by VolkswagenStiftung). The data collection consists of two datasets. The first dataset, labeled as "CovDebate", encompasses a total of 3,117 parliamentary proceedings related to Covid-19 that were debated in the German Bundestag and the 16 state parliaments between 1 February 2020 and 26 September 2021. The dataset includes the titles of the proceedings and contextual variables that facilitate a detailed analysis. The second dataset, labeled as "CovFed", comprises 4,610 manually coded statements of political parties that were identified in a qualitative content analysis of 212 key parliamentary debates in the same investigation period. The statements reflect different discursive strategies parties employ in the federal arena. The dataset covers all parties represented in the Bundestag as well as the "Freie Wähler"; all parliaments at both levels of government (Bundestag and 16 state parliaments); and three Covid-19-waves. It contains the statements as well as contextual variables, enabling a detailed analysis of the data. The new dataset is a novel and unique contribution to federalism scholarship because it provides insights into political behavior in the federal arena. It also contains analytical categories which are relevant beyond the German case and in political contexts other than Covid-19.

IntroductionDuring the first wave of the COVID-19 pandemic in Europe, from March 1 to April 15, 2020, significant variations emerged among countries regarding the implementation of lockdown policies. During this period, viewed strictly from an epidemiological perspective, lockdown measures are considered the most effective means of containing a pandemic. However, the adoption of such measures varied, raising questions about whether the reluctance or failure of countries to implement lockdown policies reflected a disregard for epidemiological knowledge or stemmed from an inability to enforce these measures.MethodsThis article employs Qualitative Comparative Analysis (QCA) with 26 European countries as case studies to investigate under what combination of conditions a country would implement lockdown policies.ResultsThe QCA results identify three distinct combinations of conditions that lead countries to implement lockdown measures. First, countries with relatively concentrated political power are more likely to implement lockdown policies. Among the 10 countries governed by a majority party or majority coalition within a two-party or moderate multi-party system, seven implemented lockdown policies. Second, in cases of relatively dispersed political power, countries facing state fragility risks are more likely to implement lockdown policies. Among the eight countries that meet both conditions, five implemented lockdown policies. Finally, factors such as political heritage, severity of the pandemic, demographic composition, healthcare access, quality standards, and the ruling party’s ideology play a lesser role in the decision to enact lockdown measures.DiscussionThis article offers a novel perspective on the dynamics of party politics and state capacity in the context of decision-making during the COVID-19 pandemic. It contributes to a deeper understanding of the intricate relationship between political systems and public health crisis management, highlighting how various political and governance factors influence the adoption of public health interventions during crises.

While Twitter has grown popular among political leaders as a means of computer-mediated mass media communication alternative, the COVID-19 pandemic required new strategies for socio-political communication to handle such a crisis. Using the case of India, which was one of the worst-hit countries and is also the world’s largest democracy, this research explicates how political leaders responded to the COVID-19 crisis on Twitter during the first wave as it was the first time such a crisis occurred. Theoretical frameworks of discursive leadership and situational crisis communication theory have been used to analyze interactions based on the usage patterns, the content of communication, the extent of usage in relation to the severity of the crisis, and the possible role of leaders’ position along with the status of their political party. The sample consisted of tweets posted by six prominent political leaders in India across the four consecutive lockdown periods from 25th March to 31st May 2020. A total of 4,158 tweets were scrapped and after filtering for retweets, the final dataset consisted of 2,809 original tweets. Exploratory data analysis, sentiment analysis, and content analysis were conducted. It was found that the tweets had an overall positive sentiment, an important crisis management strategy. Four main themes emerged: crisis management information, strengthening followers’ resilience and trust, reputation management, and leaders’ proactiveness. By focusing on such discursive aspects of crisis management, the study comprehensively highlights how political interactions on twitter integrated with politics and governance to handle COVID-19 in India. The study has implications for the fields of digital media interaction, political communication, public relations, and crisis leadership.

The purpose of this study was to explore whether the institutional presence of public health expertise within colleges and universities was associated with operational plans for the fall semester of 2020. Using cross-sectional data collected by the College Crisis Initiative of Davidson College, six levels of instructional modalities (ranked from least to most restrictive) were compared between Council on Education of Public Health (CEPH)-accredited and non-CEPH-accredited 4-year institutions. Institutions with CEPH-accredited schools and programs were more likely to select some restrictive teaching modalities: 63.8% more likely to use hybrid/hyflex or more restrictive and 66.9% more likely to be primarily online (with some in person) or more restrictive. However, having CEPH-accredited programs did not push institutions to the most restrictive modalities. COVID-19 cases in county, enrollment, and political affiliation of the state governor were also found to be associated with instructional modality selection. While any ecological study has certain limitations, this study suggests that college and university fall plans may have been influenced by the presence of CEPH-accredited schools and programs of public health, and/or the input of their faculty. The influence of relevant faculty expertise on institutional decision-making can help inform college and university responses to future crises.

As of 2022, the BioNTech vaccine against the coronavirus (COVID-19) was administered the most in Germany. Figures were significantly higher for BioNTech vaccinations, compared to the other vaccines approved for use in the EU – Moderna, AstraZeneca and Janssen. BioNTech is a German biotechnological company, which developed a vaccine against COVID-19 in cooperation with U.S. pharmaceutical giant Pfizer.

New vaccines BioNTech and Moderna are mRNA vaccines, AstraZeneca is not, but all three have one thing in common – they have to be administered in two doses over a period of several weeks to provide protection against the virus. The Janssen vaccine, also referred to as Johnson & Johnson, referring to its manufacturer, requires one dose. Both BioNTech and Moderna vaccines have already been administered as booster shots while another coronavirus wave engulfs Germany. After initial shortages in deliveries at the beginning of Germany’s vaccination campaign at the end of December 2020, production has ramped up, also within the country, and the German government repeatedly assures the population that there are enough vaccines for first, second and booster shots.

The next wave Thus far there is no national vaccination mandate in Germany, though heated debate among political parties regarding the issue continues, particularly in the wake of rising coronavirus cases in the winter of 2021 and the emergence of the Omicron variant. While all the currently greenlighted vaccines against COVID-19 are not said to make the recipient immune to the virus, they are widely hailed as helping reduce the risk of a difficult illness or the possibility of a hospital stay.

How does political ideology affect the processing of information incongruent with one’s worldview? The disagreement in prior research about this question lies in how one’s ideology interacts with cognitive ability to shape motivated numeracy, or the tendency to misinterpret data to confirm one’s prior beliefs. Our study conceptually replicates and extends Kahan et al. (2017) by testing whether monetary incentives for accuracy lessen motivated reasoning when high- and low-numeracy partisans interpret data about mask mandates and COVID-19 cases. This research leverages the ongoing COVID-19 crisis, as Americans are polarized along party lines regarding an appropriate government response to the pandemic.

Replication Data for: The Rule of Discourse: How Ideas and Discourses Shape China’s Zero-COVID Policy. Abstract: How can a controversial policy be effectively implemented and sustained over an extended period? We study this research question from the perspective of discursive institutionalism, using China’s zero-COVID policy as a case. We develop a typology that depicts China’s discursive engineering project featuring a multifaceted and adaptable nature. By analyzing Weibo posts published by Chinese state-led media accounts, we identify four types of political discourse that have prevailed: ideological, imperative, directive, and communicative discourse. The analysis from topic modeling and error correction models highlights the roles of both imperative and directive discourse in China’s COVID-19 policy, while the imperative discourse strengthened the control policy consistently across regions. This paper also sheds light on the mechanism by which the political discourse signals of the party-state reach mid-level bureaucrats, especially in the context of a public health crisis where the rule of law is further weakened.

Although the hazards posed by greenhouse warming and COVID-19 are quite different, diagnosis and mitigation prospects for both depend heavily on science. Unfortunately, the reality of both threats has been subject to politicized science rejection in the US, making these deadly problems less tractable. There are substantial parallels between the two cases of science rejection, including common rhetoric and conservative political leadership. Survey research has reached widely-replicated conclusions regarding the social bases of climate-change perceptions. Corresponding studies of COVID-19 perceptions have found some political commonalities, but less agreement on other details. Here, we address this gap using generalized structural equation modeling (GSEM) and 2021 US survey data to make direct comparisons between the social bases of rejecting the reality of anthropogenic climate change (ACC) and rejecting COVID-19 vaccination. Trumpism, operationalized from approval of ex-president Trump, is viewed as an intervening variable that influences both types of science rejection. Trumpism itself is predicted by age, race, evangelical religion, ideology, and receptivity to seemingly non-political conspiracy beliefs. Considering direct as well as indirect effects (through Trumpism), climate change and vaccine rejection are similarly predicted by white and evangelical identity, conspiracism, and by education×ideology and friends×party interactions. The finding that Trumpism exacerbates science rejection could also apply to other science- and expertise-related topics unrelated to climate and COVID. These results invite broader comparisons across topics, with analogous movements in other countries, and continued tracking as US Trumpism evolves beyond Trump.

Politicians are skilled language users who deploy words strategically and pay close attention to the emotions that those words evoke. We examined the emotional characteristics of over 92 million words spoken by Canadian Members of Parliament between 2006 and 2021. The analysis brought together the Warriner, Kuperman, and Brysbaert (Behav. Res., 2013, 45, 1191–1207) database of valence (positivity) ratings for English and the Canadian Hansard, which contains a transcription of parliamentary speech. Results revealed that the positivity of words used by politicians in parliament was significantly related to both political and social variables. Politicians increased the positivity of their language after the onset of the COVID-19 crisis. Within the time of the crisis, word positivity was linked statistically to month-by-month case counts, indicating a very fine-grained sensitivity to social realities. Our analysis also revealed a fine-grained sensitivity of word valence to political realities. As expected, parties in power used more positive language than those in opposition. In addition, our analysis revealed that individual parties have characteristic levels of word positivity and that those levels change in accordance with political changes as specific as whether or not the party in power holds a majority of seats in parliament. These findings suggest that the emotional properties of words used by Members of Parliament are reliably indexed to sociopolitical dynamics. The findings also suggest that the methodology of linking individual word ratings to Hansard Documents (which are used to document Parliamentary activities in over 25 countries) can provide a key tool for the understanding of specific crises such as the COVID-19 global pandemic as well as more general social and political trends across countries and languages.

Brazil was one of the countries most impacted by the COVID-19 pandemic in Latin America and the world considering the number of cases, deaths, and the duration of lockdowns. Between 2020 and 2022, both pharmacological and non-pharmacological interventions (NPIs) were adopted at the municipal level, with 5,568 municipalities and the Federal District taking health-related actions. We present a new dataset revealing the complexity of this situation by reporting data based on thirty-seven surveys taken by mayors between 23 March 2021 and 24 March 2022. The number of participating municipalities in each survey varied over time. The database indicates in which rounds each municipality participated. The minimum number of participating municipalities was 1,328 (23.8%), while the maximum reached 3,591 (64.49%), showing significant variation. The median was 2,461 (44.19%), and the mean of 2,482 (44.57%) suggests that, in general, municipal participation was close to the median, suggesting the data are representative. Finally, the first quartile was 2,063, and the third quartile was 2,831. The table titled “participation” presents the participation percentages for each of the rounds. This dataset deals with the need to monitor and share information about fragmented policies designed to tackle health crises like the COVID-19 pandemic. Quantifying these initiatives and how they varied across municipalities can help us to understand the effectiveness of interventions in reducing virus transmission. We offer information over time on a series of measures to encourage social distancing, implement the vaccination programme, provide infrastructure to treat infected people, and facilitate how local governments would eventually ease these measures. This information can contribute to the institutional learning of health systems worldwide, assisting in future situations where a highly contagious virus challenges society. Methods Information on local NPI policies related to COVID-19 was collected through a telephone survey conducted directly with mayors, who had the option of receiving a password-protected link to respond to the online questionnaire later or to update previous responses. We focused on information concerning three essential dimensions related to the pandemic response: the monitoring of restrictive measures, infrastructure to treat infected people, and the implementation of the vaccination programme. We have included the week that respondents received the questionnaire, the initial date the questionnaire was presented to respondents, and the final date of questionnaire submission. We collaborated with the Brazilian Confederation of Municipalities (CNM) to collect these data. The cooperation was formalised in a meeting with the CNM on 9 April 2020, and a written agreement was signed by the first and last authors of this article. The authors were given permission to describe, publish, and analyse the dataset. Prior to this current dataset with information from 2021 and 2022, the first and last authors of this dataset had already shared an initial dataset with lockdown measures in Brazil that refer to a survey conducted on October 19 2020, https://doi.org/10.5061/dryad.vdncjsxs2. Similar to our previous dataset that refers to a single survey in the initial days of COVID-19 pandemic, the data we now share on 37 surveys, are freely available to the public and to other academics for analysis. As Brazil’s largest association of municipalities, the CNM has the email and phone numbers of all elected mayors in the country; the wide reach of the association makes it an ideal partner for large-scale data collection. The partnership was established to study the impact of decentralised measures in Brazil and the effects of decentralisation on the spread of infectious diseases. After the establishment of the cooperation agreement, the CNM added other questions to the questionnaire that were of interest to its municipal monitoring, such as questions related to the possible impact of the pandemic on municipal budgets. Thirty-seven rounds of questionnaires were conducted, totalling 239 questions. Our database has 15 columns related to municipal identification, 4 on waiting for a bed, 6 on stock and yield of vaccines, 5 on intubation sets, 6 on restrictive measures, 3 on oxygen stocks in hospitals, COVID-19 centres, and other facilities, 4 on the stock of vaccines, 1 on financial resources, 3 on the situation in the UPAs, 3 on the social consequences of the pandemic, 2 on the care of people with health consequences resulting from COVID-19 infection, and 198 on vaccination. Usage notes As not all municipal authorities answered all the questions, we suggest that users of this dataset consider additional sources of information to document the implementation of missing policies, preferably using official sources of information such as local decrees. However, as decrees are not always available online, secondary sources, such as media reports, may need to be consulted. We invite researchers to use these data to deepen their understanding of the pandemic and support health policymakers’ efforts in other health emergencies. Additionally, by combining our database with other government sources, such as those from the Superior Electoral Court, we offer tools to investigate effects of politics on public health policies during the pandemic and thus generate institutional learning for health systems, empirically demonstrating how political decisions influence public health policies. For example, we can analyse how the alignment of a particular mayor with the former president, elected in 2018, their party affiliation, and other such factors affected political decisions relating to pandemic response measures.

Although the hazards posed by greenhouse warming and COVID-19 are quite different, diagnosis and mitigation prospects for both depend heavily on science. Unfortunately, the reality of both threats has been subject to politicized science rejection in the US, making these deadly problems less tractable. There are substantial parallels between the two cases of science rejection, including common rhetoric and conservative political leadership. Survey research has reached widely-replicated conclusions regarding the social bases of climate-change perceptions. Corresponding studies of COVID-19 perceptions have found some political commonalities, but less agreement on other details. Here, we address this gap using generalized structural equation modeling (GSEM) and 2021 US survey data to make direct comparisons between the social bases of rejecting the reality of anthropogenic climate change (ACC) and rejecting COVID-19 vaccination. Trumpism, operationalized from approval of ex-president Trump, is viewed as an intervening variable that influences both types of science rejection. Trumpism itself is predicted by age, race, evangelical religion, ideology, and receptivity to seemingly non-political conspiracy beliefs. Considering direct as well as indirect effects (through Trumpism), climate change and vaccine rejection are similarly predicted by white and evangelical identity, conspiracism, and by education×ideology and friends×party interactions. The finding that Trumpism exacerbates science rejection could also apply to other science- and expertise-related topics unrelated to climate and COVID. These results invite broader comparisons across topics, with analogous movements in other countries, and continued tracking as US Trumpism evolves beyond Trump.

BackgroundKerala, a south Indian state, has a long and strong history of mobilisation of people’s participation with institutionalised mechanisms as part of decentralisation reforms introduced three decades ago. This history formed the backdrop of the state’s COVID-19 response from 2020 onwards. As part of a larger health equity study, we carried out an analysis to understand the contributions of people’s participation to the state’s COVID-19 response, and what implications this may have for health reform as well as governance more broadly.MethodsWe employed in-depth interviews with participants from four districts of Kerala between July and October, 2021. Following written informed consent procedures, we carried out interviews of health staff from eight primary health care centres, elected Local Self Government (LSG, or Panchayat) representatives, and community leaders. Questions explored primary health care reforms, COVID responses, and populations left behind. Transliterated English transcripts were analysed by four research team members using a thematic analysis approach and ATLAS.ti 9 software. For this paper, we specifically analysed codes and themes related to experiences of community actors and processes for COVID mitigation activities.ResultsA key feature of the COVID-19 response was the formation of Rapid Response Teams (RRTs), groups of lay community volunteers, who were identified and convened by LSG leaders. In some cases, pre-pandemic ‘Arogya sena’ (health army) community volunteer groups were merged with RRTs. RRT members were trained and supported by the health departments at the local level to distribute medicine and essential items, provided support for transportation to health facilities, and assisted with funerary rites during lockdown and containment period. RRTs often comprised youth cadres of ruling and opposition political parties. Existing community networks like Kudumbashree (Self Help Groups) and field workers from other departments have supported and been supported by RRTs. As pandemic restrictions eased, however, there was concern about the sustainability of this arrangement as well.ConclusionParticipatory local governance in Kerala allowed for the creation of invited spaces for community participation in a variety of roles as part of the COVID 19 response, with manifest impact. However, the terms of engagement were not decided by communities, nor were they involved more deeply in planning and organising health policy or services. The sustainability and governance features of such involvement warrant further study.