scholarly journals The impact of ethnic segregation on neighbourhood-level social distancing in the United States amid the early outbreak of COVID-19

Urban Studies ◽  
2021 ◽  
pp. 004209802110501
Author(s):  
Wei Zhai ◽  
Xinyu Fu ◽  
Mengyang Liu ◽  
Zhong-Ren Peng
Keyword(s):  
Public Health ◽  
United States ◽  
Ethnic Minorities ◽  
Diversity Index ◽  
The United States ◽  
Ethnic Segregation ◽  
Minority Communities ◽  
Social Distancing ◽  
Neighbourhood Level ◽  
The Impact

The COVID-19 pandemic has been argued to be the ‘great equaliser’, but, in fact, ethnically and racially segregated communities are bearing a disproportionate burden from the disease. Although more people have been infected and died from the disease among these minority communities, still fewer people in these communities are complying with the suggested public health measures like social distancing. The factors contributing to these ramifications remain a long-lasting debate, in part due to the contested theories between ethnic stratification and ethnic community. To offer empirical evidence to this theoretical debate, we tracked public social-distancing behaviours from mobile phone devices across urban census tracts in the United States and employed a difference-in-difference model to examine the impact of racial/ethnic segregation on these behaviours. Specifically, we focussed on non-Hispanic Black and Hispanic communities at the neighbourhood level from three principal dimensions of ethnic segregation, namely, evenness, exposure, and concentration. Our results suggest that (1) the high ethnic diversity index can decrease social-distancing behaviours and (2) the high dissimilarity between ethnic minorities and non-Hispanic Whites can increase social-distancing behavior; (3) the high interaction index can decrease social-distancing behaviours; and (4) the high concentration of ethnic minorities can increase travel distance and non-home time but decrease work behaviours. The findings of this study shed new light on public health behaviours among minority communities and offer empirical knowledge for policymakers to better inform just and evidence-based public health orders.

scholarly journals Dual MD–MPH Degree Students in the United States: Moving the Medical Workforce Toward Population Health

2021 ◽  
pp. 003335492097842
Author(s):  
Jo Marie Reilly ◽  
Christine M. Plepys ◽  
Michael R. Cousineau
Keyword(s):  
Public Health ◽  
United States ◽  
Population Health ◽  
Health Care Policy ◽  
The United States ◽  
Extensive Literature ◽  
Master Of Public Health ◽  
Telephone Interviews ◽  
Public Health Training ◽  
The Impact

Objective A growing need exists to train physicians in population health to meet the increasing need and demand for physicians with leadership, health data management/metrics, and epidemiology skills to better serve the health of the community. This study examines current trends in students pursuing a dual doctor of medicine (MD)–master of public health (MPH) degree (MD–MPH) in the United States. Methods We conducted an extensive literature review of existing MD–MPH databases to determine characteristics (eg, sex, race/ethnicity, MPH area of study) of this student cohort in 2019. We examined a trend in the MD community to pursue an MPH career, adding additional public health and health care policy training to the MD workforce. We conducted targeted telephone interviews with 20 admissions personnel and faculty at schools offering MD–MPH degrees in the United States with the highest number of matriculants and graduates. Interviews focused on curricula trends in medical schools that offer an MD–MPH degree. Results No literature describes the US MD–MPH cohort, and available MD–MPH databases are limited and incomplete. We found a 434% increase in the number of students pursuing an MD–MPH degree from 2010 to 2018. The rate of growth was greater than the increase in either the number of medical students (16%) or the number of MPH students (65%) alone. Moreover, MD–MPH students as a percentage of total MPH students more than tripled, from 1.1% in 2010 to 3.6% in 2018. Conclusions As more MD students pursue public health training, the impact of an MPH degree on medical school curricula, MD–MPH graduates, and MD–MPH career pursuits should be studied using accurate and comprehensive databases.

scholarly journals Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

2020 ◽  
Author(s):  
Niayesh Afshordi ◽  
Benjamin Holder ◽  
Mohammad Bahrami ◽  
Daniel Lichtblau
Keyword(s):  
United States ◽  
Population Density ◽  
The United States ◽  
Effective Response ◽  
Susceptible Population ◽  
Local Climate ◽  
Climate Conditions ◽  
Mortality And Morbidity ◽  
Social Distancing ◽  
The Impact

The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., “herd immunity”), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.

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 Migration and Food Consumption: The Impact of Culture and Country of Origin on Obesity as an Indicator of Human Health

2020 ◽  
Vol 12 (18) ◽  
pp. 7567
Author(s):  
Yuval Arbel ◽  
Chaim Fialkoff ◽  
Amichai Kerner
Keyword(s):  
Public Health ◽  
United States ◽  
Food Consumption ◽  
The United States ◽  
Type I ◽  
Russian Speakers ◽  
Conventional Measure ◽  
Research Findings ◽  
The Impact ◽  
Overweight Prevalence

Previous research demonstrates that the 1965 American immigration wave has tended to attenuate the obesity pandemic in the United States. Based on a survey carried out by the Israeli Central Bureau of Statistics (ICBS) in 2012 and 2016, we observe the correlation between BMI, age, native language, and years-since-migration to Israel. BMI (=kgm2) is a conventional measure of obesity, where BMI ≥ 25 is considered overweight and BMI ≥ 30 as type I obesity. The results indicate that compared to 11 groups of immigrants, the median BMI among native Israelis is lower. While the prevalence of overweight (BMI ≥ 25) among Hebrew speakers is below 50%, in 11 groups of immigrants, the prevalence of overweight is above 50%. A noteworthy exception is the immigrants from Ethiopia, who exhibit lower overweight prevalence compared to native Israelis and all other population groups. Finally, while male Hebrew and Russian speakers cross the overweight benchmark at the same age (35 years), native Israeli women (Hebrew speakers) cross this benchmark only when they reach 50 years (15 years after the males) and Russian women cross this benchmark only five years after the Russian men. These research findings may be of assistance in public health and culture-oriented medicine.

scholarly journals Mining and Validating Social Media for COVID-19-Related Human Behaviors between January and July; An Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Ashlynn R. Daughton ◽  
Courtney Diane Shelley ◽  
Martha Barnard ◽  
Dax Gerts ◽  
Chrysm Watson Ross ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Ground Truth ◽  
The United States ◽  
Training Data ◽  
Long Term Effects ◽  
Social Distancing ◽  
Human Behaviors ◽  
Mobility Data ◽  
The Impact

BACKGROUND Health authorities can minimize the impact of an emergent infectious disease outbreak through effective and timely risk communication, which can build trust and adherence to subsequent behavioral messaging. Monitoring the psychological impacts of an outbreak, as well as public adherence to such messaging is also important for minimizing long term effects of an outbreak. OBJECTIVE We used social media data to identify human behaviors relevant to COVID-19 transmission and the perceived impacts of COVID-19 on individuals as a first step toward real time monitoring of public perceptions to inform public health communications. METHODS We develop a coding schema for 6 categories and 11 subcategories, which includes both a wide number of behaviors, as well codes focused on the impacts of the pandemic (e.g., economic and mental health impacts). We use this to develop training data and develop supervised learning classifiers for classes with sufficient labels. Classifiers that perform adequately are applied to our remaining corpus and temporal and geospatial trends are assessed. We compare the classified patterns to ground truth mobility data and actual COVID-19 confirmed cases to assess the signal achieved here. RESULTS We apply our labeling schema to ~7200 tweets. The worst performing classifiers have F1 scores of only 0.18-0.28 when trying to identify tweets about monitoring symptoms and testing. Classifiers about social distancing, however, are much stronger with F1 scores of 0.64-0.66. We applied the social distancing classifiers to over 228 million tweets. We show temporal patterns consistent with real-world events, and show correlations of up to -0.5 between social distancing signals on Twitter and ground-truth mobility throughout the United States. CONCLUSIONS Behaviors discussed on Twitter are exceptionally varied. Twitter can provide useful information for parameterizing models that incorporate human behavior as well as informing public health communication strategies by describing awareness of and compliance with suggested behaviors. CLINICALTRIAL N/A

scholarly journals Socioeconomic Disparities in Social Distancing During the COVID-19 Pandemic in the United States: Observational Study (Preprint)

2020 ◽  
Author(s):  
Romain Garnier ◽  
Jan R Benetka ◽  
John Kraemer ◽  
Shweta Bansal
Keyword(s):  
United States ◽  
Black People ◽  
The United States ◽  
Control Measures ◽  
Mobility Patterns ◽  
Poverty Level ◽  
Social Distancing ◽  
Mobility Data ◽  
Black Populations ◽  
The Impact

BACKGROUND Eliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic. OBJECTIVE We aimed to assess how mobility patterns have varied across the United States during the COVID-19 pandemic and to identify associations with socioeconomic factors of populations. METHODS We used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level in the United States between February and May 2020, the period during which social distancing was widespread in this country. Using linear mixed models, we assessed the associations between social distancing and socioeconomic variables, including the proportion of people in the population below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density. RESULTS We found that the speed, depth, and duration of social distancing in the United States are heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; in contrast, we show that social distancing is intensely adopted in counties with higher population densities and larger Black populations. CONCLUSIONS Socioeconomic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of the COVID-19 pandemic in communities across the United States. These inequalities are likely to amplify existing health disparities and must be addressed to ensure the success of ongoing pandemic mitigation efforts.

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 Naming racism in the public health classroom

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243560
Author(s):  
Nadia N. Abuelezam ◽  
Andrés Castro Samayoa ◽  
Alana Dinelli ◽  
Brenna Fitzgerald
Keyword(s):  
Public Health ◽  
United States ◽  
Qualitative Content Analysis ◽  
The United States ◽  
Black Mothers ◽  
Structural Determinants ◽  
Final Exam ◽  
Local Climate ◽  
The Impact ◽  
Health Teaching

Objective The discussion of racism within undergraduate public health classrooms can be highly influenced by local and national conversations about race. We explored the impact of local and national events on students’ ability to name racism on a public health exam highlighting the impact of racism on maternal and infant health disparities for Black mothers. Methods We undertook this research within the context of an undergraduate introductory public health course at a primarily white institution in the Northeastern part of the United States. A qualitative content analysis of undergraduate student responses to a final exam question soliciting the importance of racism to health outcomes among Black mothers in the United States was undertaken. ANOVA tests were run to assess differences on naming racism, using semantic alternatives, and providing alternative explanations during three main time periods: prior to the election of the 45th president of the United States (pre-Trump), after the election (post-Trump), and after a nationally recognized racist campus incident. Results Between the pre- and post-Trump periods we see no differences in naming racism or providing alternative explanations. We do see a reduction in the proportion of students providing semantic alternatives for racism in the post-Trump period (32.2 vs. 25.2%, p = 0.034). After the racist campus incident, we see increases in the proportion of students naming race (53.6 vs. 73.8%, p = 0.021) and decreases in the proportion providing an alternative explanation (43.1 vs. 12.9%, p = 0.004), but no differences in the proportion of students who used semantic alternatives. Discussion This work lends itself to our understanding of how local climate affects public health teaching and may also influence students’ learning about important social and structural determinants of health. National and local climate should frame and guide public health teaching.

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.

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