COVID-19 case-fatality rate and demographic and socioeconomic influencers: a worldwide spatial regression analysis based on country-level data

We used the COVID-19 dataset obtained from the Our World in Data website and investigated the associations between COVID-19 CFR and nine country-level indices of 209 countries/territories using the Matern correlation regression model. Spatial dependence among the data was controlled using the latitude and longitude of the centroid of the countries/territories. Stratified analyses were conducted by economic level and COVID-19 testing policy. The average of country/territory-specific COVID-19 CFR is about 2-3% worldwide, which is higher than previously reported at 0.7-1.3%. Statistically significant associations were observed between COVID-19 CFR and population size and proportion of female smokers. The open testing policies are associated with decreased CFR. Strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher stringency index was associated with higher CFR in higher income countries with active testing policies. The statistically significant association between population size and COVID-19 CRF suggests the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in females and COVID-19 CFR might be due to that the proportion of female smokers reflected broadly income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations.

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COVID-19 case-fatality rate and demographic and socioeconomic influencers: worldwide spatial regression analysis based on country-level data

BMJ Open ◽

10.1136/bmjopen-2020-043560 ◽

2020 ◽

Vol 10 (11) ◽

pp. e043560 ◽

Cited By ~ 2

Author(s):

Yang Cao ◽

Ayako Hiyoshi ◽

Scott Montgomery

Keyword(s):

Death Rate ◽

Case Fatality Rate ◽

Spatial Regression ◽

Temporal Trends ◽

Case Fatality ◽

Secondary Outcome ◽

Fatality Rate ◽

Country Level ◽

Level Data ◽

Testing Policies

ObjectiveTo investigate the influence of demographic and socioeconomic factors on the COVID-19 case-fatality rate (CFR) globally.DesignPublicly available register-based ecological study.SettingTwo hundred and nine countries/territories in the world.ParticipantsAggregated data including 10 445 656 confirmed COVID-19 cases.Primary and secondary outcome measuresCOVID-19 CFR and crude cause-specific death rate were calculated using country-level data from the Our World in Data website.ResultsThe average of country/territory-specific COVID-19 CFR is about 2%–3% worldwide and higher than previously reported at 0.7%–1.3%. A doubling in size of a population is associated with a 0.48% (95% CI 0.25% to 0.70%) increase in COVID-19 CFR, and a doubling in the proportion of female smokers is associated with a 0.55% (95% CI 0.09% to 1.02%) increase in COVID-19 CFR. The open testing policies are associated with a 2.23% (95% CI 0.21% to 4.25%) decrease in CFR. The strictness of anti-COVID-19 measures was not statistically significantly associated with CFR overall, but the higher Stringency Index was associated with higher CFR in higher-income countries with active testing policies (regression coefficient beta=0.14, 95% CI 0.01 to 0.27). Inverse associations were found between cardiovascular disease death rate and diabetes prevalence and CFR.ConclusionThe association between population size and COVID-19 CFR may imply the healthcare strain and lower treatment efficiency in countries with large populations. The observed association between smoking in women and COVID-19 CFR might be due to the finding that the proportion of female smokers reflected broadly the income level of a country. When testing is warranted and healthcare resources are sufficient, strict quarantine and/or lockdown measures might result in excess deaths in underprivileged populations. Spatial dependence and temporal trends in the data should be taken into account in global joint strategy and/or policy making against the COVID-19 pandemic.

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An Environmental GIS-based Variable Analysis of SARS-CoV-2 in the City of Recife, Brazil

10.21203/rs.3.rs-117780/v1 ◽

2020 ◽

Author(s):

Arthur Souza ◽

Caroline Mota ◽

Amanda Rosa ◽

Ciro Figueiredo ◽

Ana Lucia Candeias

Keyword(s):

Low Income ◽

Public Services ◽

Spatial Regression ◽

Case Fatality ◽

Global Scale ◽

Environmental Data ◽

Data Sets ◽

Spatial Regression Analysis ◽

Effective Drugs ◽

The City

Abstract Background: Given the increasing rates at which cases of people infected by Covid-19 have been evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs and as yet no vaccine. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peak and descending behaviours of the curve of infections.Results: This study highlights the importance of identifying and mapping clusters of the most affected neighbourhoods and their determinant effects. We have identified that it is increasingly common for there to be a phase in which hotspots of confirmed cases appear in a well-developed and heavily densely-populated neighbourhood of the city of Recife. From there, the disease is carried to areas characterised by having a precarious provision of public services and a low-income population and this quickly creates hotspots of case-fatality rates. The results also help to understand the influence of the age, income, level of education of the population and, additionally, of the extent to which they can access public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

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Globalisering in popmuziekhitlijsten in negen landen, 1960-2010

Tijdschrift voor Communicatiewetenschappen ◽

10.5117/2013.041.004.364 ◽

2013 ◽

Vol 41 (4) ◽

Author(s):

Marc Verboord ◽

Amanda Brandellero

Keyword(s):

Population Size ◽

Pop Music ◽

Global Trends ◽

Cultural Globalization ◽

Star Power ◽

Country Level ◽

Cultural Proximity ◽

Level Data ◽

The Us ◽

Media Systems

Going global. Trends in pop music charts 1960-2010 Going global. Trends in pop music charts 1960-2010 This paper studies the cultural globalization of pop music by (a) describing trends in pop music single charts in nine countries in the period 1960-2010, and (b) explaining global success using a double comparative design in which multiple origin groups are observed in multiple destinations. Our explanatory analyses thus comprise country level data (degree of cultural centrality of music industry, cultural proximity, media systems, political context, GDP, population size) and artist level data (language, star power) which affect global flows of pop music. The results show that pop charts are increasingly globalizing, with the exception of the US. Centrality of production in the origin country is highly important, yet after 1990 many European countries also host more domestic music. In addition, we find clear effects of cultural proximity. Artists’ star power as well as the language they perform in also impacts global success.

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Cross-countries comparison of Case Fatality Rates of COVID-19/SARS-COV-2 (Preprint)

10.2196/preprints.18797 ◽

2020 ◽

Author(s):

Fakher Rahim

Keyword(s):

Recovery Rate ◽

Point Of Care ◽

Case Fatality ◽

Current Data ◽

Mortality Weekly Report ◽

Patient Registries ◽

Country Level ◽

Level Data ◽

Control And Prevention ◽

Risk Areas

OBJECTIVE Given the importance of case fertility rate (CFR) and recovery rate (RR), we observed different countries during a COVID-19 ongoing epidemic using recent country-level data. METHODS data were revived from most accurate databases, including Worldometer, WHO, and Center of Disease Control and Prevention (CDC), and the Morbidity and Mortality Weekly Report (MMWR) series provided from CDC, according to the user’s guide of data sources for patient registries. Then we calculated CFR and RR from various countries. RESULTS The comparison of CFR between different countries with total cases equal or more than 1000 were observed. In addition, all countries with less than 1000 cases were given in details. Current data shows Iraq with only 71 cases has the highest CFR as 9.86%, which strikingly are higher than overall CFR of 3.61%. Overall RR was 55.83%. CONCLUSIONS Taking detailed and accurate medical history, and scoring case fatality alongside recovery rate, may show the highest risk areas, to direct the efficient medical care ; thus, this will lead to develop point-of-care tools to help clinicians in stratifying patients based on possible r CLINICALTRIAL None

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An Environmental GIS-based Variable Analysis on SARS-CoV-2 in the City of Recife, Brazil

10.21203/rs.3.rs-95748/v1 ◽

2020 ◽

Author(s):

Arthur Souza ◽

Caroline Maria de Miranda Mota ◽

Amanda Rosa ◽

Ciro Figueiredo ◽

Ana Lucia Candeias

Keyword(s):

Low Income ◽

Public Services ◽

Spatial Regression ◽

Case Fatality ◽

Global Scale ◽

Environmental Data ◽

Data Sets ◽

Spatial Regression Analysis ◽

Effective Drugs ◽

The City

Abstract Background: Given the increasing rates at which people have been infected by Covid-19 evolving to case-fatality rates on a global scale and the context of there being a world-wide socio-economic crisis, decision-making must be undertaken based on prioritizing effective measures to control and combat the disease since there is a lack of effective drugs. Method: This paper explores the determinant factors of the COVID-19 pandemic and its impacts on Recife, Pernambuco-Brazil by performing both local and global spatial regression analysis on two types of environmental data-sets. Data were obtained from ten specific days between late April and early July 2020, comprehending the ascending, peaking and descending behaviours of the curve of infections.Results: This study highlights clusters of the most affected neighbourhoods and their determinant effects. We have observed the increasing phase with hotspots of confirmed cases in a well-developed and heavily densely-populated neighbourhood of Recife city, then evolving for hotspots of case-fatality rates into areas characterised by having a precarious provision of public services and low-income population. The results also help to understand the influence of the age, income, level of education of the population and, additionally, the people’s access to public services, on the behaviour of the virus across neighbourhoods.Conclusion: This study supports government measures against the spread of Covid-19 in heterogeneous cities, evidencing social inequality as a driver for a high incidence of fatal cases of the disease. Understanding the variables which influence the local dynamics of the virus spread becomes vital for identifying the most vulnerable regions for which prevention actions need to be developed.

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APPLICATION OF SPATIAL REGRESSION ANALYSIS ON HUMAN DEVELOPMENT INDEX SUB-NATIONAL DATA

International Journal of Biology Pharmacy and Allied Sciences ◽

10.31032/ijbpas/2020/9.8.4538 ◽

2020 ◽

Vol 9 (8) ◽

Keyword(s):

Regression Analysis ◽

Human Development ◽

Human Development Index ◽

Spatial Regression ◽

National Data ◽

Development Index ◽

Spatial Regression Analysis

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Likelihoods and Simulation Methods for a Class of Nonneutral Population Genetics Models

Genetics ◽

10.1093/genetics/159.2.853 ◽

2001 ◽

Vol 159 (2) ◽

pp. 853-867 ◽

Cited By ~ 2

Author(s):

Peter Donnelly ◽

Magnus Nordborg ◽

Paul Joyce

Keyword(s):

Population Genetics ◽

Population Size ◽

Mutant Allele ◽

Mutation Rates ◽

Simulation Methods ◽

Large Populations ◽

Selection Intensities ◽

Infinite Alleles Model

Abstract Methods for simulating samples and sample statistics, under mutation-selection-drift equilibrium for a class of nonneutral population genetics models, and for evaluating the likelihood surface, in selection and mutation parameters, are developed and applied for observed data. The methods apply to large populations in settings in which selection is weak, in the sense that selection intensities, like mutation rates, are of the order of the inverse of the population size. General diploid selection is allowed, but the approach is currently restricted to models, such as the infinite alleles model and certain K-models, in which the type of a mutant allele does not depend on the type of its progenitor allele. The simulation methods have considerable advantages over available alternatives. No other methods currently seem practicable for approximating likelihood surfaces.

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Financial Access of Latin America and Caribbean Firms: What Are the Roles of Institutional, Financial, and Economic Development?

Journal of Emerging Market Finance ◽

10.1177/09726527211015317 ◽

2021 ◽

pp. 097265272110153

Author(s):

Lan Khanh Chu

Keyword(s):

Economic Development ◽

Latin America ◽

Jel Classification ◽

Caribbean Region ◽

Country Level ◽

Level Data ◽

Latin America And Caribbean ◽

The Impact ◽

Moderating Role

This article examines the impact of institutional, financial, and economic development on firms’ access to finance in Latin America and Caribbean region. Based on firm- and country-level data from the World Bank databases, we employ an ordered logit model to understand the direct and moderating role of institutional, financial, and economic development in determining firms’ financial obstacles. The results show that older, larger, facing less competition and regulation burden, foreign owned, and affiliated firms report lower obstacles to finance. Second, better macro-fundamentals help to lessen the level of obstacles substantially. Third, the role of institutions in promoting firms’ inclusive finance is quite different to the role of financial development and economic growth. JEL classification: E02; G10; O16; P48

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