scholarly journals A Correlational Study on the Gross Domestic Product and Gross Domestic Product  Per Capita of a Country and Its COVID-19 Incidence and Mortality Rates

Author(s):  
Joseph Emmanuel G. Lopez

Some studies had shown that there is a relationship between the state of the economy of a country and COVID-19 incidence and mortality rates. However, these studies are mostly done on countries that are already developed. This study aims to find the relationship between GDP and GDP per capita and COVID-19 incidence and mortality rates in all countries. In addition, they will also be analyzed based on their different income levels. The data collected are from databases from World Bank and WHO and are analyzed through MS Excel and JASP. Spearman’s rho is used to analyze the overall data and stratified data. It has been found that the GDP per capita and incidence (r = .656, p < .001) and mortality rates (r = .521, p < .001) have a strong and moderate correlation, respectively. GDP’s relationship with incidence (r = .295, p < .001) and mortality rates (r = .346, p < .001) resulted in both weak correlations. Stratified analysis resulted in no significant relationships, except for GDP per capita’s relationship with incidence (r = .362, p = .011) and mortality rates (r = .348, p = .014) in low-middle countries, which yielded both weak correlations. These results show that there is indeed a relationship between the incidence and mortality rates and the economic status of a country before a pandemic, however, more factors need to be accounted for in order to help countries improve their pandemic response in the future.

Author(s):  
Joseph Emmanuel G. Lopez

Some studies had shown that there is a relationship between the state of the economy of a country and COVID-19 incidence and mortality rates. However, these studies are just done on countries that are often on developed countries. This study aims to find the relationship between GDP and GDP per capita and COVID-19 incidence and mortality rates on all countries. In addition, they will also be analyzed based on their different income levels. The data collected are from databases from World Bank and WHO and will be analyzed through MS Excel and JASP. Spearman’s rho is used to analyze the overall data and stratified data. It has been found that the GDP per capita and incidence (r = .656, p < .001) and mortality rates (r = .521, p < .001) have a strong and moderate correlations respectively. GDP’s relationship with incidence (r = .295, p < .001) and mortality rates (r = .346, p < .001) resulted in both weak correlations. Stratified analysis resulted in no significant relationships, except for GDP per capita’s relationship with incidence (r = .362, p = .011) and mortality rates (r = .348, p = .014) in low-middle countries, which yielded both weak correlations. These results show that there is indeed a relationship between the incidence and mortality rates and the economic status of a country before a pandemic, however, more factors need to be accounted for in order to help countries improve their pandemic response in the future.


Author(s):  
Joseph Emmanuel G. Lopez

Some studies had shown that there is a relationship between the state of the economy of a country and COVID-19 incidence and mortality rates. However, these studies are just done on countries that are often on developed countries. This study aims to find the relationship between GDP and GDP per capita and COVID-19 incidence and mortality rates on all countries. In addition, they will also be analyzed based on their different income levels. The data collected are from databases from World Bank and WHO and will be analyzed through MS Excel and JASP. Spearman’s rho is used to analyze the overall data and stratified data. It has been found that the GDP per capita and incidence (r = .656, p < .001) and mortality rates (r = .521, p < .001) have a strong and moderate correlations respectively. GDP’s relationship with incidence (r = .295, p < .001) and mortality rates (r = .346, p < .001) resulted in both weak correlations. Stratified analysis resulted in no significant relationships, except for GDP per capita’s relationship with incidence (r = .362, p = .011) and mortality rates (r = .348, p = .014) in low-middle countries, which yielded both weak correlations. These results show that there is indeed a relationship between the incidence and mortality rates and the economic status of a country before a pandemic, however, more factors need to be accounted for in order to help countries improve their pandemic response in the future.


Author(s):  
Joseph Emmanuel G. Lopez

Some studies had shown that there is a relationship between the state of the economy of a country and COVID-19 incidence and mortality rates. However, these studies are just done on countries that are often on developed countries. This study aims to find the relationship between GDP and GDP per capita and COVID-19 incidence and mortality rates on all countries. In addition, they will also be analyzed based on their different income levels. The data collected are from databases from World Bank and WHO and will be analyzed through MS Excel and JASP. Spearman’s rho is used to analyze the overall data and stratified data. It has been found that the GDP per capita and incidence (r = .656, p < .001) and mortality rates (r = .521, p < .001) have a strong and moderate correlations respectively. GDP’s relationship with incidence (r = .295, p < .001) and mortality rates (r = .346, p < .001) resulted in both weak correlations. Stratified analysis resulted in no significant relationships, except for GDP per capita’s relationship with incidence (r = .362, p = .011) and mortality rates (r = .348, p = .014) in low-middle countries, which yielded both weak correlations. These results show that there is indeed a relationship between the incidence and mortality rates and the economic status of a country before a pandemic, however, more factors need to be accounted for in order to help countries improve their pandemic response in the future.


Author(s):  
Joseph Emmanuel G. Lopez

Some studies had shown that there is a relationship between the state of the economy of a country and COVID-19 incidence and mortality rates. However, these studies are just done on countries that are often on developed countries. This study aims to find the relationship between GDP and GDP per capita and COVID-19 incidence and mortality rates in all countries. In addition, they will also be analyzed based on their different income levels. The data collected are from databases from World Bank and WHO and will be analyzed through MS Excel and JASP. Spearman’s rho is used to analyze the overall data and stratified data. It has been found that the GDP per capita and incidence (r = .656, p < .001) and mortality rates (r = .521, p < .001) have a strong and moderate correlations respectively. GDP’s relationship with incidence (r = .295, p < .001) and mortality rates (r = .346, p < .001) resulted in both weak correlations. Stratified analysis resulted in no significant relationships, except for GDP per capita’s relationship with incidence (r = .362, p = .011) and mortality rates (r = .348, p = .014) in low-middle countries, which yielded both weak correlations. These results show that there is indeed a relationship between the incidence and mortality rates and the economic status of a country before a pandemic, however, more factors need to be accounted for in order to help countries improve their pandemic response in the future.


Author(s):  
Khairunnisa Musari

Loan shark is a humanitarian problem faced by many countries in the world, including in Asia, even in the Association of Southeast Asian Nations (ASEAN)'s countries. Loan shark activities are found not only in Myanmar and Cambodia, which has the lowest per capita income in ASEAN but also in Indonesia, Thailand, Malaysia, Brunei, and even Singapore, which are the five countries with the highest gross domestic product (GDP) per capita in ASEAN. How are loan shark practices in ASEAN countries? Can nanofinance overcome the microfinance gap to fight the loan shark? How the practice of Bank Wakaf Mikro (BWM) in Indonesia to nanofinance with qardhul hassan contract? Find the answers in this chapter.


2020 ◽  
Vol 2 (1) ◽  
pp. 30-38
Author(s):  
Bartosz Kobuszewski

Introduction: Mental health is necessary for achieving the complete health by individuals. According to WHO, it is "a state of well-being in which every individual realizes his or her own potential, can cope with the normal stresses of life, can work productively and fruitfully, and is able to make a contribution to her or his community" (2). Unfortunately, there is an increasing number of people suffering from mental disorders that can deteriorate their life quality, lead to problems with the standard functioning in the society, a drop in productivity, and can cause disabilities. Purpose of the article: The purpose of this article was to attempt the estimation of indirect costs of sickness absence caused by mental and behavioural disorders (ICD-10: F00-F99) in Poland in the years 2012-2018. Materials and methods: Indirect costs were estimated with the human capital approach using data on sickness absence provided by the Polish Social Insurance Institution (ZUS) and macroeconomic indicators published by the Central Statistical Office in Poland (GUS). The individual productivity loss was introduced by means of three indicators: Gross Domestic Product (GDP) per capita, Gross Domestic Product per person employed, corrected Gross Domestic Product. Results: Estimated indirect costs of sickness absence caused by mental and behavioural disorders (ICD-10: F00-F99) in Poland in 2012 were: 1.62 billion PLN measured in terms of GDP per capita, 2.86 billion PLN measured in terms of corrected GDP per person employed, and 4.40 billion PL measured in terms of GDP per person employed. And those costs in 2018 were 2.93 billion PLN, 4.57 billion PLN, and 7.03 billion PLN respectively, and they were higher by ca. 60-80% than in 2012. Conclusions: The described estimation of indirect costs can lead to conclusions that mental health care in Poland is quite poor - indirect costs can reach twice the level of National Health Fund (NFZ) expenses on the mental health care.


2020 ◽  
Author(s):  
Lev Shagam

AbstractAt early stages of the COVID-19 pandemic which we are experiencing, the publicly reported incidence, mortality and case fatality rates (CFR) vary significantly between countries. Here we aim to untangle factors that are associated with the differences during the first quarter of the year 2020. Number of performed COVID-19 tests has a strong correlation with country-specific incidence (p < 2 × 10−16) and mortality rate (p = 5.1 × 10−8). Using multivariate linear regression we show that incidence and mortality rates correlate significantly with GDP per capita (p = 2.6 × 10−15 and 7.0 × 10−4, respectively), country-specific duration of the outbreak (2.6 × 10−4 and 0.0019), fraction of citizens over 65 years old (p = 0.0049 and 3.8 × 10−4) and level of press freedom (p = 0.021 and 0.019) which cumulatively explain 80% of variability of incidence and more than 60% of variability of mortality of the disease during the period analyzed. Country hemisphere demonstrated significant correlation only with mortality (p = 0.17 and 0.036) whereas population density (p = 0.94 and p = 0.75) and latitude (p = 0.61 and 0.059) did not reach significance in our model. Case fatality rate is shown to rise as the outbreak progresses (p=0.028). We rank countries by COVID-19 mortality corrected for incidence and the factors that were shown to affect it, and by CFR corrected for outbreak duration, yielding very similar results. Among the countries where the outbreak started after the 15th of February and with at least 1000 registered patients during the period analyzed, the lowest corrected CFR are seen in Israel, South Africa and Chile. The ranking results should be considered with caution as they do not consider all confounding factors or data reporting biases.


Author(s):  
Piotr Koryś ◽  
Maciej Tymiński

Abstract This paper presents the estimates of the gross domestic product (GDP) of the Congress Kingdom of Poland for the period 1870–1912. The authors used bottom-up methodology and calculated sectoral added values using historical economic, social, and demographic data. The presented results offer first ever insight into the structure of sectoral added values in the Congress Kingdom of Poland during the period of first globalization and first reliable estimates of GDP of the Congress Kingdom of Poland. All results are presented in Geary–Khamis dollars PPP1990 and are compatible with Maddison dataset.


Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 633
Author(s):  
Ertuğrul Karaçuha ◽  
Vasil Tabatadze ◽  
Kamil Karaçuha ◽  
Nisa Özge Önal ◽  
Esra Ergün

In this study, a new approach for time series modeling and prediction, “deep assessment methodology,” is proposed and the performance is reported on modeling and prediction for upcoming years of Gross Domestic Product (GDP) per capita. The proposed methodology expresses a function with the finite summation of its previous values and derivatives combining fractional calculus and the Least Square Method to find unknown coefficients. The dataset of GDP per capita used in this study includes nine countries (Brazil, China, India, Italy, Japan, the UK, the USA, Spain and Turkey) and the European Union. The modeling performance of the proposed model is compared with the Polynomial model and the Fractional model and prediction performance is compared to a special type of neural network, Long Short-Term Memory (LSTM), that used for time series. Results show that using Deep Assessment Methodology yields promising modeling and prediction results for GDP per capita. The proposed method is outperforming Polynomial model and Fractional model by 1.538% and by 1.899% average error rates, respectively. We also show that Deep Assessment Method (DAM) is superior to plain LSTM on prediction for upcoming GDP per capita values by 1.21% average error.


2008 ◽  
Vol 5 (2) ◽  
pp. 29-30 ◽  
Author(s):  
Felix Kauye

Malawi is a country in sub-Saharan Africa bordering Mozambique, Tanzania and Zambia. It has an area of approximately 118000 km2 and is divided into northern, central and southern regions. It has an estimated population of 13 million, 47% of whom are under 15 years of age and just 5% over 60 years. Its economy is largely based on agriculture, with tobacco being the main export. The projected growth in gross domestic product (GDP) for 2007 was 8.8%; GDP per capita was $284 per annum.


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