scholarly journals Obligation or Desire: Variation in Motivation for Compliance With COVID-19 Public Health Guidance

2021 ◽  
Vol 12 ◽  
Author(s):  
Ting Ai ◽  
Glenn Adams ◽  
Xian Zhao
Keyword(s):  
Public Health ◽  
United States ◽  
The United States ◽  
Psychological Experience ◽  
Social Distancing ◽  
Prosocial Motivation ◽  
Self Study ◽  
Practical Implications ◽  
Health Guidance

Why do people comply with coronavirus disease 2019 (COVID-19) public health guidance? This study considers cultural-psychological foundations of variation in beliefs about motivations for such compliance. Specifically, we focused on beliefs about two sources of prosocial motivation: desire to protect others and obligation to society. Across two studies, we observed that the relative emphasis on the desire to protect others (vs. the obligation to the community) as an explanation for compliance was greater in the United States settings associated with cultural ecologies of abstracted independence than in Chinese settings associated with cultural ecologies of embedded interdependence. We observed these patterns for explanations of psychological experience of both others (Study 1) and self (Study 2), and for compliance with mandates for both social distancing and face masks (Study 2). Discussion of results considers both practical implications for motivating compliance with public health guidance and theoretical implications for denaturalizing prevailing accounts of prosocial motivation.

scholarly journals Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing

2021 ◽  
Author(s):  
Ibtihal Ferwana ◽  
Lav R. Varshney
Keyword(s):  
Public Health ◽  
United States ◽  
Social Capital ◽  
Community Health ◽  
Collective Efficacy ◽  
Residential Mobility ◽  
The United States ◽  
Social Distancing ◽  
The Social ◽  
Family Unity

Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior, vaccination, face masking, and physical distancing during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.

scholarly journals Social capital dimensions are differentially associated with COVID-19 vaccinations, masks, and physical distancing

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260818
Author(s):  
Ibtihal Ferwana ◽  
Lav R. Varshney
Keyword(s):  
Public Health ◽  
United States ◽  
Social Capital ◽  
Community Health ◽  
Collective Efficacy ◽  
Residential Mobility ◽  
The United States ◽  
Social Distancing ◽  
The Social ◽  
Family Unity

Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior—vaccination, face masking, and physical distancing—during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.

scholarly journals Public Health Interventions’ Effect on Hospital Use in Patients With COVID-19: Comparative Study (Preprint)

2020 ◽  
Author(s):  
Xiaofeng Wang ◽  
Rui Ren ◽  
Michael W Kattan ◽  
Lara Jehi ◽  
Zhenshun Cheng ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
New York ◽  
New York State ◽  
The United States ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Social Distancing ◽  
Transmission Rates ◽  
Hospital Use

BACKGROUND Different states in the United States had different nonpharmaceutical public health interventions during the COVID-19 pandemic. The effects of those interventions on hospital use have not been systematically evaluated. The investigation could provide data-driven evidence to potentially improve the implementation of public health interventions in the future. OBJECTIVE We aim to study two representative areas in the United States and one area in China (New York State, Ohio State, and Hubei Province), and investigate the effects of their public health interventions by time periods according to key interventions. METHODS This observational study evaluated the numbers of infected, hospitalized, and death cases in New York and Ohio from March 16 through September 14, 2020, and Hubei from January 26 to March 31, 2020. We developed novel Bayesian generalized compartmental models. The clinical stages of COVID-19 were stratified in the models, and the effects of public health interventions were modeled through piecewise exponential functions. Time-dependent transmission rates and effective reproduction numbers were estimated. The associations of interventions and the numbers of required hospital and intensive care unit beds were studied. RESULTS The interventions of social distancing, home confinement, and wearing masks significantly decreased (in a Bayesian sense) the case incidence and reduced the demand for beds in all areas. Ohio’s transmission rates declined before the state’s “stay at home” order, which provided evidence that early intervention is important. Wearing masks was significantly associated with reducing the transmission rates after reopening, when comparing New York and Ohio. The centralized quarantine intervention in Hubei played a significant role in further preventing and controlling the disease in that area. The estimated rates that cured patients become susceptible in all areas were small (<0.0001), which indicates that they have little chance to get the infection again. CONCLUSIONS The series of public health interventions in three areas were temporally associated with the burden of COVID-19–attributed hospital use. Social distancing and the use of face masks should continue to prevent the next peak of the pandemic.

scholarly journals The role of race and scientific trust on support for COVID-19 social distancing measures in the United States

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254127
Author(s):  
Sara Kazemian ◽  
Sam Fuller ◽  
Carlos Algara
Keyword(s):  
Public Health ◽  
United States ◽  
The United States ◽  
Institutional Trust ◽  
The Novel ◽  
Social Distancing ◽  
The Media ◽  
Racial Lines ◽  
Novel Coronavirus

Pundits and academics across disciplines note that the human toll brought forth by the novel coronavirus (COVID-19) pandemic in the United States (U.S.) is fundamentally unequal for communities of color. Standing literature on public health posits that one of the chief predictors of racial disparity in health outcomes is a lack of institutional trust among minority communities. Furthermore, in our own county-level analysis from the U.S., we find that counties with higher percentages of Black and Hispanic residents have had vastly higher cumulative deaths from COVID-19. In light of this standing literature and our own analysis, it is critical to better understand how to mitigate or prevent these unequal outcomes for any future pandemic or public health emergency. Therefore, we assess the claim that raising institutional trust, primarily scientific trust, is key to mitigating these racial inequities. Leveraging a new, pre-pandemic measure of scientific trust, we find that trust in science, unlike trust in politicians or the media, significantly raises support for COVID-19 social distancing policies across racial lines. Our findings suggest that increasing scientific trust is essential to garnering support for public health policies that lessen the severity of the current, and potentially a future, pandemic.

scholarly journals COVID-19 Deaths in the United States: Shifts in Hot Spots over the Three Phases of the Pandemic and the Spatiotemporally Varying Impact of Pandemic Vulnerability

2021 ◽  
Vol 18 (17) ◽  
pp. 8987
Author(s):  
Yoo Min Park ◽  
Gregory D. Kearney ◽  
Bennett Wall ◽  
Katherine Jones ◽  
Robert J. Howard ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
Hot Spots ◽  
Hot Spot ◽  
Health Planning ◽  
The United States ◽  
Death Rates ◽  
Social Distancing ◽  
Spatiotemporal Trends ◽  
Three Phases

The geographic areas most impacted by COVID-19 may not remain static because public health measures/behaviors change dynamically, and the impacts of pandemic vulnerability also may vary geographically and temporally. The nature of the pandemic makes spatiotemporal methods essential to understanding the distribution of COVID-19 deaths and developing interventions. This study examines the spatiotemporal trends in COVID-19 death rates in the United States from March 2020 to May 2021 by performing an emerging hot spot analysis (EHSA). It then investigates the effects of the COVID-19 time-dependent and basic social vulnerability factors on COVID-19 death rates using geographically and temporally weighted regression (GTWR). The EHSA results demonstrate that over the three phases of the pandemic (first wave, second wave, and post-vaccine deployment), hot spots have shifted from densely populated cities and the states with a high percentage of socially vulnerable individuals to the states with relatively relaxed social distancing requirements, and then to the states with low vaccination rates. The GTWR results suggest that local infection and testing rates, social distancing interventions, and other social, environmental, and health risk factors show significant associations with COVID-19 death rates, but these associations vary over time and space. These findings can inform public health planning.

scholarly journals Working memory capacity predicts individual differences in social-distancing compliance during the COVID-19 pandemic in the United States

2020 ◽  
Vol 117 (30) ◽  
pp. 17667-17674 ◽  
Author(s):  
Weizhen Xie ◽  
Stephen Campbell ◽  
Weiwei Zhang
Keyword(s):  
Public Health ◽  
United States ◽  
Working Memory ◽  
Individual Differences ◽  
Early Stage ◽  
Critical Role ◽  
The United States ◽  
Unique Contribution ◽  
Health Crisis ◽  
Social Distancing

Noncompliance with social distancing during the early stage of the coronavirus disease 2019 (COVID-19) pandemic poses a great challenge to the public health system. These noncompliance behaviors partly reflect people’s concerns for the inherent costs of social distancing while discounting its public health benefits. We propose that this oversight may be associated with the limitation in one’s mental capacity to simultaneously retain multiple pieces of information in working memory (WM) for rational decision making that leads to social-distancing compliance. We tested this hypothesis in 850 United States residents during the first 2 wk following the presidential declaration of national emergency because of the COVID-19 pandemic. We found that participants’ social-distancing compliance at this initial stage could be predicted by individual differences in WM capacity, partly due to increased awareness of benefits over costs of social distancing among higher WM capacity individuals. Critically, the unique contribution of WM capacity to the individual differences in social-distancing compliance could not be explained by other psychological and socioeconomic factors (e.g., moods, personality, education, and income levels). Furthermore, the critical role of WM capacity in social-distancing compliance can be generalized to the compliance with another set of rules for social interactions, namely the fairness norm, in Western cultures. Collectively, our data reveal contributions of a core cognitive process underlying social-distancing compliance during the early stage of the COVID-19 pandemic, highlighting a potential cognitive venue for developing strategies to mitigate a public health crisis.

scholarly journals Public Health Interventions’ Effect on Hospital Use in Patients With COVID-19: Comparative Study

10.2196/25174 ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. e25174
Author(s):  
Xiaofeng Wang ◽  
Rui Ren ◽  
Michael W Kattan ◽  
Lara Jehi ◽  
Zhenshun Cheng ◽  
...  
Keyword(s):  
Public Health ◽  
United States ◽  
New York ◽  
New York State ◽  
The United States ◽  
Health Interventions ◽  
Public Health Interventions ◽  
Social Distancing ◽  
Transmission Rates ◽  
Hospital Use

Background Different states in the United States had different nonpharmaceutical public health interventions during the COVID-19 pandemic. The effects of those interventions on hospital use have not been systematically evaluated. The investigation could provide data-driven evidence to potentially improve the implementation of public health interventions in the future. Objective We aim to study two representative areas in the United States and one area in China (New York State, Ohio State, and Hubei Province), and investigate the effects of their public health interventions by time periods according to key interventions. Methods This observational study evaluated the numbers of infected, hospitalized, and death cases in New York and Ohio from March 16 through September 14, 2020, and Hubei from January 26 to March 31, 2020. We developed novel Bayesian generalized compartmental models. The clinical stages of COVID-19 were stratified in the models, and the effects of public health interventions were modeled through piecewise exponential functions. Time-dependent transmission rates and effective reproduction numbers were estimated. The associations of interventions and the numbers of required hospital and intensive care unit beds were studied. Results The interventions of social distancing, home confinement, and wearing masks significantly decreased (in a Bayesian sense) the case incidence and reduced the demand for beds in all areas. Ohio’s transmission rates declined before the state’s “stay at home” order, which provided evidence that early intervention is important. Wearing masks was significantly associated with reducing the transmission rates after reopening, when comparing New York and Ohio. The centralized quarantine intervention in Hubei played a significant role in further preventing and controlling the disease in that area. The estimated rates that cured patients become susceptible in all areas were small (<0.0001), which indicates that they have little chance to get the infection again. Conclusions The series of public health interventions in three areas were temporally associated with the burden of COVID-19–attributed hospital use. Social distancing and the use of face masks should continue to prevent the next peak of the pandemic.

scholarly journals A Decision Analytic Approach for Social Distancing Policies During COVID-19 Pandemic

2020 ◽  
Author(s):  
Zeynep Ertem ◽  
Ozgur M. Araz ◽  
Mayteé Cruz-Aponte
Keyword(s):  
Public Health ◽  
United States ◽  
Population Density ◽  
The United States ◽  
Disease Spread ◽  
Public Health Issue ◽  
Mobility Patterns ◽  
Empirical Estimation ◽  
Social Distancing ◽  
The Right

AbstractThe COVID-19 pandemic has become a crucial public health issue in many countries including the United States. In the absence of the right vaccine strain and sufficient antiviral stockpiles on hand, non-pharmaceutical interventions have become valuable public health tools at the early stages of the pandemic and they are employed by many countries across the globe. These interventions are designed to increase social distancing between individuals to reduce the transmission of the virus and eventually dampen the burden on the healthcare system. The virus transmissibility is a function of the average number of contacts individuals have in their communities and it is highly dependent on population density and daily mobility patterns, along with other social factors. These show significant variation across the United States. In this article, we study the effectiveness of social distancing measures in communities with different population density. Specifically, first we show how the empirical estimation of reproduction number differs for two completely different states, thus the experience of the COVID-19 outbreak is drastically different, suggesting different outbreak growth rates in practice. Second, we develop an age-structured compartmental model for simulating the disease spread in order to demonstrate the variation in the observed outbreak characteristics. We find that early trigger and late trigger options present a trade-off between the peak magnitude and the overall death toll of the outbreak which may also vary across different populations.

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 State-level Stay-at-home Orders and Objectively Measured Movement in the United States During the COVID-19 Pandemic

2020 ◽  
Author(s):  
Kyle J. Bourassa
Keyword(s):  
Public Health ◽  
United States ◽  
Public Health Intervention ◽  
State Level ◽  
Large Degree ◽  
The United States ◽  
Total Change ◽  
Social Distancing ◽  
Objectively Measured ◽  
At Home

Objective: Social distancing has been one of the primary interventions used to slow the spread of COVID-19. State-wide stay-at-home orders received a large degree of attention as a public health intervention to increase social distancing, but relatively little peer-reviewed research has examined the extent to which stay-at-home orders affected people’s behavior. Method: This study used GPS-derived movement from 2,858 counties in the United States from March 1 to May 7, 2020 to test the degree to which changes in state-level stay-at-home orders were associated with movement outside the home. Results: From the first week of March to the first week of April, people in counties within states that enacted stay-at-home orders decreased their movement significantly more than people in counties within states that did not enact state-level stay-at-home orders. From the first week of April to the first week of May, people in counties within states that ended their stay-at-home orders increased their movement significantly more than people in counties within states whose stay-at-home orders remained in place. The magnitude of change in movement associated with state-level stay-at-home orders was many times smaller than the total change in movement across all counties over the same periods of time in both cases. Conclusions: Stay-at-home orders are likely insufficient to reduce people’s movement outside the home without additional public health actions. Existing research on behavior change would be useful to determine what additional interventions could support social distancing behaviors during the COVID-19 pandemic if becomes necessary to reduce movement in the future.

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