Higher risk of COVID-19 hospitalization for unemployed: an analysis of 1,298,416 health insured individuals in Germany

AbstractBackgroundPrevious research on infectious disease has revealed that infection risk as well as the severity of diseases is related to income and poverty. In this study we investigate if unemployed persons have a higher risk to become hospitalized with a COVID-19 diagnosis compared with employed persons.MethodsWe used routine data on hospitalizations in a study population of 1,298,416persons between the ages 18 and 65 who were enrolled in a German health insurance and who were active on the labour market (either employed or unemployed). Hospital diagnosis of COVID-19 (ICD-10-GM U07.1 and U07.2) were reported on a daily basis from 01.01.2020 to 04.06.2020. We studied if the rate of persons hospitalized with a COVID-19 diagnoses differed by employment situation. Logistic regression models comparing employed with short- and long-term unemployed were calculated adjusting for age and sex.ResultsIn total, we observed 1,311 persons who were hospitalized, corresponding to a rate of 100.98 cases per 100.000 in our study population. Rates varied between the groups in different employment situations with lowest rates for employed and highest for long-term unemployed. Odds ratio for a hospitalization was 1.84 (1.64 - 2.07) for long-term and 1.18 (0.75 - 1.85) for short-term unemployed compared with employed persons.ConclusionThe results are in line with earlier (mainly ecological) studies from the USA and Great Britain which found social inequalities in hospitalization risk. The fact that differences exist in Germany, a country with a universal health care system, indicates socioeconomic differences in the COVID-19 pandemic exists across countries.

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Forecasting of COVID-19 Reproduction Number by ARIMA Methodology and Quantile Estimation based on Best Fit Distribution by L- moments for Top-10 Affected Countries

10.21203/rs.3.rs-471180/v1 ◽

2021 ◽

Author(s):

Muhammad Waqas ◽

Songhua Xu ◽

Linyun Zhou

Keyword(s):

Reproduction Number ◽

Quantile Estimation ◽

The Usa ◽

L Moments ◽

Short And Long Term ◽

Long Term Forecasting ◽

Novel Coronavirus ◽

The Uk ◽

Health Experts

Abstract We utilized the average weekly estimated reproduction number data of COVID-19 from March (2020–2021). By applying ARIMA and L-moments methodology, short-and-long-term forecasting of R0 is made for Govt. officials and public health experts to take before-time policy measures to control the spread of novel coronavirus. This study helps medical staff to measure the expected demand of COVID-19 vaccine doses. We applied various ARIMA models on each country’s data and the best selected based on RMSE, AIC, and BIC for point and interval forecasting. Application L-Moments techniques selected GLO, GEV, and GNO distributions and quantile estimation with return period calculations. The forecasting shows that maximum countries mean R0 > 1, which is still a serious threat and can lead to heath disaster. The forecasting provided an alarming situation in the coming months for India, France, Turkey, and Spain; health experts should take strict measures because the cases rise due to the high R0 forecast. The USA, Russia, and the UK mean R0 will not suddenly increase; these countries consistent in COVID-19 R0 control. We find that even the significant population differences prevail among selected countries, the R0 is still high in maximum countries, so its a dire need to take strict control actions to minimize the R0 for public safety.

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Abstract TMP81: Artificial Intelligence Beats Conventional Regression Analysis in Predicting Short and Long Term Risk of Stroke in Patients Undergoing Percutaneous Coronary Interventions

Stroke ◽

10.1161/str.51.suppl_1.tmp81 ◽

2020 ◽

Vol 51 (Suppl_1) ◽

Author(s):

Pradyumna Agasthi ◽

Chieh-Ju Chao ◽

Han Lun Wu ◽

Farouk Mookadam ◽

Nithin Venepally ◽

...

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Area Under The Curve ◽

Coronary Intervention ◽

Test Sample ◽

Training Sample ◽

Logistic Regression Models ◽

Percutaneous Coronary ◽

Short And Long Term

Introduction: Ischemic stroke (IS) causes substantial morbidity and mortality in patients undergoing percutaneous coronary intervention (PCI) with a 5 yr incidence ~ 3%. We sought the test the accuracy of Machine learning (ML) algorithms in predicting IS in patients undergoing PCI. Methods: Mayo Clinic CathPCI registry data were retrospectively analyzed from Jan 2003 - June 2018 including 21,872 patients who underwent PCI. The cohort was randomly divided into a training sample (75%, n=16404) and a unique test sample (25%, n=5468) prior to model generation. The risk prediction model was generated utilizing a random forest algorithm (RF model) on 188 unique variables to predict the risk of IS at 6-month, 1, 2, and 5-year post PCI. Conventional risk factors for stroke were used for logistic regression. The receiver operating characteristic (ROC) curve and area under the curve for the RF and logistic regression models were compared for the test cohort. Results: The mean age was 66.9 ± 12.4 years, and 71% were male. Patient demographics and outcomes are shown in Table 1 . The ROC area under the curve for the RF model was superior compared to the logistic regression model in predicting IS at 6 months, 1,2 and 5 yrs for the test cohort ( Figure 1 .) Conclusions: The RF model accurately predicts short and long term risk of IS and outperforms logistic regression analysis in patients undergoing PCI.

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Perceptions, Knowledge, and Practices Concerning Indoor Environmental Pollution of Parents or Future Parents

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17207669 ◽

2020 ◽

Vol 17 (20) ◽

pp. 7669

Author(s):

Laure Daniel ◽

Marylou Michot ◽

Maxime Esvan ◽

Pauline Guérin ◽

Guillaume Chauvet ◽

...

Keyword(s):

Environmental Pollution ◽

Social Inequalities ◽

Knowledge Score ◽

Cosmetic Products ◽

Social Inequalities In Health ◽

Indoor Pollutants ◽

Factors Associated ◽

Short And Long Term ◽

Random Draw

Indoor pollutants can have short- and long-term health effects, especially if exposure occurs during prenatal life or early childhood. This study describe the perceptions, knowledge, and practices of adults concerning indoor environmental pollution. Adults of 18 to 45 years of age were recruited in the department of Ille-et-Vilaine (Brittany-France) in 2019 through a stratified random draw in the waiting rooms of general practitioners (GPs) (n = 554) who completed a self-questionnaire. The 71% who had already heard of this type of pollution were older (p = 0.001), predominantly women (p = 0.007), not expecting a baby (p = 0.005), and had a higher knowledge score (p < 0.001). The average knowledge score was 6.6 ± 6.6 out of 11, which was higher for participants living in a couple and with a higher level of education (p < 0.001). Some practices were well implemented (>80% of participants) (aeration during renovation) whereas others were insufficiently practiced (<60% of participants) (paying attention to the composition of cosmetic products). Factors associated differed depending on the frequency of integration: living in a couple and having a child for well implemented practices and educational level, knowledge level, and perception for those under implemented. Knowledge must be improved to modify perceptions and certain practices, making sure not to increase social inequalities in health.

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Municipal Residence Level of Long-Term PM10 Exposure Associated with Obesity among Young Adults in Seoul, Korea

10.20944/preprints202008.0629.v1 ◽

2020 ◽

Author(s):

Jayeun Kim ◽

Kyuhyun Yoon

Keyword(s):

Young Adults ◽

Specific Effect ◽

Life Time ◽

Total Study Population ◽

Logistic Regression Models ◽

Specific Effects ◽

Study Population ◽

Socio Demographic Factors ◽

Pm10 Exposure

Background: The associations between long-term exposure to particulate matters (PM) in residential ambiance and obesity are comparatively less elucidated among young adults. Methods: Using 2017 Community Health Survey data with aged 19−29 participants in 25 communities, Seoul, the relationship between obesity and long−term PM10 levels of living district was examined. We defined obesity as overweight (25≤BMI&lt;30) or obese (30≤BMI) using Body Mass Index (BMI) from self-reported anthropometric information. Analysis was conducted sampling weighted logistic regression models by fitting municipal PM10 levels according to individual residence periods with 10 years and more residing in a current municipality. Socio-demographic factors were adjusted over all models and age−specific effect was explored among aged 19–24 and 25–29. Results: Total study population are 3,655 [men 1,680 (46.0%) and aged 19–24 1,933 (52.9%)] individuals. Among the communities with greater level of PM10; 2001–2005, associations with obesity were increased for overall with residence period; 10 years ≤ [Odds ratio, OR 1.071, 95% Confidence interval (CI) 0.969–1.185], 15 years ≤ [OR 1.118, 95% CI 1.004–1.245], and 20 years ≤ [OR 1.156, 95% CI 1.032–1.294]. However, decreased associations were detected for PM10; 2006–2010, and age–specific effects were modified according to the residence period. Conclusions: Although currently PM10 levels are decreasing, higher levels of PM10 exposure at the residential area during the earlier life-time may contribute in increasing obesity among young adults.

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Identifying early indicators of secondary peritonitis in critically ill patients with cirrhosis

Scientific Reports ◽

10.1038/s41598-021-00629-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Carole Ruault ◽

Nathalie Zappella ◽

Julien Labreuche ◽

Pierrick Cronier ◽

Baptiste Claude ◽

...

Keyword(s):

Functional Outcomes ◽

Secondary Peritonitis ◽

Decompensated Cirrhosis ◽

Rank Test ◽

Fungal Peritonitis ◽

Icd 10 ◽

Life Threatening ◽

Short And Long Term ◽

Early Indicators

AbstractAscitic fluid infection (AFI) is a life-threatening complication of cirrhosis. We aimed to identify early indicators of secondary peritonitis (SP), which requires emergency surgery, and to describe the outcomes of SP and spontaneous bacterial/fungal peritonitis (SBFP). Adults with cirrhosis and AFI admitted to 16 university or university-affiliated ICUs in France between 2002 and 2017 were studied retrospectively. Cases were identified by searching the hospital databases for relevant ICD-10 codes and hospital charts for AFI. Logistic multivariate regression was performed to identify factors associated with SP. Secondary outcomes were short- and long-term mortality and survivors’ functional outcomes. Of 178 included patients (137 men and 41 women; mean age, 58 ± 11 years), 21 (11.8%) had SP, confirmed by surgery in 16 cases and by abdominal computed tomography in 5 cases. Time to diagnosis exceeded 24 h in 7/21 patients with SP. By multivariate analysis, factors independently associated with SP were ascitic leukocyte count > 10,000/mm3 (OR 3.70; 95%CI 1.38–9.85; P = 0.009) and absence of laboratory signs of decompensated cirrhosis (OR 4.53; 95%CI 1.30–15.68; P = 0.017). The 1-year mortality rates in patients with SBFP and SP were 81.0% and 77.5%, respectively (Log-rank test, P = 0.92). Patients with SP vs. SBFP had no differences in 1-year functional outcomes. This multicenter retrospective study identified two indicators of SP as opposed to SBFP in patients with cirrhosis. Using these indicators may help to provide early surgical treatment.

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The Impact of the Global Financial Crisis, Does It Sustain?

International Journal of Economics and Finance ◽

10.5539/ijef.v8n10p82 ◽

2016 ◽

Vol 8 (10) ◽

pp. 82 ◽

Cited By ~ 1

Author(s):

Bashar Al-Zu'bi ◽

Hussein Salameh ◽

Qasim Mousa Abu Eid

Keyword(s):

Financial Crisis ◽

Stock Market ◽

Global Financial Crisis ◽

Stock Market Index ◽

The World ◽

The Usa ◽

Short And Long Term ◽

The Global Financial Crisis ◽

The Impact

<p>This paper studies the short and long term relationship between S&P500 USA stock market index and the stock market indices of 30 countries around the world over the period June 2010-April 2015. We implement OLS regression and use error correction model to examine the short and long term relationship between the variables. Empirically, we find that there is a relationship on the short and long term between S&P500 and the indices of 27 countries from East Asia, Europe, Latin America, Middle East as well as the countries of Australia and Canada. These results conclude that the global financial crisis of 2007-2008 significantly and lengthy increased the already high level of co-movement between the USA financial market and the observed stock market for 27 countries around the world. The findings from our research are important; however, we believe that further research based on our findings is necessary.</p>

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Modelling methane emissions from remotely collected liveweight data and faecal near-infrared spectroscopy in beef cattle

Animal Production Science ◽

10.1071/an14615 ◽

2014 ◽

Vol 54 (12) ◽

pp. 1980 ◽

Cited By ~ 4

Author(s):

L. A. González ◽

E. Charmley ◽

B. K. Henry

Keyword(s):

Infrared Spectroscopy ◽

Beef Cattle ◽

Near Infrared Spectroscopy ◽

Feed Intake ◽

Near Infrared ◽

Daily Basis ◽

Methane Emissions ◽

National Inventory ◽

Short And Long Term

The objective of the present study was to develop a model-data fusion approach using remotely collected liveweight (LW) data from individual animals (weighing station placed at the water trough) and evaluate the potential for these data from frequent weighing to increase the accuracy of estimates of methane emissions from beef cattle grazing tropical pastures. Remotely collected LW data were used to calculate daily LW change (LWC), i.e. growth rate on a daily basis, and then to predict feed intake throughout a 342-day grazing period. Feed intake and diet dry matter digestibility (DMD) from faecal near-infrared spectroscopy analysis were used to predict methane emissions using methods for both tropical and temperate cattle as used in the Australian national inventory (Commonwealth of Australia 2014). The remote weighing system captured both short- and long-term environmental (e.g. dry and wet season, and rainfall events) and management effects on LW changes, which were then reflected in estimated feed intake and methane emissions. Large variations in all variables, measured and predicted, were found both across animals and throughout the year. Methane predictions using the official national inventory model for tropical cattle resulted in 20% higher emissions than those for temperate cattle. Predicted methane emissions based on a simulation using only initial and final LW and assuming a linear change in LW between these two points were 7.5% and 5.8% lower than those using daily information on LW from the remote weighing stations for tropical and temperate cattle, respectively. Methane emissions and feed intake can be predicted from remotely collected LW data in near real-time on a daily basis to account for short- and long-term variations in forage quality and intake. This approach has the potential to provide accurate estimates of methane emissions at the individual animal level, making the approach suitable for grazing livestock enterprises wishing to participate in carbon markets and accounting schemes.

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Mortality among patients with pleural effusion undergoing thoracentesis

European Respiratory Journal ◽

10.1183/09031936.00217114 ◽

2015 ◽

Vol 46 (2) ◽

pp. 495-502 ◽

Cited By ~ 34

Author(s):

Erin M. DeBiasi ◽

Margaret A. Pisani ◽

Terrence E. Murphy ◽

Katy Araujo ◽

Anna Kookoolis ◽

...

Keyword(s):

Heart Failure ◽

Congestive Heart Failure ◽

Renal Failure ◽

Pleural Effusion ◽

Malignant Effusion ◽

Risk Of Death ◽

The Usa ◽

Short And Long Term ◽

Long Term Mortality

Of the 1.5 million people diagnosed with pleural effusion in the USA annually, ∼178 000 undergo thoracentesis. While it is known that malignant pleural effusion portends a poor prognosis, mortality of patients with nonmalignant effusions has not been well studied.This prospective cohort study evaluated 308 patients undergoing thoracentesis. Chart review was performed to obtain baseline characteristics. The aetiology of the effusions was determined using standardised criteria. Mortality was determined at 30 days and 1 year.247 unilateral and 61 bilateral thoracenteses were performed. Malignant effusion had the highest 30-day (37%) and 1-year (77%) mortality. There was substantial patient 30-day and 1-year mortality with effusions due to multiple benign aetiologies (29% and 55%), congestive heart failure (22% and 53%), and renal failure (14% and 57%, respectively). Patients with bilateral, relative to unilateral, pleural effusion were associated with higher risk of death at 30 days and 1 year (17% versus 47% (hazard ratio (HR) 2.58, 95% CI 1.44–4.63) and 36% versus 69% (HR 2.32, 95% CI 1.55–3.48), respectively).Patients undergoing thoracentesis for pleural effusion have high short- and long-term mortality. Patients with malignant effusion had the highest mortality followed by multiple benign aetiologies, congestive heart failure and renal failure. Bilateral pleural effusion is distinctly associated with high mortality.

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Evolving Trends and Research Hotspots in Disaster Epidemiology From 1985 to 2020: A Bibliometric Analysis

Frontiers in Public Health ◽

10.3389/fpubh.2021.720787 ◽

2021 ◽

Vol 9 ◽

Author(s):

Tao Liu ◽

Xin Liu ◽

Yue Li ◽

Shuyu Liu ◽

Chunxia Cao

Keyword(s):

Health Effects ◽

Disaster Management ◽

Relevant Literature ◽

Disaster Medicine ◽

The Past ◽

The Usa ◽

Disaster Epidemiology ◽

Short And Long Term ◽

Research Hotspots

Background: Disaster epidemiology has not attracted enough attention in the past few decades and still faces significant challenges. This study aimed to systematically analyze the evolving trends and research hotspots in disaster epidemiology and provide insights into disaster epidemiology.Methods: We searched the Scopus and Web of Science Core Collection (WoSCC) databases between 1985 and 2020 to identify relevant literature on disaster epidemiology. The retrieval strategies were TITLE-ABS-KEY (disaster epidemiology) and TS = (disaster AND epidemiology). Bibliometrix, VOSviewer 1.6.6 and SigmaPlot 12.5 were used to analyze the key bibliometric indicators, including trends and annual publications, the contributions of countries, institutions, journals and authors, and research hotspots.Results: A total of 1,975 publications were included. There was an increasing trend in publications over the past 35 years. The USA was the most productive country. The most frequent institutions and journals were Fukushima Medical University and Prehospital and Disaster Medicine. Galea S made significant contributions to this field. “Epidemiology” was the highest-frequency keyword. COVID-19 was highly cited after 2019. Three research hotspots were identified: (i) the short- and long-term adverse health effects of disasters on the population; (ii) COVID-19 pandemic and emergency preparedness; and (iii) disaster management.Conclusions: In recent decades, the USA was a global leader in disaster epidemiology. Disaster management, the short- and long-term health effects of disasters, and the COVID-19 pandemic reflected the research focuses. Our results suggest that these directions will remain research hotspots in the future. International collaboration is also expected to widen and deepen in the field of disaster epidemiology.

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Global Investment and Development Trends in the Fintech Secto

Scientific Papers NaUKMA Economics ◽

10.18523/2519-4739.2021.6.1.90-98 ◽

2021 ◽

Vol 6 (1) ◽

pp. 90-98

Author(s):

Iryna Lukianenko ◽

Yevhen Riabtsun

Keyword(s):

Asia Pacific ◽

General Tendency ◽

Business Climate ◽

Investment Structure ◽

The Usa ◽

Innovation Capacity ◽

National Bank ◽

World Economic ◽

Short And Long Term

The article’s objectives are to reveal the general tendency in the global investment climate within the fintech industry and introduce the grouping approach for countries based on distinctive characteristics of local fintech and economic environments. Moreover, the paper results can be used as recommendations for local regulators in terms of the fintech industry development, which is a vital force for enhancing the competitiveness level of the countries in the context of world economic uncertainty.Statistics method is used to perform the investment activities and investment structure overview with a close look at three regions: Americas, EMEA (Europe, the Middle East, and Africa), and the Asia Pacific. The results indicate the largest role of the America region, the smallest – of the Asia-Pacific region, and two main trends in the investment structure by the nature of deals, the first with a predominance of M&A deals and the second with a high venture investments part.Another applied approach is clustering analysis. It is used to group the countries by the set of characteristics, which reflect the general economic conditions and innovation capacity in the financial sector of different countries from the general population. The clustering results give a snapshot of six groups of countries. The group with the highest results is called FinTech Olympus and consists of countries such as the USA, UK, and Singapore. The worst results were shown by the Fintech Jungle group represented by Kenya, Lebanon, Egypt, Uganda, Pakistan, Ghana, Nigeria, Bangladesh, and Ukraine. The other countries are grouped in four more clusters with research names – FinTech periphery, Asian-European, FinTech middle class, and Major players. Local regulators, for example, the National Bank of Ukraine, can further consider the results of clustering for maintaining fintech development policy to benefit the economy in general.In such conditions, the main tasks for the Ukrainian government are the improvement of business climate and fintech ecosystem development with the further discovery of their impact on the country’s competitiveness in an unstable economic environment in the short and long term. JEL classіfіcatіon: C40, G19, G20

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