scholarly journals A Comprehensive Analysis of COVID-19 Transmission and Fatality Rates at the County level in the United States considering Socio-Demographics, Health Indicators, Mobility Trends and Health Care Infrastructure Attributes

2020 ◽  
Author(s):  
Tanmoy Bhowmik ◽  
Sudipta Dey Tirtha ◽  
Naveen Chandra Iraganaboina ◽  
Naveen Eluru
Keyword(s):  
Health Care ◽  
Mortality Rate ◽  
Health Indicators ◽  
Mortality Rates ◽  
County Level ◽  
Model Framework ◽  
Transmission Rates ◽  
Health Care Infrastructure ◽  
The Impact ◽  
At Home

Background: Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that can contribute to the COVID-19 transmission/mortality rate. The current study effort is designed to remedy this by analyzing COVID-19 transmission/mortality rates considering a comprehensive set of factors in a unified framework. Method: We study two per capita dependent variables: (1) daily COVID-19 transmission rates and (2) total COVID-19 mortality rates. The first variable is modeled using a linear mixed model while the later dimension is analyzed using a linear regression approach. The model results are augmented with a sensitivity analysis to predict the impact of mobility restrictions at a county level. Findings: Several county level factors including proportion of African-Americans, income inequality, health indicators associated with Asthma, Cancer, HIV and heart disease, percentage of stay at home individuals, testing infrastructure and Intensive Care Unit capacity impact transmission and/or mortality rates. From the policy analysis, we find that enforcing a stay at home order that can ensure a 50% stay at home rate can result in a potential reduction of about 30% in daily cases. Interpretation: The model framework developed can be employed by government agencies to evaluate the influence of reduced mobility on transmission rates at a county level while accommodating for various county specific factors. Based on our policy analysis, the study findings support a county level stay at home order for regions currently experiencing a surge in transmission. The model framework can also be employed to identify vulnerable counties that need to be prioritized based on health indicators for current support and/or preferential vaccination plans (when available). Funding: None.

scholarly journals A comprehensive analysis of COVID-19 transmission and mortality rates at the county level in the United States considering socio-demographics, health indicators, mobility trends and health care infrastructure attributes

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249133
Author(s):  
Tanmoy Bhowmik ◽  
Sudipta Dey Tirtha ◽  
Naveen Chandra Iraganaboina ◽  
Naveen Eluru
Keyword(s):  
Health Care ◽  
Mortality Rate ◽  
Health Indicators ◽  
Mortality Rates ◽  
County Level ◽  
Model Framework ◽  
Transmission Rates ◽  
Health Care Infrastructure ◽  
The Impact ◽  
At Home

Background Several research efforts have evaluated the impact of various factors including a) socio-demographics, (b) health indicators, (c) mobility trends, and (d) health care infrastructure attributes on COVID-19 transmission and mortality rate. However, earlier research focused only on a subset of variable groups (predominantly one or two) that can contribute to the COVID-19 transmission/mortality rate. The current study effort is designed to remedy this by analyzing COVID-19 transmission/mortality rates considering a comprehensive set of factors in a unified framework. Methods and findings We study two per capita dependent variables: (1) daily COVID-19 transmission rates and (2) total COVID-19 mortality rates. The first variable is modeled using a linear mixed model while the later dimension is analyzed using a linear regression approach. The model results are augmented with a sensitivity analysis to predict the impact of mobility restrictions at a county level. Several county level factors including proportion of African-Americans, income inequality, health indicators associated with Asthma, Cancer, HIV and heart disease, percentage of stay at home individuals, testing infrastructure and Intensive Care Unit capacity impact transmission and/or mortality rates. From the policy analysis, we find that enforcing a stay at home order that can ensure a 50% stay at home rate can result in a potential reduction of about 33% in daily cases. Conclusions The model framework developed can be employed by government agencies to evaluate the influence of reduced mobility on transmission rates at a county level while accommodating for various county specific factors. Based on our policy analysis, the study findings support a county level stay at home order for regions currently experiencing a surge in transmission. The model framework can also be employed to identify vulnerable counties that need to be prioritized based on health indicators for current support and/or preferential vaccination plans (when available).

Endovascular Aortic Repair in Patients of Advanced Age

2021 ◽  
pp. 152660282110493
Author(s):  
Mitri K. Khoury ◽  
Micah A. Thornton ◽  
Christopher A. Heid ◽  
Jacqueline Babb ◽  
Bala Ramanan ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Survival Benefit ◽  
Elective Surgery ◽  
Endovascular Aneurysm Repair ◽  
The Elderly ◽  
Mortality Rates ◽  
Current Data ◽  
Aortic Aneurysms ◽  
Advanced Age ◽  
The Impact

Purpose: Treatment decisions for the elderly with abdominal aortic aneurysms (AAAs) are challenging. With advancing age, the risk of endovascular aneurysm repair (EVAR) increases while life expectancy decreases, which may nullify the benefit of EVAR. The purpose of this study was to quantify the impact of EVAR on 1-year mortality in patients of advanced age. Materials and Methods: The 2003–2020 Vascular Quality Initiative Database was utilized to identify patients who underwent EVAR for AAAs. Patients were included if they were 80 years of age or older. Exclusions included non-elective surgery or missing aortic diameter data. Predicted 1-year mortality of untreated AAAs was calculated based on a validated comorbidity score that predicts 1-year mortality (Gagne Index, excluding the component associated with AAAs) plus the 1-year aneurysm-related mortality without repair. The primary outcome for the study was 1-year mortality. Results: A total of 11 829 patients met study criteria. The median age was 84 years [81, 86] with 9014 (76.2%) being male. Maximal AAA diameters were apportioned as follows: 39.6% were <5.5 cm, 28.6% were 5.5–5.9 cm, 21.3% were 6.0–6.9 cm, and 10.6% were ≥7.0 cm. The predicted 1-year mortality rate without EVAR was 11.9%, which was significantly higher than the actual 1-year mortality rate with EVAR (8.2%; p<0.001). The overall rate of perioperative MACE was 4.4% (n = 516). Patients with an aneurysm diameter <5.5cm had worse actual 1-year mortality rates with EVAR compared to predicted 1-year mortality rates without EVAR. In contrast, those with larger aneurysms (≥5.5cm) had better actual 1-year mortality rates with EVAR. The benefit from EVAR for those with Gagne Indices 2–5 was largely restricted to those with AAAs ≥ 7.0cm; whereas those with Gagne Indices 0–1 experience a survival benefit for AAAs larger than 5.5 cm. Conclusion: The current data suggest that EVAR decreases 1-year mortality rates for patients of advanced age compared to non-operative management in the elderly. However, the survival benefit is largely limited to those with Gagne Indices 0–1 with AAAs ≥ 5.5 cm and Gagne Indices 2–5 with AAAs ≥ 7.0 cm. Those of advanced age may benefit from EVAR, but realizing this benefit requires careful patient selection.

Ethics and Efficiency in the Provision of Health Care

1988 ◽  
Vol 23 ◽  
pp. 111-126 ◽  
Author(s):  
Alan Williams
Keyword(s):  
Health Care ◽  
Driving Force ◽  
Mortality Rates ◽  
Equal Access ◽  
Demographic Structure ◽  
Major Purpose ◽  
Relative Mortality ◽  
Distribution Rule ◽  
The Uk ◽  
The Impact

1.1. A major purpose in nationalizing the provision of health care in the UK was to affect its distribution between people, and, in particular, to minimize the impact of willingness and ability to pay upon that distribution. It has never been clear, however, what alternative distribution rule is to apply. There is no shortage of rhetoric about ‘equality’ and ‘need’, but most of it is vacuous, by which I mean it does not lead to any clear operational guidelines about who should get priority and at whose expense. The closest we have got so far to such explicit guidelines has been the formulae which determine the geographical distribution of NHS funds, the driving force behind which is a notion of need based on relative mortality rates and on the demographic structure. The avowed objective is to bring about equal access for equal need irrespective of where in the UK you happen to be.

scholarly journals Using Satellite Images and Deep Learning to Identify Associations Between County-Level Mortality and Residential Neighborhood Features Proximal to Schools: A Cross-Sectional Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Joshua J. Levy ◽  
Rebecca M. Lebeaux ◽  
Anne G. Hoen ◽  
Brock C. Christensen ◽  
Louis J. Vaickus ◽  
...  
Keyword(s):  
United States ◽  
Deep Learning ◽  
Mortality Rate ◽  
Satellite Images ◽  
The United States ◽  
Mortality Rates ◽  
Image Features ◽  
County Level ◽  
Crude Mortality Rate ◽  
Crude Mortality

What is the relationship between mortality and satellite images as elucidated through the use of Convolutional Neural Networks?Background: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images, prior work has demonstrated associations of the built environment with income, education, access to care, and health factors such as obesity. However, assessment of learned image feature relationships with variation in crude mortality rate across the United States has been lacking.Objective: We sought to investigate if county-level mortality rates in the U.S. could be predicted from satellite images.Methods: Satellite images of neighborhoods surrounding schools were extracted with the Google Static Maps application programming interface for 430 counties representing ~68.9% of the US population. A convolutional neural network was trained using crude mortality rates for each county in 2015 to predict mortality. Learned image features were interpreted using Shapley Additive Feature Explanations, clustered, and compared to mortality and its associated covariate predictors.Results: Predicted mortality from satellite images in a held-out test set of counties was strongly correlated to the true crude mortality rate (Pearson r = 0.72). Direct prediction of mortality using a deep learning model across a cross-section of 430 U.S. counties identified key features in the environment (e.g., sidewalks, driveways, and hiking trails) associated with lower mortality. Learned image features were clustered, and we identified 10 clusters that were associated with education, income, geographical region, race, and age.Conclusions: The application of deep learning techniques to remotely-sensed features of the built environment can serve as a useful predictor of mortality in the United States. Although we identified features that were largely associated with demographic information, future modeling approaches that directly identify image features associated with health-related outcomes have the potential to inform targeted public health interventions.

scholarly journals The situation of elderly with cognitive impairment living at home during lockdown in the Corona-pandemic in Germany

2020 ◽  
Author(s):  
Jochen René Thyrian ◽  
Friederike Kracht ◽  
Angela Nikelski ◽  
Melanie Boekholt ◽  
Fanny Schumacher-Schönert ◽  
...  
Keyword(s):  
Primary Care ◽  
Health Care ◽  
Cognitive Impairment ◽  
Health Care Provision ◽  
Social Activities ◽  
Care Provision ◽  
Convenience Sample ◽  
Personal Impact ◽  
The Impact ◽  
At Home

Abstract Background: The outbreak of the Corona virus is a challenge for health care systems worldwide. The aim of this study is to analyze a) knowledge about, and feelings related to the Corona-pandemic. Describe b) loneliness, depression and anxiety and, c) the perceived, immediate impact of the lockdown on frequency of social contacts and quality of health care provision of people with cognitive impairment during social distancing and lockdown in the primary care system and living at home in Germany. Methods: This analysis is based on data of a telephone-based assessment in a convenience sample of n=141 people with known cognitive impairment in the primary care setting. Data on e.g. cognitive and psychological status prior to the pandemic was available. Attitudes, knowledge about and perceived personal impact of the pandemic, social support, loneliness, anxiety, depression, change in the frequency of social activities due to the pandemic and perceived impact of the pandemic on health care related services were assessed during the time of lockdown. Results: The vast majority of participants are sufficiently informed about Corona (85%) and most think that the measures taken are appropriate (64%). A total of 11% shows one main symptom of a depression according to DSM-5. The frequency of depressive symptoms has not increased between the time before pandemic and lockdown in almost all participants. The sample shows minimal (65.0%) or low symptoms of anxiety (25%). The prevalence of loneliness is 10%. On average seven activities have decreased in frequency due to the pandemic. Social activities related to meeting people, dancing or visiting birthdays have decreased significantly. Talking with friends by phone and activities like gardening have increased. Utilization of health care services like day clinics, relief services and prescribed therapies have been reported to have worsened due to the pandemic. Visits to general practitioners decreased. Conclusions: The study shows a small impact of the pandemic on psychological variables like depression, anxiety and loneliness in the short-term in Germany. There is a decrease in social activities as expected. The impact on health care provision is prominent. There is a need for qualitative, in-depth studies to further interpret the results.

NEONATAL MORTALITY IN THE EMPOWERED ACTION GROUP STATES OF INDIA: TRENDS AND DETERMINANTS

2008 ◽  
Vol 40 (2) ◽  
pp. 183-201 ◽  
Author(s):  
PERIANAYAGAM AROKIASAMY ◽  
ABHISHEK GAUTAM
Keyword(s):  
Health Care ◽  
Infant Mortality ◽  
Neonatal Mortality ◽  
Universal Coverage ◽  
Mortality Rates ◽  
Mortality Data ◽  
Registration System ◽  
Action Group ◽  
Eag States ◽  
The Impact

SummaryIn India, the eight socioeconomically backward states of Bihar, Chhattisgarh, Jharkhand, Madhya Pradesh, Orissa, Rajasthan, Uttaranchal and Uttar Pradesh, referred to as the Empowered Action Group (EAG) states, lag behind in the demographic transition and have the highest infant mortality rates in the country. Neonatal mortality constitutes about 60% of the total infant mortality in India and is highest in the EAG states. This study assesses the levels and trends in neonatal mortality in the EAG states and examines the impact of bio-demographic compared with health care determinants on neonatal mortality. Data from India’s Sample Registration System (SRS) and National Family and Health Survey (NFHS-2, 1998–99) are used. Cox proportional hazard models are applied to estimate adjusted neonatal mortality rates by health care, bio-demographic and socioeconomic determinants. Variations in neonatal mortality by these determinants suggest that universal coverage of all pregnant women with full antenatal care, providing assistance at delivery and postnatal care including emergency care are critical inputs for achieving a reduction in neonatal mortality. Health interventions are also required that focus on curtailing the high risk of neonatal deaths arising from the mothers’ younger age at childbirth, low birth weight of children and higher order births with short birth intervals.

The Effect of Health Expenditure and Immunisation on Under-Five Mortality Rate in Selected African Countries.

2021 ◽  
Author(s):  
Alfred EBOH ◽  
Steve METIBOBA
Keyword(s):  
Health Care ◽  
Mortality Rate ◽  
Health Expenditure ◽  
Health Care Systems ◽  
Health Care Expenditure ◽  
African Countries ◽  
Under Five ◽  
Significant Negative Effect ◽  
Negative Effect ◽  
The Impact

Abstract Background: As a way of tackling child mortality, many countries in the world depend on their respective health-care system. But governments of most countries in Africa are yet to provide robust funding of their health-care systems as many people still depend on the out-of-pocket payment to receive health services. Against this backdrop, this study used annual panel data to assess the effect of health-care expenditure and immunisation on the under-five mortality rate in 30 selected African countries for the period 2000-2017. Methods: Multiple regression technique was adopted for the data analysis and the robust fixed regression estimator was preferred to the random effects as determined by Hausman test.Results: The findings indicated that domestic government general health expenditure had a significant negative effect on the under-five mortality rate. However, the effect of domestic private health expenditure on under-five mortality was not significant while external health expenditure had a significant negative effect on under-five mortality rate. The impact of diphtheria immunisation on under-five mortality was significant. Conclusions: Except domestic private health expenditure, government and external forms of health expenditure coupled with diphtheria immunisation were significant factors for the reduction of the under-five mortality in the selected countries.

scholarly journals (A3) Health Care Facilities Affected by the Earthquake in Chile

2011 ◽  
Vol 26 (S1) ◽  
pp. s1-s2
Author(s):  
C. Bambaren
Keyword(s):  
Health Care ◽  
Health Care Services ◽  
Health Sector ◽  
Health Care Facilities ◽  
Cold Chain ◽  
Care Services ◽  
Biomedical Equipment ◽  
Care Facilities ◽  
Health Care Infrastructure ◽  
The Impact

IntroductionOn February 27, 2010, a 8,8 MW earthquake struck the central and southern coast of Chile, that was followed by a tsunami that destroyed some cities such as Constitution, Ilaco, Talcahuando and Dichato. The national authorities reported 512 dead and 81,444 homes were affected. It was the one of the five most powerful earthquakes in the human modern history. The most affected regions were Maule (VII) and Bio (VIII).ResultsThe impact of the quake in the health sector was enormous especially on the health care infrastructure. The preliminary evaluations showed that 18 hospitals were out of service due severe structural and no-structural damages, interruption of the provision of water or because they were at risk to landslides. Another 31 hospitals had moderate damage. The Ministry of Health lost 4249 beds including 297 (7%) in critical care units. Twenty-two percent of the total number of beds and thirty-nine surgical facilities available in the affected regions were lost in a few minutes due to quake. At least eight hospitals should be reconstructed and other hospitals will need complex repair.ConclusionThe effect of the earthquake was significant on hospital services. It included damages to the infrastructure and the loss of furniture and biomedical equipment. The interruption of the cold chain caused loss of vaccines. National and foreign field hospitals, temporary facilities and the strengthening of the primary health care facilities had been important to assure the continuation of health care services. *Based on information from PAHO – Chile.

Ethics and Efficiency in the Provision of Health Care

1988 ◽  
Vol 23 ◽  
pp. 111-126
Author(s):  
Alan Williams
Keyword(s):  
Health Care ◽  
Driving Force ◽  
Mortality Rates ◽  
Equal Access ◽  
Demographic Structure ◽  
Major Purpose ◽  
Relative Mortality ◽  
Distribution Rule ◽  
The Uk ◽  
The Impact

1.1. A major purpose in nationalizing the provision of health care in the UK was to affect its distribution between people, and, in particular, to minimize the impact of willingness and ability to pay upon that distribution. It has never been clear, however, what alternative distribution rule is to apply. There is no shortage of rhetoric about ‘equality’ and ‘need’, but most of it is vacuous, by which I mean it does not lead to any clear operational guidelines about who should get priority and at whose expense. The closest we have got so far to such explicit guidelines has been the formulae which determine the geographical distribution of NHS funds, the driving force behind which is a notion of need based on relative mortality rates and on the demographic structure. The avowed objective is to bring about equal access for equal need irrespective of where in the UK you happen to be.

Withdrawal of Care in a Trauma Intensive Care Unit: The Impact on Mortality Rate

2014 ◽  
Vol 80 (8) ◽  
pp. 764-767 ◽  
Author(s):  
Leonard J. Weireter ◽  
Jay N. Collins ◽  
Rebecca C. Britt ◽  
T. J. Novosel ◽  
L. D. Britt
Keyword(s):  
Intensive Care Unit ◽  
Decision Making ◽  
Mortality Rate ◽  
Trauma Center ◽  
Mortality Rates ◽  
Active Aging ◽  
Neurologic Injury ◽  
Trauma Service ◽  
The Impact ◽  
Overall Mortality

Withdrawal of care has increased in recent years as the population older than 65 years of age has increased. We sought to investigate the impact of this decision on our mortality rate. We retrospectively reviewed a prospectively collected database to determine the percentage of cases in which care was actively withdrawn. Neurologic injury as the cause for withdrawal, age of the patient, number of days to death, number of cases thought to be treatment failures, and the reason for failure were analyzed. Between January 2008 and December 2012, there were 536 trauma service deaths; 158 (29.5%) had care withdrawn. These patients were 67 (6 18.5) years old and neurologic injury was responsible in 63 per cent (6 5.29%). Fifty-two per cent of the patients died by Day 3; 65 per cent by Day 5; and 74 per cent Day 7. A total of 22.7 per cent (6 7.9%) could be considered a treatment failure. Accounting for cases in which care was withdrawn for futility would decrease the overall mortality rate by approximately 23 per cent. Trauma center mortality calculation does not account for care withdrawn. Treating an active, aging population, with advance directives, requires methodologies that account for such decision-making when determining mortality rates.

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