scholarly journals COVID-19 and socioeconomic development in Africa: The first 6 months (February 2020-August 2020)

2020 ◽  
Vol 6 (2) ◽  
pp. 1
Author(s):  
M. Michel Garenne
Keyword(s):  
Population Density ◽  
Age Structure ◽  
Socioeconomic Development ◽  
Case Fatality ◽  
World Health ◽  
Gdp Per Capita ◽  
Reproduction Rate ◽  
African Countries ◽  
The World ◽  
Per Capita

The study covers the first 6 months of the coronavirus disease 2019 (COVID-19) epidemics in 56 African countries (February 2020-August 2020). It links epidemiological parameters (incidence, case fatality) with demographic parameters (population density, urbanization, population concentration, fertility, mortality, and age structure), with economic parameters (gross domestic product [GDP] per capita, air transport), and with public health parameters (medical density). Epidemiological data are cases and deaths reported to the World Health Organization, and other variables come from databases of the United Nations agencies. Results show that COVID-19 spread fairly rapidly in Africa, although slower than in the rest of the world: In 3 months, all countries were affected, and in 6 months, approximately 1.1 million people (0.1% of the population) were diagnosed positive for COVID-19. The dynamics of the epidemic were fairly regular between April and July, with a net reproduction rate R0 = 1.35, but tended to slow down afterward, when R0 fell below 1.0 at the end of July. Differences in incidence were very large between countries and were correlated primarily with population density and urbanization, and to a lesser extent, with GDP per capita and population age structure. Differences in case fatality were smaller and correlated primarily with mortality level. Overall, Africa appeared very heterogeneous, with some countries severely affected while others very little.

scholarly journals SARS-COV-2 Vaccines: What Indicators are Associated with the Worldwide Distribution of the First Doses

2021 ◽  
Vol 58 ◽  
pp. 004695802110601
Author(s):  
Marcos Felipe Falcão Sobral ◽  
Brigitte Renata Bezerra de Oliveira ◽  
Ana Iza Gomes da Penha Sobral ◽  
Marcelo Luiz Monteiro Marinho ◽  
Gisleia Benini Duarte ◽  
...  
Keyword(s):  
Population Density ◽  
Life Expectancy ◽  
Human Development ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Gdp Per Capita ◽  
Reproduction Rate ◽  
Worldwide Distribution ◽  
Per Capita

The present study aimed to identify the factors associated with the distribution of the first doses of the COVID-19 vaccine. In this study, we used 9 variables: human development index (HDI), gross domestic product (GDP per capita), Gini index, population density, extreme poverty, life expectancy, COVID cases, COVID deaths, and reproduction rate. The time period was until February 1, 2021. The variable of interest was the sum of the days after the vaccine arrived in the countries. Pearson’s correlation coefficients were calculated, and t-test was performed between the groups that received and did not receive the immunizer, and finally, a stepwise linear regression model was used. 58 (30.4%) of the 191 countries received the SARS-CoV-2 vaccine. The countries that received the most doses were the United States, China, the United Kingdom, and Israel. Vaccine access in days showed a positive Pearson correlation HDI, GDP, life expectancy, COVID-19 cases, deaths, and reproduction rate. Human development level, COVID-19 deaths, GDP per capita, and population density are able to explain almost 50% of the speed of access to immunizers. Countries with higher HDI and per capita income obtained priority access.

scholarly journals Early trends of socio-economic and health indicators influencing case fatality rate of COVID-19 pandemic

2020 ◽  
Vol 90 (3) ◽  
Author(s):  
Shahir Asfahan ◽  
Aneesa Shahul ◽  
Gopal Chawla ◽  
Naveen Dutt ◽  
Ram Niwas ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Case Fatality Rate ◽  
Case Fatality ◽  
Health Indicators ◽  
World Health ◽  
Fatality Rate ◽  
Medical Doctors ◽  
Selection Of Variables ◽  
The World ◽  
Per Capita

Coronavirus disease 2019, i.e. COVID-19, started as an outbreak in a district of China and has engulfed the world in a matter of 3 months. It is posing a serious health and economic challenge worldwide. However, case fatality rates (CFRs) have varied amongst various countries ranging from 0 to 8.91%. We have evaluated the effect of selected socio-economic and health indicators to explain this variation in CFR. Countries reporting a minimum of 50 cases as on 14th March 2020, were selected for this analysis. Data about the socio-economic indicators of each country was accessed from the World bank database and data about the health indicators were accessed from the World Health Organisation (WHO) database. Various socioeconomic indicators and health indicators were selected for this analysis. After selecting from univariate analysis, the indicators with the maximum correlation were used to build a model using multiple variable linear regression with a forward selection of variables and using adjusted R-squared score as the metric. We found univariate regression results were significant for GDP (Gross Domestic Product) per capita, POD 30/70 (Probability Of Dying Between Age 30 And Exact Age 70 From Any of Cardiovascular Disease, Cancer, Diabetes or Chronic Respiratory Disease), HCI (Human Capital Index), GNI(Gross National Income) per capita, life expectancy, medical doctors per 10000 population, as these parameters negatively corelated with CFR (rho = -0.48 to -0.38 , p<0.05). Case fatality rate was regressed using ordinary least squares (OLS) against the socio-economic and health indicators. The indicators in the final model were GDP per capita, POD 30/70, HCI, life expectancy, medical doctors per 10,000, median age, current health expenditure per capita, number of confirmed cases and population in millions. The adjusted R-squared score was 0.306. Developing countries with a poor economy are especially vulnerable in terms of COVID-19 mortality and underscore the need to have a global policy to deal with this on-going pandemic. These trends largely confirm that the toll from COVID-19 will be worse in countries ill-equipped to deal with it. These analyses of epidemiological data are need of time as apart from increasing situational awareness, it guides us in taking informed interventions and helps policy-making to tackle this pandemic.

Searching for new Sources of growth. Are the Developing Countries Catching up with the Developed ones?

2015 ◽  
pp. 30-53
Author(s):  
V. Popov
Keyword(s):  
Developing Countries ◽  
Western Europe ◽  
Gdp Per Capita ◽  
The West ◽  
Catching Up ◽  
The Us ◽  
The World ◽  
Economic Divergence ◽  
Per Capita ◽  
Relative Standing

This paper examines the trajectory of growth in the Global South. Before the 1500s all countries were roughly at the same level of development, but from the 1500s Western countries started to grow faster than the rest of the world and PPP GDP per capita by 1950 in the US, the richest Western nation, was nearly 5 times higher than the world average and 2 times higher than in Western Europe. Since 1950 this ratio stabilized - not only Western Europe and Japan improved their relative standing in per capita income versus the US, but also East Asia, South Asia and some developing countries in other regions started to bridge the gap with the West. After nearly half of the millennium of growing economic divergence, the world seems to have entered the era of convergence. The factors behind these trends are analyzed; implications for the future and possible scenarios are considered.

The monetary value of disability-adjusted-life-years lost in Kenya in 2017.pdf

2019 ◽  
Author(s):  
Joses Kirigia ◽  
Rose Nabi Deborah Karimi Muthuri
Keyword(s):  
New York ◽  
International Monetary Fund ◽  
Health Expenditure ◽  
Analytical Framework ◽  
World Health ◽  
Gdp Per Capita ◽  
Current Health ◽  
Monetary Value ◽  
Life Years ◽  
Per Capita

<div>A variant of human capital (or net output) analytical framework was applied to monetarily value DALYs lost from 166 diseases and injuries. The monetary value of each of the 166 diseases (or injuries) was obtained through multiplication of the net 2019 GDP per capita for Kenya by the number of DALYs lost from each specific cause. Where net GDP per capita was calculated by subtracting current health expenditure from the GDP per capita. </div><div> </div><p>The DALYs data for the 166 causes were from IHME (Global Burden of Disease Collaborative Network, 2018), GDP per capita data from the International Monetary Fund world economic outlook database (International Monetary Fund, 2019), and the current health expenditure per person data from the WHO Global Health Expenditure Database (World Health Organization, 2019b). A model consisting of fourteen equations was calculated with Excel Software developed by Microsoft (New York).</p><p> </p>

Impact of hydroxychloroquin/azithromycin protocol on COVID-19 case-fatality rate reduction in Algeria. (Preprint)

2020 ◽  
Author(s):  
Ahmed Youssef Kada
Keyword(s):  
Case Fatality Rate ◽  
Doubling Time ◽  
Case Fatality ◽  
World Health ◽  
Fatality Rate ◽  
Therapeutic Protocol ◽  
First Case ◽  
The World ◽  
The Impact ◽  
At Home

BACKGROUND Covid-19 is an emerging infectious disease like viral zoonosis caused by new coronavirus SARS CoV 2. On December 31, 2019, Wuhan Municipal Health Commission in Hubei province (China) reported cases of pneumonia, the origin of which is a new coronavirus. Rapidly extendable around the world, the World Health Organization (WHO) declares it pandemic on March 11, 2020. This pandemic reaches Algeria on February 25, 2020, date on which the Algerian minister of health, announced the first case of Covid-19, a foreign citizen. From March 1, a cluster is formed in Blida and becomes the epicentre of the coronavirus epidemic in Algeria, its total quarantine is established on March 24, 2020, it will be smoothly alleviated on April 24. A therapeutic protocol based on hydroxychloroquine and azithromycin was put in place on March 23, for complicated cases, it was extended to all the cases confirmed on April 06. OBJECTIVE This study aimed to demonstrate the effectiveness of hydroxychloroquin/azithromycin protocol in Algeria, in particular after its extension to all patients diagnosed COVID-19 positive on RT-PCR test. We were able to illustrate this fact graphically, but not to prove it statistically because the design of our study, indeed in the 7 days which followed generalization of therapeutic protocol, case fatality rate decrease and doubling time increase, thus confirming the impact of wide and early prescription of hydroxychloroquin/azithromycin protocol. METHODS We have analyzed the data collected from press releases and follow-ups published daily by the Ministry of Health, we have studied the possible correlations of these data with certain events or decisions having a possible impact on their development, such as confinement at home and its reduction, the prescription of hydroxychloroquine/azithromycin combination for serious patients and its extension to all positive COVID subjects. Results are presented in graphics, the data collection was closed on 31/05/2020. RESULTS Covid-19 pandemic spreads from February 25, 2020, when a foreign citizen is tested positive, on March 1 a cluster is formed in the city of Blida where sixteen members of the same family are infected during a wedding party. Wilaya of Blida becomes the epicentre of coronavirus epidemic in Algeria and lockdown measures taken, while the number of national cases diagnosed begins to increases In any event, the association of early containment measures combined with a generalized initial treatment for all positive cases, whatever their degree of severity, will have contributed to a reduction in the fatality rate of COVID 19 and a slowing down of its doubling time. CONCLUSIONS In Algeria, the rapid combination of rigorous containment measure at home and early generalized treatment with hydroxychloroquin have demonstrated their effectiveness in terms of morbidity and mortality, the classic measures of social distancing and hygiene will make it possible to perpetuate these results by reducing viral transmission, the only unknown, the reopening procedure which can only be started after being surrounded by precautions aimed at ensuring the understanding of the population. CLINICALTRIAL Algeria, Covid-19, pandemic, hydroxychloroquin, azithromycin, case fatality rate

scholarly journals Infectious disease outbreaks in the African region: overview of events reported to the World Health Organization in 2018

2019 ◽  
Vol 147 ◽  
Author(s):  
F. Mboussou ◽  
P. Ndumbi ◽  
R. Ngom ◽  
Z. Kassamali ◽  
O. Ogundiran ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Disease Onset ◽  
Disease Outbreaks ◽  
Case Fatality ◽  
World Health ◽  
African Region ◽  
Regional Office ◽  
Member States ◽  
Infectious Disease Outbreaks ◽  
The World

Abstract The WHO African region is characterised by the largest infectious disease burden in the world. We conducted a retrospective descriptive analysis using records of all infectious disease outbreaks formally reported to the WHO in 2018 by Member States of the African region. We analysed the spatio-temporal distribution, the notification delay as well as the morbidity and mortality associated with these outbreaks. In 2018, 96 new disease outbreaks were reported across 36 of the 47 Member States. The most commonly reported disease outbreak was cholera which accounted for 20.8% (n = 20) of all events, followed by measles (n = 11, 11.5%) and Yellow fever (n = 7, 7.3%). About a quarter of the outbreaks (n = 23) were reported following signals detected through media monitoring conducted at the WHO regional office for Africa. The median delay between the disease onset and WHO notification was 16 days (range: 0–184). A total of 107 167 people were directly affected including 1221 deaths (mean case fatality ratio (CFR): 1.14% (95% confidence interval (CI) 1.07%–1.20%)). The highest CFR was observed for diseases targeted for eradication or elimination: 3.45% (95% CI 0.89%–10.45%). The African region remains prone to outbreaks of infectious diseases. It is therefore critical that Member States improve their capacities to rapidly detect, report and respond to public health events.

Convergence of GDP Per Capita Among Coffee Producing and Re-Exporting Countries in the World

2022 ◽  
Author(s):  
Reuben M.J. Kadigi ◽  
Elizabeth Robinson ◽  
Sylvia Szabo ◽  
Rajabu KANGILE ◽  
Charles P. Mgeni ◽  
...  
Keyword(s):  
Gdp Per Capita ◽  
The World ◽  
Per Capita

scholarly journals Using fuzzy logic for evaluating the level of countries’ (regions’) economic development

2012 ◽  
Vol 59 (3) ◽  
pp. 293-310 ◽  
Author(s):  
Gordan Stojic
Keyword(s):  
Mathematical Model ◽  
Economic Development ◽  
Fuzzy Logic ◽  
Developed Countries ◽  
Gdp Per Capita ◽  
Industrial Growth ◽  
The Poor ◽  
The World ◽  
Level Of Economic Development ◽  
Per Capita

There are several divisions of countries and regions in the world. Besides geo-political divisions, there also are economic divisions. The most common economic division is the that on developed countries and the poor ones. These divisions are a consequence of the level of: GDP, GDP per capita, unemployment rate, industrial growth, and so on. The question is how to define a mathematical model based on which the following will be assessed: who is rich and who is poor, or who is economically developed and who is not? How the boundaries of transition from one category to another can be defined? This paper presents a model for evaluating the level of economic development of countries and regions using "fuzzy" logic. The model was tested on a sample of 19 EU member countries and aspirants for membership.

scholarly journals Regional quality of living in Europe

REGION ◽  
2015 ◽  
Vol 2 (2) ◽  
pp. 1 ◽  
Author(s):  
Piet Lagas ◽  
Frank Van Dongen ◽  
Frank Van Rijn ◽  
Hans Visser
Keyword(s):  
Population Density ◽  
Capital City ◽  
Gdp Per Capita ◽  
European Regions ◽  
Policy Makers ◽  
The North ◽  
City Regions ◽  
Quality Of Living ◽  
Per Capita

This article sets out the conceptual framework and results of Regional Quality of Living indicators that were developed in order to benchmark European NUTS2 regions. Nine non-business-related indicators are constructed to support the goal of policy makers to improve the attractiveness of regions and cities for people or companies to settle in, and by doing so create economic growth. Each of the constructed indicators represents a pillar of the Quality of Living. The highest indicator scores are found for regions within Switzerland, Sweden, Norway and the Netherlands. Some countries show a wide divergence between regional scores. The southern regions of Italy and Spain, for example, have significantly lower scores than those in the north. In addition, capital city regions have better RQI scores. A positive correlation was found between the average RQI scores and both GDP per capita and weighted population density. Compared to GDP per capita, weighted population density has a modest influence on the RQI score. The European regions are divided into 11 clusters, based upon GDP per capita and weighted population density in order to benchmark a region with its peers.

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