A Spatial Cluster and Socio-demographic Analysis of COVID-19 Infection Determinants in Ohio, Michigan and Kentucky PDF Download

Author: Emmy Chepkemoi Soy
Publisher:
ISBN:
Category : COVID-19 (Disease)
Languages : en
Pages : 24

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Book Description
The World Health Organization declared COVID-19 a global pandemic in March 2020. Many countries and economies were greatly affected, including the United States of America. Many people were greatly affected causing them to go into critical care resulting in some eventual fatalities. Some of the factors that could have led to the widespread of infections can be attributed to the socio-demographic determinants, including gender, race/ethnicity, income, urban-rural location, access to healthcare and age. This study is aimed at exploring and examining patterns of COVID-19 infections by considering age, gender, health insurance coverage, race/ethnicity and income factors. Data from the Center for Disease Control (CDC), Department of Health and Human Services (HSS), the COVID tracking Project, and the U.S. Census Bureau (USCB) were used in this study. A Bayesian Conditional Autoregressive (CAR) model was used to explore the association between COVID-19 infection rates, hospitalizations and deaths, and socio-demographic variables using Open BUGS for the states of Ohio, Michigan and Kentucky. At the beginning of March 2020, the number of COVID-19 cases reported by the CDC for the USA was 123,498 infections.

Author: David A. Swanson
Publisher: IAP
ISBN:
Category : Health & Fitness
Languages : en
Pages : 259

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Book Description
The present volume undertakes socio-demographic analyses of four major topics surrounding the COVID-19 pandemic: Data Issues; Statistical Modeling; Analyses; and Policy Concerns. Regarding Data Issues, three chapters cover topics about obtaining reliable information; the production of summary statistics and using the geometric mean; and the importance of using a Demographic framework in better understanding the COVID-19 pandemic. Statistical modeling is a second topic, and is covered by three chapters. To begin with, one approach centers on modeling local areas. A second chapter discusses and provides a simple method for estimating the number of unconfirmed COVID-19 cases in a local area; a third chapter undertakes an examination of early warnings and responses. Analysis is a third topic and is covered by four chapters. The first chapter under this topic covers the effects of race and age on COVID-19. A second chapter examines the effects of COVID-19 on the broadband access and Census 2020 results for the Hopi and Lummi reservations. A third chapter examines the Black Lives Matters activism during the COVID-19 pandemic. A final chapter in this section examines the relative risk of dying from COVID-19 among those infected. A final topic focuses on policy issues. The first chapter under this topic examines partisan politics and COVID-19. A second chapter examines US policy and COVID-19 cases and deaths. A third chapter examines COVID-19 mortality rates and race-ethnic differences. A fourth chapter examines anti-Asian hate during the COVID-19 pandemic. A final chapter looks at America’s post-pandemic future.

Author: Rosemary M. Caron
Publisher: Frontiers Media SA
ISBN: 283255105X
Category : Medical
Languages : en
Pages : 229

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Book Description
The COVID-19 pandemic has disproportionately affected those population sectors that experience inequality. Specifically, marginalized racial and ethnic populations with pre-existing health conditions, those living in poverty, those possessing a low education level, hourly wage employees, etc. have experienced an excess burden of COVID-19 morbidity and mortality compared to their White counterparts in developed countries. The interaction of the social determinants of health with a novel virus has made visible the inequities that have been hidden or accustomed to in many communities globally. As we work to end the current pandemic, we must consider the post-COVID-19 pandemic era and address the social determinants of health so that populations start from a place of health, as opposed to a place of disease for the next public health challenge. Syndemic research has demonstrated the interaction among socio-cultural factors, socio-economic factors, structural factors, and individual factors (collectively referred to as the social determinants of health) and infectious disease epidemics (e.g., COVID-19, AIDS) and social epidemics (e.g., structural racism). These interactions can exacerbate and sustain adverse health outcomes for marginalized populations. How can communities improve the social determinants of health for impoverished populations? The importance of doing so would have implications not only for the health status of communities but could also improve economic conditions for these geographic areas. Addressing the social determinants of health for marginalized populations has the potential to improve health for all.

Author: Yefu Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 14

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Book Description
The COVID-19 is a global pandemic and crisis of public health. Although studies investigate the spatial factors of COVID-19, most of them are based on the macro-level. There is a rising demand to examine the emerging patterns of socio-demographic and COVID-19, especially for preventing the second-peak of COVID-19 outbreaks. This study was based on the recent release of zip code level data of COVID-19 and explore spatial relationships between socio-demographics and COVID-19 density through ordinary least squares (OLS) and geographically weighted regression (GWR). OLS results indicate that rates of poverty, rates of African Americans, and rates of Hispania were influential factors. Results of GWR are complementary to the OLS results. They suggest that associations between socio-demographics and COVID-19 density should be various in different postal areas. We argued that socio-demographics could play significant roles in COVID-19 outbreaks, which may be evidence that socio-demographic disparities happened during the COVID-19 crisis. We suggested that policymakers work on implementations involving interventions and prevention based on different priority levels. Also, it may be more productive for policymakers to implement strategies depending on local situations instead of globally.

Author: Dustin T. Duncan
Publisher: Oxford University Press
ISBN: 0197625215
Category : Medical
Languages : en
Pages : 497

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Book Description
"The novel coronavirus of 2019 (COVID-19) has caused one of the largest pandemics in human history. COVID-19 was declared a global pandemic in March 2020. The worldwide COVID health crisis has affected virtually every aspect of daily life, namely the conditions in which we are born, grow, learn, work, and age. For the last three years, for instance, we have engaged in social distancing, remote meetups and seemingly endless Zoom calls. We have also changed how we view healthcare, with many increasing their use of telemedicine. Many have also abandoned city living for a more comfortable life in suburban, peri-rural and rural environments, with greater access to trees and parkland. Travel has been significantly impacted-disrupting existing social networks but also potentially deepening more localized social networks. For some, these changes were only in initial lockdown period(s); for others, these changes may be ongoing. The idea for our book emerged from overwhelming evidence that the pandemic intersects with nearly every social determinant of population health and aggravating existing inequalities in social conditions and health outcomes"--

Author: Shih-Lung Shaw
Publisher: Springer Nature
ISBN: 3030728080
Category : Social Science
Languages : en
Pages : 358

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Book Description
This book describes the spatial and temporal perspectives on COVID-19 and its impacts and deepens our understanding of human dynamics during and after the global pandemic. It critically examines the role smart city technologies play in shaping our lives in the years to come. The book covers a wide-range of issues related to conceptual, theoretical and data issues, analysis and modeling, and applications and policy implications such as socio-ecological perspectives, geospatial data ethics, mobility and migration during COVID-19, population health resilience and much more. With accelerated pace of technological advances and growing divide on political and policy options, a better understanding of disruptive global events such as COVID-19 with spatial and temporal perspectives is an imperative and will make the ultimate difference in public health and economic decision making. Through in-depth analyses of concepts, data, methods, and policies, this book stimulates future studies on global pandemics and their impacts on society at different levels.

Author:
Publisher: World Health Organization
ISBN: 9240038388
Category : Social Science
Languages : en
Pages : 32

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Book Description

Author: George J. Borjas
Publisher:
ISBN:
Category : Coronavirus infections
Languages : en
Pages : 28

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Book Description
New York City is the hot spot of the COVID-19 pandemic in the United States. This paper merges information on the number of tests and the number of infections at the New York City zip code level with demographic and socioeconomic information from the decennial census and the American Community Surveys. People residing in poor or immigrant neighborhoods were less likely to be tested; but the likelihood that a test was positive was larger in those neighborhoods, as well as in neighborhoods with larger households or predominantly black populations. The rate of infection in the population depends on both the frequency of tests and on the fraction of positive tests among those tested. The non-randomness in testing across New York City neighborhoods indicates that the observed correlation between the rate of infection and the socioeconomic characteristics of a community tells an incomplete story of how the pandemic evolved in a congested urban setting.

Author: S M Asger Ali
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
The 21st century experienced several health crises, especially in the form of infectious disease outbreaks such as the SARS outbreak in 2003, the H1N1 in 2009, and Ebola outbreaks in 2013. However, none has produced a worldwide socio-economic and health impact compared to the recent pandemic, known as COVID-19. As of October 4, 2022, more than 614 million cases with 6 million deaths have been reported worldwide. The United States is currently in the leading position with more than 98 million cases and 1 million deaths. The pandemic, however, did not impact the entire region similarly, and the infections and intensity varied with geographical and socio-economic characteristics. In this project, I used a multi-method approach to analyze the relationship between health disparities and COVID-19-related health outcomes in the USA and examine the influence of health disparities reporting on newspaper coverage of COVID-19. This assessment was performed in three ways. First, I have explored the relationship between Mississippi’s county-level COVID-19-related cases and deaths with the Center for Disease Control and Preventions’s Social Vulnerability Index (CDC SVI). Second, I have investigated the spatial pattern of COVID-19 in the USA and its associations with Social Determinants of Health (SDoH) by utilizing the County Health Rankings & Roadmaps (CHRR) dataset.Finally, I analyzed how news media reporting of key health determinants (i.e., age, race, income and gender) is framed, including the role of different stakeholders in the context of COVID-19. Findings revealed a statistical relationship between CDC’s Social Vulnerability Index (SVI) and Mississippi’s county-level COVID-19 cases and deaths. I also found that COVID-19 infections showed considerable spatial heterogeneity as the distribution of COVID-19 cases and deaths varies across the US counties and among the three largest waves. The multiple regression results also exhibited a temporal association between social determinants of health (SDH) indicators and COVID-19-related health outcomes across the USA. Finally, I found that the NYT coverage of COVID-19 dealt more with human interest, responsibility, and conflict than economic and morality frames. The findings revealed the vital role social determinants of health play during a health crisis, such as the COVID-19 pandemic.

Author: Nader Zidan
Publisher:
ISBN:
Category : COVID-19 (Disease)
Languages : en
Pages : 0

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Book Description
The COVID-19 pandemic has impacted global health. To develop an effective strategy, understanding the relationship between comorbidities and COVID-19 outcomes is important. Equally as important is broad access to a large amount of patient data related to COVID-19 for research. A cohort of 776,936 confirmed COVID-19 patients (cases) and 1,362,545 healthy controls (with negative/no COVID-19 testing) was collected from the Regenstrief Institute COVID-19 Research Data Commons (CoRDaCo) in Indiana. Demographics, clinical diagnoses and encounters were collected for both cases and controls. Statistical analysis was conducted to determine the association of several demographic and clinical factors with COVID-19 severity. Data regarding county population and per capita income were obtained from the US Census Bureau. Hypothesis testing is applied to detect associations between various clinical variables and COVID-19 severity. Predictive analysis was conducted to evaluate the predictive power of CoRDaCo EHR data including comorbidities to predict COVID-19 severity. We found that chronic obstructive pulmonary disease (COPD), cardiovascular disease (CVD), and type 2 diabetes (T2D) were found in 3.49%, 2.59% and 4.76% of the COVID-19 patients, respectively. COVID-19 patients with these comorbidities have significantly higher ICU admission rates of 10.23%, 14.33% and 11.11%, respectively, compared to the entire COVID-19 patient population (1.94%). Furthermore, patients with these comorbidities have significantly higher mortality rates of 8.22%, 13.48% and 9.16%, respectively, compared to that of the entire COVID-19 patient population (2.24%). Socio-economic factor analysis suggests potential health disparities among counties in Indiana. Predictive analysis achieved F1-scores of 0.8011 and 0.7057 for classifying COVID-19 cases vs. controls and ICU vs. non-ICU cases, respectively. Overall, the findings indicate that elder patients are more susceptible to COVID-19 and comorbidities are strong risk factors for COVID-19 severity and mortality. ICU-admitted cases with comorbidities such as CVD, acute kidney failure, and cardiac arrest were older, and had higher death mortality rates than ICU-admitted controls with the same comorbidities. Furthermore, the Black population in Indiana was more adversely affected by COVID-19 than the White population.