Estimation of fatality rate in Africa through the behavior of COVID-19 in Italy relevance to age profiles (original) (raw)
Related papers
Dynamics of factors associated with rates of COVID-19 cases and deaths in African countries
Globalization and Health
Background African countries have not had the high case and death rates from COVID-19 as was predicted early in the pandemic. It is not well understood what factors modulated the rate of COVID-19 cases and death on the continent. Methods We collated data from the World Bank data site, Our World in Data and Freedom House for African for 54 African countries who are members of the African Union. We used them as explanatory variables in two general linear model regression analyses. COVID cases and deaths per 100,000 obtained from WHO COVID-19 dashboard on August 12, 2021, as outcome variables in two prediction models. Results GDP, percentage of population under 14 years of age, Maternal Mortality Ratio, number of international tourists visiting per year and public transportation closures were not significant in predicting COVID-19 cases. Higher percentage of unemployed adults in the population, lower percentage of the population over 25 years of age with secondary education, internal t...
2021
The SARS-CoV-2 infection, which causes the COVID-19 disease, has impacted every nation on the globe, albeit disproportionately. African countries have seen lower infection and mortality rates than most countries in the Americas Europe and Asia. In this commentary, we explore some of the factors purported to be responsible for the low COVID-19 infection and case fatality rates in Africa: low testing rate, poor documentation of cause of death, younger age population, good vitamin D status as a result of exposure to sunlight, cross-immunity from other viruses including coronaviruses, and lessons learnt from other infectious diseases such as HIV and Ebola. With the advent of a new variant of COVID-19 and inadequate roll-out of vaccines, an innovative and efficient response is needed to ramp up testing, contact tracing and accurate reporting of infection rates and cause of death in order to mitigate the spread of the infection.
Epidemiology and infection, 2021
This study analysed the reported incidence of COVID-19 and associated epidemiological and socioeconomic factors in the WHO African region. Data from COVID-19 confirmed cases and SARS-CoV-2 tests reported to the WHO by Member States between 25 February and 31 December 2020 and publicly available health and socioeconomic data were analysed using univariate and multivariate binomial regression models. The overall cumulative incidence was 1846 cases per million population. Cape Verde (21 350 per million), South Africa (18 060 per million), Namibia (9840 per million), Eswatini (8151 per million) and Botswana (6044 per million) recorded the highest cumulative incidence, while Benin (260 per million), Democratic Republic of Congo (203 per million), Niger (141 cases per million), Chad (133 per million) and Burundi (62 per million) recorded the lowest. Increasing percentage of urban population (β = −0.011, P = 0.04) was associated with low cumulative incidence, while increasing number of cumulative SARS-CoV-2 tests performed per 10 000 population (β = 0.0006, P = 0.006) and the proportion of population aged 15-64 years (adjusted β = 0.174, P < 0.0001) were associated with high COVID-19 cumulative incidence. With limited testing capacities and overwhelmed health systems, these findings highlight the need for countries to increase and decentralise testing capacities and adjust testing strategies to target most at-risk populations.
Estimates of the COVID-19 Infection Fatality Rate for 48 African Countries: A Model-based Analysis
2020
Introduction: The infection fatality rate (IFR) is key to determining the effect of the pandemic at population level, as well as the effects of public policies and regulations. We examine global data from 48 African countries to estimate the SARS-CoV-2 IFR. Methods: We analyzed time series data on the confirmed cases and deaths from COVID-19 disease outbreak across Africa. We define IFR as the ratio of the number of deaths caused by COVID-19 (numerator) and the total number of people in the population who were infected by the virus (denominator). We controlled for the upward bias associated with the denominator, to accommodate for the untested individuals by adjusting for population density, population aged 65 years and older, population with basic handwashing facilities, extreme poverty, diabetes prevalence, and death rate from cardiovascular disease in a Bayesian prediction model based on the technique of Monte Carlo. Results: We analyzed data on the 135,126 confirmed cases and 3,...
Background: The epidemiology of COVID-19 remains speculative in Africa. To the best of our knowledge, no study, using robust methodology provides its trajectory for the region or accounts for the local context. This paper is the first systematic attempt to provide prevalence, incidence, and mortality estimates across Africa. Methods: Caseloads and incidence forecasts are from a co-variate-based instrumental variable regression model. Fatality rates from Italy and China were applied to generate mortality estimates after making relevant health system and population-level characteristics related adjustments between each of the African countries. Results: By June 30 2020, around 16.3 million people in Africa will contract COVID-19 (95% CI 718,403 to 98,358,799). Northern and Eastern Africa will be the most and least affected areas. Cumulative cases by June 30 are expected to reach around 2.9 million (95% CI 465,028 to 18,286,358) in Southern Africa, 2.8 million (95% CI 517,489 to 15,056...
COVID-19 Cases and Case Fatality Rate by age
2020
The report provides a comparison of cases and fatalities of COVID-19 by age and by provinces and regions in some of the most affected countries. The main objective of the comparison is to evaluate possible effects of the demographic characteristics of population on the epidemic outcomes. The analysis is preliminary since it is based on constantly evolving data while the COVID-19 pandemic is still unfolding. Age distributions are presented by large age classes and using estimated values for harmonised 5-year age groups. In addition to Case Fatality Rates, we calculate three main indicators: Synthetic CFR, Relative Illness Ratio and Relative Mortality Ratio. Finally, we examine the relation between the geographical patterns of cases and fatalities and the demographic profiles of the population. The distribution of both cases and fatalities across ages shows several anomalies. However our findings seem to exclude the fact that an older population alone may justify the high number of fa...
The first year of the COVID-19 pandemic in the ECOWAS region
Ghana Medical Journal
Objective: to analyse the pandemic after one year in terms of the evolution of morbidity and mortality and factors that may contribute to this evolutionDesign: This is a secondary analysis of data gathered to respond to the COVID-19 pandemic. The number of cases, incidence rate, cumulative incidence rate, number of deaths, case fatality rate and their trends were analysed during the first year of the pandemic. Testing and other public health measures were also described according to the information available.Settings: The 15 States members of the Economic Community of West African States (ECOWAS) were considered.Results: As of 31st March 2021, the ECOWAS region reported 429,760 COVID-19 cases and 5,620 deaths. In the first year, 1,110.75 persons were infected per million, while 1.31% of the confirmed patients died. The ECOWAS region represents 30% of the African population. One year after the start of COVID-19 in ECOWAS, this region reported 10% of the cases and 10% of the deaths in...
Background: COVID-19, the disease associated with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is currently a global pandemic with several thousands of confirmed cases of infection and death. However, the death rate across affected countries shows variation deserving of critical evaluation. Methods: In this study, we evaluated differentials in COVID-19 confirmed cases of infection and associated deaths of selected countries in Sub-Sahara Africa (Nigeria and Ghana), South Africa, Europe (Italy, Spain, Sweden and UK) and USA. Data acquired for various standard databases on mutational shift of the SARS-CoV-2 virus based on geographical location, BCG vaccination policy, malaria endemicity, climatic conditions (temperature), differential healthcare approaches were evaluated over a period of 45 days from the date of reporting the index case. Results: The number of confirmed cases of infection and associated deaths in Sub-Sahara Africa were found to be very low compared...
Lancet, 2024
Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic.
Exploring Statistical Signifance of COVID-19 Data in Africa
International Journal of Statistics and Applied Mathematics 2020; 5(4): 34-42, 2020
It has been cited by different researchers that COVID-19 infections in Africa is insignificant. This paper delves into the regional data to scrutinize the statistical significance of COVID-19 in Africa. The data of all regions, according to World Health Organization (WHO) classification, is compared to that of Africa. The paper explores COVID-19 infections data including cases, case fatality, case fatality rates, case recovery, and case recovery rates. These are compared to COVID-19 status in Africa on May 9, 2020. First, the COVID-19 regional data is taken through logarithmic transformation, normality tests and One-way ANOVA analysis of mean infections, case fatality, case fatality rates, recoveries, and case recovery rates. Then Tukey post hoc method is used to identify which regions exhibit statistical difference in, cases, case fatality, case fatality rates, recoveries, and case recovery rates. Estimation of linear models of various parameters with regions as factor is done. The residuals of the linear models are tested for normality using Q-Qplots, residual-fitted plots, and histograms. Lastly, 95% family-wise confidence level of regional mean differences in COVIFD-19 infections and resultant effects are estimated and plotted. In this paper selected countries in the East, West, and mid- west Mediterranean, and Oceania regions are referred to as OCEA. In the statistical analysis the regions are denoted as Americas (AMER), Europe (EURO), Africa (AFRO), and OCEA. Results indicate that the mean COVID-19 infection cases in Africa are significantly different from Americas, Europe, and OCEA at 95% confidence level. Also, the mean COVID-19 case fatality in Africa is significantly different from Europe and Americas but not OCEA. In addition, mean COVID-19 case fatality rate in Africa is not statistically different from Americas, Europe, and OCEA at 95% confidence level. Further, the mean COVID-19 case recoveries in Africa is significantly different from Europe and OCEA but not Americas at 95% confidence level. Interestingly, all regional case recovery rates are not significantly different from each other at 95% confidence level.