Determinants of COVID-19 Case and Death Rates: An Ecological Study

Introduction: The Coronavirus Disease 2019 (COVID-19) pandemic has had a variable worldwide impact, likely related to country-level characteristics. In this ecological study, we explored the association of COVID-19 case rates (per 100,000 people) and death rates (per 100,000 people) with country-level population health characteristics, economic and human development indicators, and habitat-related variables. Methods: To calculate country-level COVID-19 case and death rates, the number of cases and deaths were extracted from the Johns Hopkins Coronavirus Resource Center for 2020. Country-level population health characteristics, economic and human development indicators, and habitat-related variables were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Univariate and multivariable linear regression analyses were performed to examine determinants of COVID-19 case rates and death rates. Results: A total of 187 countries and territories were analyzed, with an aggregate COVID-19 case rate of 779 per 100,000 people, a death rate of 19 per 100,000 people, and a case-fatality rate of 2.4%. For country-level population health characteristics, a higher percentage rate of adults with obesity and a higher percentage rate of adults with high blood pressure was independently associated with a higher COVID-19 case rate, and a higher percentage rate of adults with obesity was associated with a higher COVID-19 death rate. For country-level economic and human development indicators, only a higher gross domestic product percentage rate spent on total health expenditure and a higher human development index was independently associated with a higher COVID-19 case rate and death rate. A higher percentage of urban population was independently associated with a higher COVID-19 death rate, whereas a higher income per capita was independently associated with a lower COVID-19 death rate. For country-level habitat-related variables, a higher average household size and a higher percentage rate of population with primary reliance on polluting fuels and technologies was independently associated with a lower COVID-19 case rate and death rate whereas a higher percentage rate of households with at least one-member age 65 years or over was associated with a higher case rate and death rates. Conclusion: This ecological study informs the need to develop country-specific public health interventions to better target populations at high risk for COVID-19, and test environmental interventions to prevent indoor transmission of SARS-CoV-2, taking into consideration population health characteristics, economic and human development indicators, and habitat-related variables that are unique to each country.

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Does Cyberbullying Prevalence Among Adolescents Relate With Country Socioeconomic and Development Indicators? An Ecological Study of 31 Countries

Violence and Victims ◽

10.1891/0886-6708.vv-d-15-00139 ◽

2017 ◽

Vol 32 (5) ◽

pp. 771-790

Author(s):

Sara Soares ◽

Sandra Brochado ◽

Henrique Barros ◽

Sílvia Fraga

Keyword(s):

Ecological Study ◽

Tertiary Education ◽

National Income ◽

Significant Negative Correlation ◽

Individual Characteristics ◽

Development Indicators ◽

Country Level ◽

Cyberbullying Victimization ◽

The World Bank ◽

Internet Users

Background: In addition to individual characteristics, it is also important to evaluate how the environment may influence the dynamics of cyberbullying. We aim to study the correlation between cyberbullying prevalence among adolescents and selected country-level indicators. Methods: We used two different data sources: data from a previously published literature review, to identify information on cyberbullying prevalence across countries, and data from the World Bank databases, to extract information on country-level indicators. A correlation matrix was used to present the association between the selected country-level indicators and the prevalence of cyberbullying. Results: We observed a statistically significant negative correlation between cyberbullying victimization (cybervictims and cyberbully-victims, respectively) and gross domestic product (r = −.474 and −.842), gross national income (r = −.485 and −.758), enrollment in secondary (r = −.446 and −.898) and tertiary education (r = −.222 and −.881), the number of secure Internet servers (r = −.118 and −.794), and the number of Internet users (r = −.190 and −.818). Conclusions: A country’s educational level seems to be an important contributor to the occurrence of cyberbullying.

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Country-level Determinants of the Severity of the First Global Wave of the COVID-19 Pandemic: An Ecological Study

10.1101/2020.05.13.20100677 ◽

2020 ◽

Cited By ~ 1

Author(s):

Tiberiu A Pana ◽

Sohinee Bhattacharya ◽

David T Gamble ◽

Zahra Pasdar ◽

Weronika A Szlachetka ◽

...

Keyword(s):

Mortality Rate ◽

Study Design ◽

Vaccination Coverage ◽

Death Rate ◽

Ecological Study ◽

The Philippines ◽

International Travel ◽

Bcg Vaccination ◽

Country Level ◽

The Mean

ABSTRACTObjectiveWe aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic.DesignAn ecological study design of publicly available data was employed. Countries reporting >25 COVID-related deaths until 08/06/2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, median age, average body mass index, smoking prevalence), Economic parameters (Gross Domestic Product per capita); environmental parameters: pollution levels, mean temperature (January-May)), co-morbidities (prevalence of diabetes, hypertension and cancer), health system parameters (WHO Health Index and hospital beds per 10,000 population); international arrivals, the stringency index, as a measure of country-level response to COVID-19, BCG vaccination coverage, UV radiation exposure and testing capacity. Multivariable linear regression was used to analyse the data.Primary OutcomeCountry-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase.ParticipantsThirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the United Kingdom and the United States.ResultsOf all country-level predictors included in the multivariable model, total number of international arrivals (beta 0.033 (95% Confidence Interval 0.012,0.054)) and BCG vaccination coverage (−0.018 (−0.034,-0.002)), were significantly associated with the mean death rate.ConclusionsInternational travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID outbreak and prevent related deaths.ARTICLE SUMMARYStrengths and limitationsA comparable and relevant outcome variable quantifying country-level increases in the COVID-19 death rate was derived which is largely independent of different testing policies adopted by each countryOur multivariable regression models accounted for public health and economic measures which were adopted by each country in response to the COVID-19 pandemic by adjusting for the Stringency IndexThe main limitation of the study stems from the ecological study design which does not allow for conclusions to be drawn for individual COVID-19 patientsOnly countries that had reported at least 25 daily deaths over the analysed period were included, which reduced our sample and consequently the power.

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Comparing the COVID-19 Responses in Cuba and the United States

American Journal of Public Health ◽

10.2105/ajph.2021.306526 ◽

2021 ◽

Vol 111 (12) ◽

pp. 2186-2193

Author(s):

Mary Anne Powell ◽

Paul C. Erwin ◽

Pedro Mas Bermejo

Keyword(s):

United States ◽

Death Rate ◽

Health Inequities ◽

The United States ◽

Death Rates ◽

Excess Death ◽

Future Studies ◽

Effective Strategies ◽

The Us ◽

Case Rate

The purpose of this analytic essay is to contrast the COVID-19 responses in Cuba and the United States, and to understand the differences in outcomes between the 2 nations. With fundamental differences in health systems structure and organization, as well as in political philosophy and culture, it is not surprising that there are major differences in outcomes. The more coordinated, comprehensive response to COVID-19 in Cuba has resulted in significantly better outcomes compared with the United States. Through July 15, 2021, the US cumulative case rate is more than 4 times higher than Cuba’s, while the death rate and excess death rate are both approximately 12 times higher in the United States. In addition to the large differences in cumulative case and death rates between United States and Cuba, the COVID-19 pandemic has unmasked serious underlying health inequities in the United States. The vaccine rollout presents its own set of challenges for both countries, and future studies can examine the comparative successes to identify effective strategies for distribution and administration. (Am J Public Health. 2021;111(12):2186–2193. https://doi.org/10.2105/AJPH.2021.306526 )

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Differences by country-level income in COVID-19 cases, deaths, case-fatality rates, and rates per million population in the first five months of the pandemic

10.1101/2020.07.13.20153064 ◽

2020 ◽

Cited By ~ 1

Author(s):

Wrishmeen Sabawoon

Keyword(s):

Low Income ◽

Case Fatality Rate ◽

Case Fatality ◽

Incidence Rates ◽

High Income ◽

Fatality Rate ◽

Middle Income ◽

Death Rates ◽

Middle Income Countries ◽

Country Level

Abstract Objective: To describe differences by country-level income in COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates per million population. Methods: Publicly available data on COVID-19 cases and deaths from December 31, 2019 to June 3, 2020 were analyzed. Kruskal-Wallis tests were used to examine associations of country-level income with COVID-19 cases, deaths, case-fatality rates, incidence rates, and death rates. Results: A total of 380,803 deaths out of 6,348,204 COVID-19 cases were reported from 210 countries and territories globally in the period under study, and the global case-fatality rate was 6.0%. Of the total globally reported cases and deaths, the percentages of cases and deaths were 59.9% and 75.0% for high-income countries, and 30.9% and 20.7% for upper-middle-income countries. Countries in higher-income categories had higher incidence rates and death rates. Between April and May, the incidence rates in higher-income groups of countries decreased, but in other groups, it increased. Conclusions In the first five months of the COVID-19 pandemic, most cases and deaths were reported from high-income and upper-middle-income countries, and those countries had higher incidence rates and death rates per million population than did lower-middle and low-income countries. Keywords: COVID-19, incidence rate, death rate, case fatality rate, income, and country

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The Longevity-Frailty Hypothesis: Evidence from COVID-19 Death Rates in Europe

10.1101/2020.04.14.20065540 ◽

2020 ◽

Cited By ~ 1

Author(s):

Sammy Zahran ◽

Levi Altringer ◽

Ashok Prasad

Keyword(s):

Death Rate ◽

Elderly Population ◽

Strong Predictor ◽

Case Fatality ◽

Strong Relationship ◽

The Elderly ◽

System Capacity ◽

Death Rates ◽

Age Related ◽

Population Survival

AbstractCOVID-19 death rates vary strikingly across Europe. The death rate in Spain, for example, is greater than the death rate in Germany by more than a factor of ten. Few if any epidemiological indicators distinguish the countries of Europe by such a vast margin. Evidence on age-specific case-fatality rates (deaths over observed infections) and age-specific death rates (deaths over population) indicate that COVID-19 disproportionately afflicts the elderly and frail, suggesting that the share of elderly population (≥ 65 years of age) in a country ought to be a strong predictor of the COVID-19 death rate. However, the COVID-19 death rate and the share of elderly population are statistically uncorrelated (r = 0.163, p = 0.399). Share of population ≥ 65 years of age is confounded by mortality selection, as well as other demographic dynamics. By contrast, elderly longevity or life expectancy at 65 more effectively captures population survival and the accumulation of age-related frailty in society. We find a strong statistical relationship between the COVID-19 death rate (r = 0.839, p < .001) and elderly longevity, and a moderately strong relationship between the date of epidemic timing and elderly longevity (r = −0.634, p < .001). These relationships are robust to the inclusion of statistical controls for international tourism inflow and hospital bed capacity. While the countries of Europe vary meaningfully in healthcare system capacity and in the timing and intensity of non-pharmaceutical interventions, the striking variation in COVID-19 death rates across these countries is statistically and intuitively associated with elderly survival and consequent frailty.

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Country‐level determinants of COVID‐19 case rates and death rates: An ecological study

Transboundary and Emerging Diseases ◽

10.1111/tbed.14360 ◽

2021 ◽

Author(s):

Christopher El Mouhayyar ◽

Luke T. Jaber ◽

Matthias Bergmann ◽

Hocine Tighiouart ◽

Bertrand L. Jaber

Keyword(s):

Ecological Study ◽

Death Rates ◽

Country Level

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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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Identifying High-Potential Work Areas in Engineering for Global Development: Linking Industry Sectors to the Human Development Index

Journal of Mechanical Design ◽

10.1115/1.4048746 ◽

2020 ◽

Vol 143 (6) ◽

Author(s):

Daniel O. Smith ◽

Christopher A. Mattson ◽

Eric C. Dahlin

Keyword(s):

Developing Countries ◽

Human Development ◽

Human Development Index ◽

Three Dimensions ◽

Global Development ◽

Development Index ◽

Development Indicators ◽

Work Related ◽

Country Level ◽

Development State

Abstract Those working in Engineering for Global Development seek to improve the conditions in developing countries. A common metric for understanding the development state of a given country is the Human Development Index (HDI), which focuses on three dimensions: health, education, and income. An engineer’s expertise does not always align with any of those dimensions directly, while they still hope to perform impactful work for human development. To discover other areas of expertise that are highly associated with the HDI, correlations and variable selection were performed between all World Development Indicators and the HDI. The resultant associations are presented according to industry sector for a straightforward connection to engineering expertise. The associated areas of expertise can be used during opportunity development as surrogates for focusing on the HDI dimensions themselves. The data analysis shows that work related to “Trade, Transportation, and Utilities,” such as electricity distribution, and exports or imports, “Natural Resources and Mining,” such as energy resources, agriculture, or access to clean water, and “Manufacturing,” in general, are most commonly associated with improvements in the HDI in developing countries. Also, because the associations were discovered at country-level, they direct where geographically particular areas of expertise have been historically associated with improving HDI.

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Identifying High-Potential Work Areas in Engineering for Global Development: Linking Industry Sectors to the Human Development Index

Volume 11B: 46th Design Automation Conference (DAC) ◽

10.1115/detc2020-22063 ◽

2020 ◽

Author(s):

Daniel O. Smith ◽

Christopher A. Mattson ◽

Eric C. Dahlin

Keyword(s):

Human Development ◽

Human Development Index ◽

Three Dimensions ◽

Global Development ◽

Development Index ◽

Development Indicators ◽

Work Related ◽

Country Level ◽

Development State ◽

Industry Sectors

Abstract Those working in Engineering for Global Development seek to improve the conditions in under-served regions. A common metric for understanding the development state of a given country is the Human Development Index (HDI), which focuses on three dimensions: health, education, and income. An engineer’s expertise does not always align with any of those dimensions directly, while they still hope to perform impactful work for human development. To discover other areas of expertise that are highly associated with the HDI, correlations and variable selection were performed between all World Development Indicators and the HDI. The resultant associations are presented according to industry sector for a straightforward connection to engineering expertise, such that they can be used during opportunity development where associated areas of expertise act as surrogates for focusing on the HDI dimensions themselves. The data analysis shows that work related to “Trade, Transportation, and Utilities”, such as merchandise exports and imports and electricity distribution, and “Manufacturing”, especially electronics manufacturing and employment in manufacturing are insightful associations with improvements in the HDI in developing countries. Also, because the associations were discovered at country-level, they geographically direct where particular areas of expertise have been historically associated with improving HDI.

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The impact of climate temperature on counts, recovery, and death rates due to SARS-CoV-2 in South Africa. (Preprint)

10.2196/preprints.22816 ◽

2020 ◽

Author(s):

Neven Chetty ◽

Bamise Adeleye ◽

Abiola Olawale Ilori

Keyword(s):

South Africa ◽

South African ◽

Death Rate ◽

Western Cape ◽

Warm Climate ◽

The South ◽

Recovery Rates ◽

Death Rates ◽

Online Resource ◽

The Impact

BACKGROUND The impact of climate temperature on the counts (number of positive COVID-19 cases reported), recovery, and death rates of COVID-19 cases in South Africa's nine provinces was investigated. The data for confirmed cases of COVID-19 were collected for March 25 and June 30, 2020 (14 weeks) from South Africa's Government COVID-19 online resource, while the daily provincial climate temperatures were collected from the website of the South African Weather Service. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that no particular temperature range is closely associated with a faster or slower death rate of COVID-19 patients. As evidence from our study, a warm climate temperature can only increase the recovery rate of COVID-19 patients, ultimately impacting the death and active case rates and freeing up resources quicker to enable health facilities to deal with those patients' climbing rates who need treatment. OBJECTIVE This study aims to investigate the impact of climate temperature variation on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperature values. METHODS The data for confirmed cases of COVID-19 were collected for March 25 and June 30 (14 weeks) for South African provinces, including daily counts, death, and recovery rates. The dates were grouped into two, wherein weeks 1-5 represent the periods of total lockdown to contain the spread of COVID-19 in South Africa. Weeks 6-14 are periods where the lockdown was eased to various levels 4 and 3. The daily information of COVID-19 count, death, and recovery was obtained from South Africa's Government COVID-19 online resource (https://sacoronavirus.co.za). Daily provincial climate temperatures were collected from the website of the South African Weather Service (https://www.weathersa.co.za). The provinces of South Africa are Eastern Cape, Western Cape, Northern Cape, Limpopo, Northwest, Mpumalanga, Free State, KwaZulu-Natal, Western Cape, and Gauteng. Weekly consideration was given to the daily climate temperature (average minimum and maximum). The recorded values were considered, respectively, to be in the ratio of death-to-count (D/C) and recovery-to-count (R/C). Descriptive statistics were performed for all the data collected for this study. The analyses were performed using the Person’s bivariate correlation to analyze the association between climate temperature, death-to-count, and recovery-to-count ratios of COVID-19. RESULTS The results showed that higher climate temperatures aren't essential to avoid the COVID-19 from being spread. The present results conform to the reports that suggested that COVID-19 is unlike the seasonal flu, which does dissipate as the climate temperature rises [17]. Accordingly, the ratio of counts and death-to-count cannot be concluded to be influenced by variations in the climate temperatures within the study areas. CONCLUSIONS The study investigates the impact of climate temperature on the counts, recovery, and death rates of COVID-19 cases in all South Africa's provinces. The findings were compared with those of countries with comparable climate temperatures as South Africa. Our result indicates that a higher or lower climate temperature does not prevent or delay the spread and death rates but shows significant positive impacts on the recovery rates of COVID-19 patients. Warm climate temperatures seem not to restrict the spread of the COVID-19 as the count rate was substantial at every climate temperatures. Thus, it indicates that the climate temperature is unlikely to impose a strict limit on the spread of COVID-19. There is no correlation between the cases and death rates, an indicator that there is no particular temperature range of the climatic conditions closely associated with a faster or slower death rate of COVID-19 patients. However, other shortcomings in this study's process should not be ignored. Some other factors may have contributed to recovery rates, such as the South African government's timely intervention to announce a national lockout at the early stage of the outbreak, the availability of intensive medical care, and social distancing effects. Nevertheless, this study shows that a warm climate temperature can only help COVID-19 patients recover more quickly, thereby having huge impacts on the death and active case rates.

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