scholarly journals Application of Distribution-Delay Models to Estimating the Hospitalized Mortality Rate of Covid-19 According to Delay Effect of Hospitalizations Counts

2021 ◽  
Author(s):  
Sedighe Rastaghi ◽  
Noushin Akbari Shark ◽  
Azadeh Saki
Keyword(s):  
Mortality Rate ◽  
Measurement Errors ◽  
Distributed Delay ◽  
Delay Model ◽  
Delay Effect ◽  
Global Rate ◽  
Long Run ◽  
The World ◽  
Delay Models ◽  
Daily Hospitalization

Introduction:The COVID-19 infectious epidemic has become a serious worry all over the world, including Iran. The high outbreak of disease ranked Iran as second in Asia and 11th in the world. Given the growing progress of this epidemic in infecting and killing individuals, it is essential to forecast the delay effect of the number of hospitalized upon the hospitalized mortality rate. Methods: In this study, we used the daily Hospitalization cases of COVID-19 of IRAN for the period of 15-May 2020 to 5-Oct 2020 which were obtained from the online database. Five distribution delay models were compared for estimating and forecasting. Results: Based on measurement errors DDM selected as the best model for forecasting the number of death. According to this model, the long-run effects show that observing the effect of hospitalization counts on death counts takes an average of five days and the long-run hospitalized mortality rate was 12%. Conclusion: The overall hospitalized mortality rate of COVID-19 in Iran is less than the global rate of 15%. The mean of delay effect of daily hospitalization on mortality is approximately 5 days. Our findings showed distributed delay model (DDM) has better performance in the forecasting of the future behavior of the Coronavirus mortality, and providing to government and health care decision- makers the possibility to predict the outcomes of their decision on public health.

scholarly journals Modeling and forecasting hospitalized mortality rate of COVID-19 according to delay effect of daily hospitalization

2020 ◽  
Author(s):  
Sedighe Rastaghi ◽  
Noushin Akbari Shark ◽  
Azadeh Saki
Keyword(s):  
Mortality Rate ◽  
Measurement Errors ◽  
Distributed Delay ◽  
Delay Model ◽  
Delay Effect ◽  
Global Rate ◽  
Long Run ◽  
Modeling And Forecasting ◽  
The World ◽  
Daily Hospitalization

Abstract Introduction: The COVID-19 infectious epidemic has become a serious worry all over the world, including Iran. The high outbreak of disease ranked Iran as second in Asia and 11th in the world. Given the growing progress of this epidemic in infecting and killing individuals, it is essential to forecast the delay effect of the number of hospitalized upon the hospitalized mortality rate. Methods: In this study, we used the daily Hospitalization cases of COVID-19 of IRAN for the period of 15-May 2020 to 5-Oct 2020 which were obtained from the "Iran-COVID-19-Data[1]" database. Five distribution delay models were compared for estimating and forecasting. Results: based on measurement errors DDM selected as the best model for forecasting the number of death. According to this model, the long-run effects show that observing the effect of hospitalization counts on death counts takes an average of five days and the overall hospitalized mortality rate was 12%.Conclusion: The overall hospitalized mortality rate of COVID-19 in Iran is less than the global rate of 15%. The mean of delay effect of daily hospitalization on mortality is approximately 5 days. Our findings showed distributed delay model (DDM) has better performance in the forecasting of the future behavior of the Coronavirus mortality, and providing to government and health care decision- makers the possibility to predict the outcomes of their decision on public health.

The Role of Technological Change in the Long-run Global Economy Forecasting

2013 ◽  
pp. 97-116 ◽  
Author(s):  
A. Apokin
Keyword(s):  
Technological Change ◽  
Data Quality ◽  
Long Range ◽  
Global Economy ◽  
World Economy ◽  
Qualitative Approaches ◽  
Long Run ◽  
The World ◽  
National Economies

The author compares several quantitative and qualitative approaches to forecasting to find appropriate methods to incorporate technological change in long-range forecasts of the world economy. A?number of long-run forecasts (with horizons over 10 years) for the world economy and national economies is reviewed to outline advantages and drawbacks for different ways to account for technological change. Various approaches based on their sensitivity to data quality and robustness to model misspecifications are compared and recommendations are offered on the choice of appropriate technique in long-run forecasts of the world economy in the presence of technological change.

A Sustainable Approach for Organisational using Strategic Management

2020 ◽  
Vol 11 (2) ◽  
Author(s):  
Abdulla Almazrouei ◽  
◽  
Azlina Md Yassin ◽  
Keyword(s):  
Mortality Rate ◽  
Strategic Planning ◽  
Strategic Management ◽  
Crime Rate ◽  
External Environment ◽  
Police Department ◽  
Public Institutions ◽  
Abu Dhabi ◽  
The Public ◽  
The World

Strategic management have gained popularity in the public institutions to foster good delivery service to the public. The strategic planning enables organizations to establish a strategic match between the internal competency, resources and external environment. Majority of the successful organizations across the world use strategic management and planning as a tool that enables to optimize the operations and achieve maximum productivity with the resources. This paper reviewed on strategic management for organisations in Abu Dhabi especially for Abu Dhabi Police (ADP) force. It presents three strategic management theories which can be adopted by an organisation. This would help the organisation such as police department to reduce the increasing crime rate and mortality rate in UAE.

An Econometric Analysis on the Relationship between Globalisation and Inequality in South Africa

2020 ◽  
Vol 11 (1) ◽  
pp. 89-89
Author(s):  
Jacques de Jongh
Keyword(s):  
South Africa ◽  
Well Being ◽  
Causality Analysis ◽  
Global Integration ◽  
Development Indicators ◽  
Long Run ◽  
The World ◽  
Distribution Of Resources ◽  
Short Run ◽  
The Impact

Globalisation has had an unprecedented impact on the development and well-being of societies across the globe. Whilst the process has been lauded for bringing about greater trade specialisation and factor mobility many have also come to raise concerns on its impact in the distribution of resources. For South Africa in particular this has been somewhat of a contentious issue given the country's controversial past and idiosyncratic socio-economic structure. Since 1994 though, considerable progress towards its global integration has been made, however this has largely coincided with the establishment of, arguably, the highest levels of income inequality the world has ever seen. This all has raised several questions as to whether a more financially open and technologically integrated economy has induced greater within-country inequality (WCI). This study therefore has the objective to analyse the impact of the various dimensions of globalisation (economic, social and political) on inequality in South Africa. Secondary annual time series from 1990 to 2018 were used sourced from the World Bank Development indicators database, KOF Swiss Economic Institute and the World Inequality database. By using different measures of inequality (Palma ratios and distribution figures), the study employed two ARDL models to test the long-run relationships with the purpose to ensure the robustness of the results. Likewise, two error correction models (ECM) were used to analyse the short-run dynamics between the variables. As a means of identifying the casual effects between the variables, a Toda-Yamamoto granger causality analysis was utilised. Keywords: ARDL, Inequality, Economic Globalisation; Social Globalisation; South Africa

scholarly journals Computational Intelligence-Based Model for Mortality Rate Prediction in COVID-19 Patients

2021 ◽  
Vol 18 (12) ◽  
pp. 6429
Author(s):  
Irfan Ullah Khan ◽  
Nida Aslam ◽  
Malak Aljabri ◽  
Sumayh S. Aljameel ◽  
Mariam Moataz Aly Kamaleldin ◽  
...  
Keyword(s):  
Mortality Rate ◽  
Computational Intelligence ◽  
Nearest Neighbor ◽  
Gradient Boosting ◽  
K Nearest Neighbor ◽  
Detection And Identification ◽  
Proposed Model ◽  
Extreme Gradient Boosting ◽  
The World ◽  
Detection And Diagnosis

The COVID-19 outbreak is currently one of the biggest challenges facing countries around the world. Millions of people have lost their lives due to COVID-19. Therefore, the accurate early detection and identification of severe COVID-19 cases can reduce the mortality rate and the likelihood of further complications. Machine Learning (ML) and Deep Learning (DL) models have been shown to be effective in the detection and diagnosis of several diseases, including COVID-19. This study used ML algorithms, such as Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost), and K-Nearest Neighbor (KNN) and DL model (containing six layers with ReLU and output layer with sigmoid activation), to predict the mortality rate in COVID-19 cases. Models were trained using confirmed COVID-19 patients from 146 countries. Comparative analysis was performed among ML and DL models using a reduced feature set. The best results were achieved using the proposed DL model, with an accuracy of 0.97. Experimental results reveal the significance of the proposed model over the baseline study in the literature with the reduced feature set.

SARS-CoV-2 and Tissue Damage: Current Insights and Biomaterial-based Therapeutic Strategies

2021 ◽  
Author(s):  
Himadri Roy ◽  
Rupali Singh ◽  
Deepa Ghosh
Keyword(s):  
Mortality Rate ◽  
High Mortality ◽  
Tissue Damage ◽  
Therapeutic Strategies ◽  
The World ◽  
Rapid Transmission

The effect of SARS-CoV-2 infection on humanity has gained worldwide attention and importance due to its rapid transmission, lack of treatment and high mortality rate. While scientists across the world...

Twitter users exhibited coping behaviours during the COVID-19 lockdown: an analysis of tweets using mixed methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mittal ◽  
Wasim Ahmed ◽  
Amit Mittal ◽  
Ishan Aggarwal
Keyword(s):  
Data Analysis ◽  
The Body ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Long Run ◽  
The World ◽  
Twitter Users ◽  
The Government ◽  
Using Data

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.

The Comparison of Susceptibility to SARS-CoV-2 Infection between Pediatric and Adults

2021 ◽  
Author(s):  
Milad Zandi ◽  
Saber Soltani ◽  
Mona Fani ◽  
Haniye Shafipour ◽  
Samaneh Abbasi
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Mortality Rate ◽  
Age Groups ◽  
Severe Illness ◽  
Converting Enzyme ◽  
Angiotensin Converting Enzyme 2 ◽  
The World ◽  
Smoking Susceptibility ◽  
The Relationship

SARS-CoV-2 causes coronavirus disease 2019 (COVID-19) and is responsible for the recent pandemic in the world. It has been recently recognized as a challenge for public health and a significant cause of severe illness in all age groups. Young children and older people are susceptible to SARS-CoV-2 infection. However, children usually present mild symptoms compared to adult patients. The relationship between age, severity, and COVID-19 transmission is compared to determine whether there is any reasonable relationship between age and COVID-19. It should be mentioned that some risk factors may increase the probability of developing severe COVID-19 by advancing age, such as pathophysiological changes in the respiratory system, angiotensin-converting enzyme 2 expression in the nasopharynx, and smoking. Susceptibility to SARS-CoV-2 infection is independent of age, but the mortality rate of COVID-19 depends on age.

ORGANIZATIONAL AND METHODOLOGICAL APPROACHES TO THE RATIONAL MANAGEMENT OF THE PROCESS OF REDUCING MORTALITY FROM DISEASES OF THE CIRCULATORY SYSTEM

Vestnik ◽  
2021 ◽  
pp. 280-283
Author(s):  
М.А. Камалиев ◽  
С.Х. Алимбаева
Keyword(s):  
Mortality Rate ◽  
Medical Care ◽  
Circulatory System ◽  
The World ◽  
Rational Management ◽  
Methodological Approaches

Во всем мире болезни системы кровообращения считаются важнейшей проблемой потому, что показатели смертности от них превышают показатели смертности от любой другой причины. Обоснован перечень организационных резервов совершенствования медицинской помощи населению при болезнях системы кровообращения на основе усиления профилактической деятельности, ориентированной на конечные результаты. Diseases of the circulatory system are considered a serious problem all over the world, as the mortality rate from them exceeds the mortality rate from any other causes. The list of organizational reserves for improving medical care for the population with diseases of the circulatory system on the basis of strengthening preventive activities focused on the final results is justified.

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