Trends in Extreme Distress in the United States, 1993–2019

2020 ◽  
Vol 110 (10) ◽  
pp. 1538-1544
Author(s):  
David G. Blanchflower ◽  
Andrew J. Oswald
Keyword(s):  
Public Health ◽  
Time Trends ◽  
Mental Distress ◽  
State Level ◽  
The United States ◽  
The Us ◽  
Low Education ◽  
Proxy Measure ◽  
Personal Level ◽  
Using Data

Objectives. To investigate changes from 1993 to 2019 in the percentage of US citizens suffering extreme distress. Methods. Using data on 8.1 million randomly sampled US citizens, we created a new proxy measure for exceptional distress (the percentage who reported major mental and emotional problems in all 30 of the last 30 days). We examined time trends for different groups and predictors of distress. Results. The proportion of the US population in extreme distress rose from 3.6% in 1993 to 6.4% in 2019. Among low-education midlife White persons, the percentage more than doubled, from 4.8% to 11.5%. Regression analysis revealed that (1) at the personal level, the strongest statistical predictor of extreme distress was “I am unable to work,” and (2) at the state level, a decline in the share of manufacturing jobs was a predictor of greater distress. Conclusions. Increasing numbers of US citizens report extreme levels of mental distress. This links to poor labor-market prospects. Inequality of distress has also widened. Public Health Implications. Policymakers need to recognize the crisis of an ever-growing group of US citizens in extreme distress.

scholarly journals The Partisan Mask: Political Orientation, Collectivism, and Religiosity Predict Mask Use During COVID-19

2021 ◽  
Author(s):  
Hohjin Im ◽  
Peiyi Wang ◽  
Chuansheng Chen
Keyword(s):  
State Level ◽  
The United States ◽  
Political Orientation ◽  
Third Party ◽  
The Us ◽  
Political Conservatism ◽  
Strong Correlate ◽  
Using Data ◽  
The Individual ◽  
Socioeconomic And Demographic Factors

In the United States, the COVID-19 pandemic became an unconventional vehicle to advance partisan rhetoric and antagonism. Using data available at the individual- (Study 1; N = 4,220), county- (Study 2; n = 3,046), and state-level (n = 49), we found that partisanship and political orientation was a robust and strong correlate of mask use. Political conservatism and Republican partisanship were related to downplaying the severity of COVID-19 and perceiving masks as being ineffective that, in turn, were related to lower mask use. In contrast, we found that counties with majority Democrat partisanship reported greater mask use, controlling for various socioeconomic and demographic factors. Lastly, states with strong cultural collectivism reported greater mask use while those with strong religiosity reported the opposite. States with greater Democrat partisanship and strong cultural collectivism subsequently reported lower COVID-19 deaths, mediated by greater mask use and lower COVID-19 cases, in the five months following the second wave of COVID-19 in the US during the Summer of 2020. Nonetheless, more than the majority for Democrats (91.58%), Republicans (77.52%), and third-party members (82.48%) reported using masks. Implications for findings are discussed.

scholarly journals Community Pharmacists Roles During the COVID-19 Pandemic

2020 ◽  
pp. 089719002098062
Author(s):  
Karl Hess ◽  
Albert Bach ◽  
Kimberly Won ◽  
Sheila M. Seed
Keyword(s):  
Public Health ◽  
Health Services ◽  
Pharmacy Practice ◽  
Community Pharmacists ◽  
State Level ◽  
The United States ◽  
Public Health Care ◽  
Public Health Services ◽  
The Public ◽  
The Us

The aim of this paper is to review the roles that community pharmacists in the United States (US) can play to support public health measures during the current severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic (COVID-19). Community pharmacists in the US are highly visible and accessible to the public and have long been regarded as a source for immunization services as well as other public health activities. In the US, the scope of pharmacy practice continues to expand and incorporate various health services on a state-by-state level. For the purposes of this article, a PubMed literature search was undertaken to identify published articles on SARS-CoV-2, COVID-19, pharmacist- and pharmacy-based immunization and other public health care activities in the US in order to identify and discuss roles that community pharmacists can play during this pandemic including as vaccinators, screeners and testers. In conclusion, community pharmacists are knowledgeable and capable providers of public health services and are easily accessible and well regarded by the public. The incorporation of community pharmacists into this nation’s COVID-19 pandemic response plan can help aid recovery efforts in the US.

scholarly journals Early COVID-19 Interventions Failed to Replicate 1918 St. Louis vs. Philadelphia Outcomes in the United States

2020 ◽  
Author(s):  
Aliea M. Jalali ◽  
Brent M. Peterson ◽  
Thushara Galbadage
Keyword(s):  
Public Health ◽  
United States ◽  
State Level ◽  
The United States ◽  
The State ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Public Health Response ◽  
Health Response ◽  
The Us

The Coronavirus disease 2019 (COVID-19) pandemic has elicited an abrupt pause in the United States in multiple sectors of commerce and social activity. As the US faces this health crisis, the magnitude, and rigor of their initial public health response was unprecedented. As a response, the entire nation shutdown at the state-level for the duration of approximately one to three months. These public health interventions, however, were not arbitrarily decided, but rather, implemented as a result of evidence-based practices. These practices were a result of lessons learned during the 1918 influenza pandemic and the city-level non-pharmaceutical interventions (NPIs) taken across the US. During the 1918 pandemic, two model cities, St. Louis, MO, and Philadelphia, PA, carried out two different approaches to address the spreading disease, which resulted in two distinctly different outcomes. Our group has evaluated the state-level public health response adopted by states across the US, with a focus on New York, California, Florida, and Texas, and compared the effectiveness of reducing the spread of COVID-19. Our assessments show that while the states mentioned above benefited from the implementations of early preventative measures, they inadequately replicated the desired outcomes observed in St. Louis during the 1918 crisis. Our study indicates that there are other factors, including health disparities that may influence the effectiveness of public health interventions applied. Identifying more specific health determinants may help implement targeted interventions aimed at preventing the spread of COVID-19 and improving health equity.

scholarly journals Impacts of social distancing policies on mobility and COVID-19 case growth in the US

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gregory A. Wellenius ◽  
Swapnil Vispute ◽  
Valeria Espinosa ◽  
Alex Fabrikant ◽  
Thomas C. Tsai ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Infection Control ◽  
State Level ◽  
The United States ◽  
Social Consequences ◽  
Social Distancing ◽  
Mobility Data ◽  
The Us ◽  
Public Health Officials

AbstractSocial distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.

scholarly journals Delayed Interventions, Low Compliance, and Health Disparities Amplified the Early Spread of COVID-19

2020 ◽  
Author(s):  
Aliea M. Jalali ◽  
Sumaia G. Khoury ◽  
JongWon See ◽  
Alexis M. Gulsvig ◽  
Brent M. Peterson ◽  
...  
Keyword(s):  
Public Health ◽  
Health Disparities ◽  
State Level ◽  
The United States ◽  
Health Interventions ◽  
Systematic Evaluation ◽  
Public Health Interventions ◽  
Multivariate Statistical ◽  
The Us ◽  
At Home

AbstractThe United States (US) public health interventions were rigorous and rapid, yet failed to arrest the spread of the Coronavirus Disease 2019 (COVID-19) pandemic as infections spread throughout the US. Many factors have contributed to the spread of COVID-19, and the success of public health interventions depends on the level of community adherence to preventative measures. Public health professionals must also understand regional demographic variation in health disparities and determinants to target interventions more effectively. In this study, a systematic evaluation of three significant interventions employed in the US, and their effectiveness in slowing the early spread of COVID-19 was conducted. Next, community-level compliance with a state-level stay at home orders was assessed to determine COVID-19 spread behavior. Finally, health disparities that may have contributed to the disproportionate acceleration of early COVID-19 spread between certain counties were characterized. The contribution of these factors for the disproportionate spread of the disease was analyzed using both univariate and multivariate statistical analyses. Results of this investigation show that delayed implementation of public health interventions, a low level of compliance with the stay at home orders, in conjunction with health disparities, significantly contributed to the early spread of the COVID-19 pandemic.

scholarly journals Economic Geography and Economic Voting: Evidence from the US States

2006 ◽  
Vol 36 (3) ◽  
pp. 527-547 ◽  
Author(s):  
MICHAEL EBEID ◽  
JONATHAN RODDEN
Keyword(s):  
Commodity Prices ◽  
State Level ◽  
Economic Voting ◽  
The United States ◽  
Economic Conditions ◽  
Government Responsibility ◽  
Gubernatorial Elections ◽  
The Us ◽  
Macroeconomic Indicators ◽  
Using Data

If voters use information about the economy to assess the competence of incumbents, a connection between economic conditions and incumbent success should only be discernible in settings where public policy might plausibly affect the economy, and where the assignment of government responsibility is relatively straightforward. Applying this logic to gubernatorial elections in the United States, we test the following hypothesis: the connection between economic conditions and incumbents' vote shares is mediated by the structure of the state economy. This hypothesis is premised on the idea that voters understand that raw macroeconomic aggregates – when driven by factors like weather, commodity prices and federal policy – are poor signals of incumbent performance. Using data from gubernatorial elections held between 1950 and 1998, we show that the connection between macroeconomic indicators and incumbent success is weak in states dominated by natural resources and farming but quite strong elsewhere. This finding helps explain why earlier studies found no connection between state-level economic conditions and gubernatorial elections.

Can increases in Twitter posts predict increases in cumulative incidence of COVID-19 in the United States? Evidence that social media can inform epidemic surveillance. (Preprint)

2020 ◽  
Author(s):  
Ruoyan Sun ◽  
Henna Budhwani
Keyword(s):  
Public Health ◽  
United States ◽  
Cumulative Incidence ◽  
Hot Spots ◽  
Adult Population ◽  
State Level ◽  
The United States ◽  
Education Attainment ◽  
Public Health Systems ◽  
Per Capita

BACKGROUND Though public health systems are responding rapidly to the COVID-19 pandemic, outcomes from publicly available, crowd-sourced big data may assist in helping to identify hot spots, prioritize equipment allocation and staffing, while also informing health policy related to “shelter in place” and social distancing recommendations. OBJECTIVE To assess if the rising state-level prevalence of COVID-19 related posts on Twitter (tweets) is predictive of state-level cumulative COVID-19 incidence after controlling for socio-economic characteristics. METHODS We identified extracted COVID-19 related tweets from January 21st to March 7th (2020) across all 50 states (N = 7,427,057). Tweets were combined with state-level characteristics and confirmed COVID-19 cases to determine the association between public commentary and cumulative incidence. RESULTS The cumulative incidence of COVID-19 cases varied significantly across states. Ratio of tweet increase (p=0.03), number of physicians per 1,000 population (p=0.01), education attainment (p=0.006), income per capita (p = 0.002), and percentage of adult population (p=0.003) were positively associated with cumulative incidence. Ratio of tweet increase was significantly associated with the logarithmic of cumulative incidence (p=0.06) with a coefficient of 0.26. CONCLUSIONS An increase in the prevalence of state-level tweets was predictive of an increase in COVID-19 diagnoses, providing evidence that Twitter can be a valuable surveillance tool for public health.

State Intervention During Public Health Emergencies: Is the United States Prepared for an Ebola Outbreak?

2015 ◽  
Vol 12 (2) ◽  
Author(s):  
Marie-Helen Maras ◽  
Michelle D. Miranda
Keyword(s):  
Public Health ◽  
State Intervention ◽  
The United States ◽  
International Travel ◽  
American Government ◽  
Training And Education ◽  
Public Health Emergencies ◽  
The Us ◽  
Bioterrorism Agent ◽  
Legal Guidelines

AbstractIn the fall of 2014, the US was faced with the reality that a deadly, foreign virus had entered its borders. Ebola, a disease thought to be of little threat to the US yet classified as a major bioterrorism agent, became a reality for the American government and its citizens. The introduction of Ebola unveiled many deficiencies in the country’s health care system, international travel policies, and ability to control or restrict the movement of exposed individuals in order to protect the larger population. The need to review and establish legal guidelines and policies to deal with these deficiencies is paramount: the inherent lack of training and education; weaknesses in monitoring, maintenance, and treatment; and the lack of uniform guidelines to isolate international travelers have all demonstrated that the country may not be able to control a larger-scale threat in the future.

scholarly journals Patterns and correlates of mis-implementation in state chronic disease public health practice in the United States

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Margaret M. Padek ◽  
Stephanie Mazzucca ◽  
Peg Allen ◽  
Emily Rodriguez Weno ◽  
Edward Tsai ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Decision Making ◽  
Chronic Disease ◽  
Multinomial Logistic Regression ◽  
Public Health Practice ◽  
State Level ◽  
The United States ◽  
Organizational Level ◽  
Effective Programs

Abstract Background Much of the disease burden in the United States is preventable through application of existing knowledge. State-level public health practitioners are in ideal positions to affect programs and policies related to chronic disease, but the extent to which mis-implementation occurring with these programs is largely unknown. Mis-implementation refers to ending effective programs and policies prematurely or continuing ineffective ones. Methods A 2018 comprehensive survey assessing the extent of mis-implementation and multi-level influences on mis-implementation was reported by state health departments (SHDs). Questions were developed from previous literature. Surveys were emailed to randomly selected SHD employees across the Unites States. Spearman’s correlation and multinomial logistic regression were used to assess factors in mis-implementation. Results Half (50.7%) of respondents were chronic disease program managers or unit directors. Forty nine percent reported that programs their SHD oversees sometimes, often or always continued ineffective programs. Over 50% also reported that their SHD sometimes or often ended effective programs. The data suggest the strongest correlates and predictors of mis-implementation were at the organizational level. For example, the number of organizational layers impeded decision-making was significant for both continuing ineffective programs (OR=4.70; 95% CI=2.20, 10.04) and ending effective programs (OR=3.23; 95% CI=1.61, 7.40). Conclusion The data suggest that changing certain agency practices may help in minimizing the occurrence of mis-implementation. Further research should focus on adding context to these issues and helping agencies engage in appropriate decision-making. Greater attention to mis-implementation should lead to greater use of effective interventions and more efficient expenditure of resources, ultimately to improve health outcomes.

scholarly journals Associations between Google Search Trends for Symptoms and COVID-19 Confirmed and Death Cases in the United States

2021 ◽  
Vol 18 (9) ◽  
pp. 4560
Author(s):  
Mostafa Abbas ◽  
Thomas B. Morland ◽  
Eric S. Hall ◽  
Yasser EL-Manzalawy
Keyword(s):  
Functional Data ◽  
Time Series Data ◽  
Principal Component ◽  
State Level ◽  
The United States ◽  
Functional Principal Component Analysis ◽  
Series Data ◽  
Dynamic Correlation ◽  
The Us ◽  
Google Search

We utilize functional data analysis techniques to investigate patterns of COVID-19 positivity and mortality in the US and their associations with Google search trends for COVID-19-related symptoms. Specifically, we represent state-level time series data for COVID-19 and Google search trends for symptoms as smoothed functional curves. Given these functional data, we explore the modes of variation in the data using functional principal component analysis (FPCA). We also apply functional clustering analysis to identify patterns of COVID-19 confirmed case and death trajectories across the US. Moreover, we quantify the associations between Google COVID-19 search trends for symptoms and COVID-19 confirmed case and death trajectories using dynamic correlation. Finally, we examine the dynamics of correlations for the top nine Google search trends of symptoms commonly associated with COVID-19 confirmed case and death trajectories. Our results reveal and characterize distinct patterns for COVID-19 spread and mortality across the US. The dynamics of these correlations suggest the feasibility of using Google queries to forecast COVID-19 cases and mortality for up to three weeks in advance. Our results and analysis framework set the stage for the development of predictive models for forecasting COVID-19 confirmed cases and deaths using historical data and Google search trends for nine symptoms associated with both outcomes.

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