Local TV News Coverage of Racial Disparities in COVID-19 During the First Wave of the Pandemic, March-June 2020

US Nationwide Multi-City Media Coverage of COVID-19 Responses: Community Structure Theory, Belief System, and a "Violated Way of Life"

Community structure analysis compared city characteristics and newspaper coverage of state/local government responses to COVID-19 in 25 major U.S. cities, sampling all 250+ word articles from 4/4/20 to 7/6/20. The resulting 588 articles were coded for "prominence" and "direction" (favorable/unfavorable/balanced-neutral coverage), then combined into each newspaper's composite "Media Vector" (range=0.3552 to -0.5197, or 0.8749). Twenty-one of 25 newspapers (84%) displayed unfavorable coverage of local COVID-19 responses. Pearson correlations and regression analysis confirmed a muscular "violated way of life" pattern, when a community perceives itself as threatened by a "biological threat or a threat to a cherished way of life." Political and belief system polarization (in particular percent Evangelical and percent voting Republican) were strongly associated with unfavorable coverage of local pandemic responses, compared to more favorable responses linked to percent voting Democratic or percent Catholic. Vulnerability (percent uninsured) was also linked to negative coverage. Conversely, two different measures of access to healthcare (percent municipal spending on health and welfare, and physicians/100,000) were significantly linked to favorable coverage of the same local government efforts. Community structure theory's grass roots "bottom up" expectations linking community demographics to variations in reporting on critical issues were robustly confirmed.

Communicating science in the COVID-19 news in the UK during Omicron waves: exploring representations of nature of science with epistemic network analysis

News media plays a vital role in communicating scientific evidence to the public during the COVID-19 pandemic. Such communication is important for convincing the public to follow social distancing guidelines and to respond to health campaigns such as vaccination programmes. However, newspapers were criticised that they focus on the socio-political perspective of science, without explaining the nature of scientific works behind the government's decisions. This paper examines the connections of the nature of science categories in the COVID-19 era by four local newspapers in the United Kingdom between November 2021 to February 2022. Nature of science refers to different aspects of how science works such as aims, values, methods and social institutions of science. Considering the news media may mediate public information and perception of scientific stories, it is relevant to ask how the various British newspapers covered aspects of science during the pandemic. In the period explored, Omicron variant was initially a variant of concern, and an increasing number of scientific evidence showed that the less severity of this variant might move the country from pandemic to endemic. We explored how news articles communicate public health information by addressing how science works during the period when Omicron variants surge. A novel discourse analysis approach, epistemic network analysis is used to characterise the frequency of connections of categories of the nature of science. The connection between political factors and the professional activities of scientists, as well as that with scientific practices are more apparent in left-populated and centralist outlets than in right-populated news outlets. Among four news outlets across the political spectrum, a left-populated newspaper, the Guardian, is not consistent in representing relations of different aspects of the nature of scientific works across different stages of the public health crisis. Inconsistency of addressing aspects of scientific works and a downplay of the cognitive-epistemic nature of scientific works likely lead to failure in trust and consumption of scientific knowledge by the public in the healthcare crisis.

News Media Coverage of Childcare: How U.S. Local TV News Framed the Problem Before and During the Early Stage of the COVID-19 Pandemic

Early care and education (ECE), or the care young children receive before entering formal schooling, can take multiple forms and is delivered in different settings, such as a center, church, or public school. Federal and state governments regularly fund ECE programs and policies through the Child Care and Development Block Grant Act (CCDBG). Many families, however, face significant challenges in access, cost, and quality of ECE programs, and ECE professionals report substantial challenges in the workplace (e.g., inadequate training) and beyond (e.g., low wages). Policies addressing issues related to ECE were proposed in 2021, but stalled on the U.S. federal policy agenda. In this study, we examine the ECE content of local television news coverage both for its representations of and for its potential influences on ECE policy agendas. We use data from local stations affiliated with the major networks (ABC, NBC, CBS, and FOX) in media markets across the U.S., airing before and during the pandemic. We analyze elements of coverage that could affect public recognition of ECE-related issues, including how problems were framed (e.g., news coverage highlighting scandals or adverse events at ECE facilities) and solutions identified (e.g., public policy). We find that during 2018 and 2019, more coverage highlighted scandalous activity than public policy. The reverse was true, however, during the early period of the pandemic (from mid-March through June of 2020). Researchers and health professionals were seldom included in stories in either sample, and very few stories offered context about the benefits of ECE for health and well-being. These coverage patterns have implications for the public's understanding of ECE policy and the perceived need for reform. Policymakers, advocates, and researchers looking to advance support for ECE should consider ways to use local television news to present health and policy-relevant information to broad segments of the public.

Who does COVID-19 hurt most? Perceptions of unequal impact and political implications

While the overall impact of the COVID-19 pandemic on U.S. population health has been devastating, it has not affected everyone equally. The risks of hospitalization and death from the disease are relatively low for the population as a whole, but much higher for specific subpopulations defined by age, health status, and race or ethnicity. The extent to which Americans perceive these disparities is an open question, with potentially important political implications. Recognition of unequal impacts may prime concerns about justice and fairness, making Americans more concerned and willing to support government intervention. On the other hand, belief that the pandemic primarily threatens "other people" or out-groups may reduce, rather than increase, a person's concern. Partisanship and media consumption habits are also likely to play a role in these perceptions, as they do in most issues related to COVID-19. In this paper, we use original survey data from the Cooperative Election Study (N = 1000) to explore Americans' perceptions of which groups are most harmed by the pandemic, the demographic and political determinants of these perceptions, and the relationship of these perceptions with their opinions about COVID-related mitigation policy. We find that, on average, people perceived accurately that certain groups (e.g., Black Americans, older people) were more affected, but these group perceptions varied by demographic and political characteristics of respondents. We find, in contrast with recent experimental evidence, that the perception that populations of color were harmed was associated with more support for pandemic mitigation strategies. More research should investigate the relationships among pandemic politics and the racial dynamics of the target populations most affected.

An SEM-ANN approach to evaluate public awareness about COVID, A pathway toward adaptation effective strategies for sustainable development

This study was conducted to evaluate public awareness about COVID with aimed to check public strategies against COVID-19. A semi structured questionnaire was collected and the data was analyzed using some statistical tools (PLS-SEM) and artificial neural networks (ANN). We started by looking at the known causal linkages between the different variables to see if they matched up with the hypotheses that had been proposed. Next, for this reason, we ran a 5,000-sample bootstrapping test to assess how strongly our findings corroborated the null hypothesis. PLS-SEM direct path analysis revealed HRP -> PA-COVID, HI -> PA-COVID, MU -> PA-COVID, PM -> PA-COVID, SD -> PA-COVID. These findings provide credence to the acceptance of hypotheses H1, H3, and H5, but reject hypothesis H2. We have also examined control factors such as respondents' age, gender, and level of education. Age was found to have a positive correlation with PA-COVID, while mean gender and education level were found to not correlate at all with PA-COVID. However, age can be a useful control variable, as a more seasoned individual is likely to have a better understanding of COVID and its effects on independent variables. Study results revealed a small moderation effect in the relationships between understudy independent and dependent variables. Education significantly moderates the relationship of PA-COVID associated with MU, PH, SD, RP, PM, PA-COVID, depicts the moderation role of education on the relationship between MU^*Education->PA-COVID, HI^*Education->PA.COVID, SD^*Education->PA.COVID, HRP^*Education->PA.COVID, PM^*Education -> PA.COVID. The artificial neural network (ANN) model we've developed for spreading information about COVID-19 (PA-COVID) follows in the footsteps of previous studies. The root means the square of the errors (RMSE). Validity measures how well a model can predict a certain result. With RMSE values of 0.424 for training and 0.394 for testing, we observed that our ANN model for public awareness of COVID-19 (PA-COVID) had a strong predictive ability. Based on the sensitivity analysis results, we determined that PA. COVID had the highest relative normalized relevance for our sample (100%). These factors were then followed by MU (54.6%), HI (11.1%), SD (100.0%), HRP (28.5%), and PM (64.6%) were likewise shown to be the least important factors for consumers in developing countries struggling with diseases caused by contaminated water. In addition, a specific approach was used to construct a goodness-of-fit coefficient to evaluate the performance of the ANN models. The study will aid in the implementation of effective monitoring and public policies to promote the health of local people.