scholarly journals Understanding the Impact of Walkability, Population Density, and Population Size on COVID-19 Spread: A Pilot Study of the Early Contagion in the United States

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1512
Author(s):  
Fernando T. Lima ◽  
Nathan C. Brown ◽  
José P. Duarte
Keyword(s):  
United States ◽  
Los Angeles ◽  
Population Density ◽  
Population Size ◽  
Spatial Configuration ◽  
The United States ◽  
Population Characteristics ◽  
Clear Correlation ◽  
Population Mixing ◽  
The Impact

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.

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.

Mitigation of COVID Strategies Comparison Between United States and Europe

2021 ◽  
pp. 359-382
Author(s):  
Mercedes Barrachina ◽  
Lucia Barrachina
Keyword(s):  
United States ◽  
Population Density ◽  
The United States ◽  
American Government ◽  
Additional Time ◽  
Hard Times ◽  
Medium Businesses ◽  
The Impact ◽  
Lower Population ◽  
Lower Population Density

The COVID-19 pandemic started in China at the end of 2019; however, during 2020, it has spread to more than 188 countries causing very hard times. Europe and the United States have followed different strategies to fight the virus. The differences between those areas in relation with the pandemic could be named shortly as for example the additional time that the United States had to prepare everything against the pandemic compared to Europe, as the American government had around three weeks in comparison to Europe to plan the strategy against the pandemic. The density of population is also an example of the differences between those areas as the United States has a lower population density compared to Europe, and this is another key fact affecting the spreading of COVID-19. The main objective of the study is to compare the different measures adopted by each region and analyze the impact they have in the economy and in small and medium businesses. Specific conclusions about the impact of the measures adopted will be extracted, and some lessons could be obtained from those conclusions.

Danzas Chuscas: Performing Migration in a Zapotec Community

2008 ◽  
Vol 40 (2) ◽  
pp. 3-22 ◽  
Author(s):  
Adriana Cruz-Manjarrez
Keyword(s):  
United States ◽  
Los Angeles ◽  
Inner City ◽  
Social Disorganization ◽  
Social Economic ◽  
The United States ◽  
Social Instability ◽  
The Subject ◽  
The Impact ◽  
The Village

Danzas chuscas are parodic dances performed in indigenous and mestizo villages throughout Mexico. In the village of Yalálag, a Zapotec indigenous village in the state of Oaxaca, Mexico, danzas chuscas are performed during religious celebrations, a time when many Yalaltecos (people from Yalálag) who have immigrated to Los Angeles return to visit their families. Since the late 1980s, these immigrants have become the subject of the dances. Yalaltecos humorously represent those who have adopted “American” behaviors or those who have remitted negative values and behaviors from inner-city neighborhoods of Los Angeles to Yalálag. Danzas chuscas such as “Los Mojados” (“The Wetbacks”), “Los Cocineros” (“The Cooks”), and “Los Cholos” (“Los Angeles Gangsters”) comically portray the roles that Yalaltec immigrants have come to play in the United States. Danzas chuscas such as “Los Norteños” (“The Northerners”), “Los Turistas” (“The Tourists”), and “El Regreso de los Mojados” (“The Return of the Wetbacks”) characterize Yalaltec immigrants as outsiders and visitors. And the choreography in dances like “Los Yalaltecos” (“The Residents of Yalálag”) and “Las Minifaldas” (“The Miniskirts”) reflect changes in these immigrants' social status, gender behaviors, and class position. In other words, these dances embody the impact of migration on social, economic, and cultural levels. Through physical humor immigrants and nonimmigrants confront the tensions and uncertainties stemming from Zapotec migration into the United States: community social disorganization, social instability, and changes in the meaning of group identity as it relates to gender, class, ethnicity, and culture.

scholarly journals The Spatiotemporal Interaction Effect of COVID-19 Transmission in the United States

2021 ◽  
Vol 10 (6) ◽  
pp. 387
Author(s):  
Lingbo Liu ◽  
Tao Hu ◽  
Shuming Bao ◽  
Hao Wu ◽  
Zhenghong Peng ◽  
...  
Keyword(s):  
United States ◽  
Population Density ◽  
Spatial Autocorrelation ◽  
Low Income ◽  
Pearson Correlation ◽  
The United States ◽  
Time Varying ◽  
Ols Regression ◽  
Highly Educated ◽  
The Impact

(1) Background: Human mobility between geographic units is an important way in which COVID-19 is spread across regions. Due to the pressure of epidemic control and economic recovery, states in the United States have adopted different policies for mobility limitations. Assessing the impact of these policies on the spatiotemporal interaction of COVID-19 transmission among counties in each state is critical to formulating epidemic policies. (2) Methods: We utilized Moran’s I index and K-means clustering to investigate the time-varying spatial autocorrelation effect of 49 states (excluding the District of Colombia) with daily new cases at the county level from 22 January 2020 to 20 August 2020. Based on the dynamic spatial lag model (SLM) and the SIR model with unreported infection rate (SIRu), the integrated SLM-SIRu model was constructed to estimate the inter-county spatiotemporal interaction coefficient of daily new cases in each state, which was further explored by Pearson correlation test and stepwise OLS regression with socioeconomic factors. (3) Results: The K-means clustering divided the time-varying spatial autocorrelation curves of the 49 states into four types: continuous increasing, fluctuating increasing, weak positive, and weak negative. The Pearson correlation analysis showed that the spatiotemporal interaction coefficients in each state estimated by SLM-SIRu were significantly positively correlated with the variables of median age, population density, and proportions of international immigrants and highly educated population, but negatively correlated with the birth rate. Further stepwise OLS regression retained only three positive correlated variables: poverty rate, population density, and highly educated population proportion. (4) Conclusions: This result suggests that various state policies in the U.S. have imposed different impacts on COVID-19 transmission among counties. All states should provide more protection and support for the low-income population; high-density populated states need to strengthen regional mobility restrictions; and the highly educated population should reduce unnecessary regional movement and strengthen self-protection.

Transnational Twist: Pecuniary Remittances and the Socioeconomic Integration of Authorized and Unauthorized Mexican Immigrants in Los Angeles County

2005 ◽  
Vol 39 (1) ◽  
pp. 69-102 ◽  
Author(s):  
Enrico A. Marcelli ◽  
B. Lindsay Lowell
Keyword(s):  
United States ◽  
Los Angeles ◽  
Los Angeles County ◽  
Mexican Immigrants ◽  
The United States ◽  
Neighborhood Context ◽  
Immigrant Integration ◽  
Individual Characteristics ◽  
Community Context ◽  
The Impact

Annual U.S.-Mexico pecuniary remittances are estimated to have more than doubled recently to at least $10 billion – augmenting interest among policymakers, financial institutions, and transnational migrant communities concerning how relatively poor expatriate Mexicans sustain such large transfers and the impact on immigrant integration in the United States. We employ the 2001 Los Angeles County Mexican Immigrant Residency Status Survey (LAC-MIRSS) to investigate how individual characteristics and social capital traditionally associated with integration, neighborhood context, and various investments in the United States influenced remitting in 2000. Remitting is estimated to have been inversely related to conventional integration metrics and influenced by community context in both sending and receiving areas. Contrary to straight-line assimilation theories and more consistent with a transnational or nonlinear perspective, however, remittances are also estimated to have been positively related to immigrant homeownership in Los Angeles County and negatively associated with having had public health insurance such as Medicaid.

scholarly journals Influence of Socio-Economic, Demographic and Climate Factors on the Regional Distribution of Dengue in the United States and Mexico

2020 ◽  
Author(s):  
Matthew Watts ◽  
Panagiota Kotsilla ◽  
P Graham Mortyn ◽  
Victor Sarto i Monteys ◽  
Cesira Urzi Brancati
Keyword(s):  
United States ◽  
Factor Analysis ◽  
Population Density ◽  
Age Structure ◽  
Regional Distribution ◽  
The United States ◽  
Economic Indicators ◽  
Climate Factors ◽  
Demographic Indicators ◽  
The Impact

Abstract Background: Dengue is one of the important vector-borne diseases in the world today; it infects tens of millions of people each year and has been on the rise since the 1950s. In this study, we develop a set of indicators that help us examine the impact of socio-economic and demographic factors on the occurrence of dengue in regions of the United States and Mexico. Methods: We assess the relationship between dengue occurrence in humans, climate factors (temperature and minimum quarterly rainfall), socio-economic factors (such as household income, regional rates of education, housing overcrowding, life expectancy, and medical resources), and demographic factors (such as migration flows, age structure of the population, and population density). Areas at risk of dengue are first selected based on the predicted presence of at least one of the two mosquito vectors responsible for dengue’s transmission: Aedes aegypti and Aedes albopictus. In those regions where the vectors had a high probability of presence, we assess the impact of the composite socio-economic indicators (derived through factor analysis to account for collinearity), and three composite demographic indicators (also derived from factor analysis) on the regional distribution of dengue cases, controlling for climate and spatial correlation. Results: We found that an increase of one unit in one of our socio-economic indicators representing labour force with at least secondary education, better broadband access, and rooms per inhabitant, a higher proportions of active physicians is related to a drop in the occurrence of dengue, whereas the demographic indicators such as population density, age structure of the population and population growth showed no significant impact after taking climate into account. More importantly, our socio-economic indicator can also explain differences in the occurrence of dengue across Mexico, whereas simpler measures, such as regional GDP could not. Conclusions: These results suggest that the set of indicators developed is a better indicator than GDP at predicting the distribution of dengue, by capturing information that is much more tailored to poverty related conditions which aid dengue transmission. Given that data for these indicators are available at a sub-national scale for OECD countries and selected OECD non-member economies, these indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations.

Eldercare in the United States and South Korea

2000 ◽  
Vol 21 (5) ◽  
pp. 632-651 ◽  
Author(s):  
DIANE I. LEVANDE ◽  
JOHN M. HERRICK ◽  
KYU-TAIK SUNG
Keyword(s):  
United States ◽  
South Korea ◽  
Cultural Values ◽  
Family Caregiving ◽  
Population Aging ◽  
Formal System ◽  
The United States ◽  
Population Characteristics ◽  
Informal System ◽  
The Impact

Despite a variety of differences in size, location, population characteristics, social organization, and cultural values and traditions, South Korea and the United States face dramatic increases in the numbers and proportions of older adults. Population aging raises profound questions about current and future eldercare arrangements in both countries. This article compares eldercare in the informal system of family caregiving and the formal system of government policies and public and private services in the United States and South Korea. Critical issues about changing conditions in each country and the impact of such changes for eldercare planning are addressed with attention to how the experiences of providing care for vulnerable elders in each country may be informative for the other.

A Pipeline of Unscrupulous Practices: Qualitative Study of Attitudes Toward the Social Security Disability Program

2020 ◽  
Vol 31 (3) ◽  
pp. 173-180
Author(s):  
Lila Rabinovich
Keyword(s):  
United States ◽  
Los Angeles ◽  
Qualitative Study ◽  
Social Security ◽  
The United States ◽  
Disability Benefits ◽  
Convenience Sample ◽  
The Social ◽  
Social Security Disability ◽  
The Impact

In the United States more than 8 million adults currently are covered by the Social Security Disability Insurance (SSDI) program, with enrollment projected to increase in the coming decades. This qualitative study explores views on work disability in the United States, and specifically on the SSDI program, among the general public. Six focus groups with a convenience sample of nonbeneficiary adults ( N = 41) were conducted in Los Angeles. We found that in spite of low levels of familiarity with the program, suspicion and prejudice against people claiming disability benefits and against the program itself were widespread among our participants. Specifically, participants argued that (a) there is a high prevalence of “scammer” disability applicants, and (b) the program fails to adequately safeguard against nondisabled claimants. Moreover, they viewed disability benefits as a symbolic admission of weakness, contrary to the U.S. ethos of hard work and against “government handouts,” and expressed a preference for claiming disability benefits as a last resort if they were ever to develop a disabling condition. Exploring public perceptions of disability and disability benefit programs helps us shed light on current cultural narratives around these topical issues. Future research could examine the impact of stigma of beneficiary status on beneficiaries’ wellbeing.

scholarly journals The Impact of the El Niño Southern Oscillation on the Number of Visitors to Natural Attractions: The Moderating Effect of Disposable Personal Income, per Capita GDP and Population

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1189
Author(s):  
Li Xiong ◽  
Ke Gong ◽  
Qingyun Tang ◽  
Yuanxiang Dong ◽  
Wei Xu
Keyword(s):  
United States ◽  
Population Size ◽  
Southern Oscillation ◽  
Gaussian Mixture ◽  
The United States ◽  
Disposable Income ◽  
Per Capita Gdp ◽  
Income Per Capita ◽  
Per Capita ◽  
The Impact

Analyzing the impact of El Nilo Southern Oscillation (ENSO) on the number of tourists is essential in realizing the sustainable development of natural scenic spots. From the current research results, research on the effects of ENSO on tourism focuses on the impact of the formation of the natural environment. However, there is a lack of ENSO-related research on the number of people arriving at natural attractions. This paper considers the adjustment effects of personal disposable income, per capita GDP, and population size and constructs a new framework of ENSO’s influence on tourism. This paper builds a system GMM (Gaussian Mixture Model) and analyzes the impact of ENSO on tourist flow by using Google Trend data (big data technology) to obtain annual passenger flow data of 48 natural scenic spots in the United States (mainly national parks and national forests). The empirical results show that the increase in ENSO has led to a significant decrease in visitors to natural attractions in the United States. Moreover, the increase in personal disposable income, per capita GDP, and population size can weaken the relationship between ENSO and the number of tourists. This research expands and enriches the theoretical perspective of ENSO and outdoor tourism.

scholarly journals The Spatiotemporal Interaction Effect of COVID-19 Transmission in the United States

2021 ◽  
Author(s):  
Lingbo Liu ◽  
Tao Hu ◽  
Shuming Bao ◽  
Hao Wu ◽  
Zhenghong Peng ◽  
...  
Keyword(s):  
United States ◽  
Population Density ◽  
Spatial Autocorrelation ◽  
Low Income ◽  
Pearson Correlation ◽  
The United States ◽  
Time Varying ◽  
Ols Regression ◽  
Highly Educated ◽  
The Impact

Abstract Background: Human mobility among geographic units is a possible cause of the widespread transmission of COVID-19 across regions. Due to the pressure of epidemic control and economic recovery, the states of the United States have adopted different policies for mobility limitations. Assessing the impact of these policies on the spatiotemporal interaction of COVID-19 transmission among counties in each state is critical to formulating the epidemic policies.Methods: The study utilized Moran’s I index and K-means clustering to investigate the time-varying spatial autocorrelation effect of 49 states (except the District of Colombia) with the daily new cases at the county level from Jan 22, 2020, to August 20, 2020. Based on the dynamic spatial lag model (SLM) and the SIR model with unreported infection rate (SIRu), the integrated SLM-SIRu model was constructed to estimate the inter-county spatiotemporal interaction coefficient of daily new cases in each state, which was further explored by Pearson correlation and stepwise OLS regression with socioeconomic factors.Results: The K-means clustering divided the time-varying spatial autocorrelation curves of 49 states into four types: continuous increasing, fluctuating increasing, weak positive, and weak negative. The Pearson correlation analysis showed that the spatiotemporal interaction coefficients in each state estimated by SLM-SIRu were significantly positively correlated with median age, population density, and the proportion of international immigrants and the highly educated population, but negatively correlated with the birth rate. The voting rate for Donald Trump in the 2016 U.S. presidential election showed a weak negative correlation. Further stepwise OLS regression retained only three positive correlated variables: poverty rate, population density, and the highly educated population proportion.Interpretation: This result suggests that various state policies in the U.S. have imposed different impacts on COVID-19 transmission among counties. All states should provide more protection and support for the low-income population, high-density populated states need to strengthen regional mobility restrictions, and the highly educated population should reduce unnecessary regional movement and strengthen self-protection.

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