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The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis

ABSTRACT: Background: More than 1 year after the beginning of the international spread of coronavirus 2019 (COVID-19), the reasons explaining its apparently lower reported burden in Africa are still to be fully elucidated. Few studies previously investigated the potential reasons explaining this epidemiological observation using data at the level of a few African countries. However, an updated analysis considering the various epidemiological waves and variables across an array of categories, with a focus on African countries might help to better understand the COVID-19 pandemic on the continent. Thus, we investigated the potential reasons for the persistently lower transmission and mortality rates of COVID-19 in Africa. Methods: Data were collected from publicly available and well-known online sources. The cumulative numbers of COVID-19 cases and deaths per 1 million population reported by the African countries up to February 2021 were used to estimate the transmission and mortality rates of COVID-19, respectively. The covariates were collected across several data sources: clinical/diseases data, health system performance, demographic parameters, economic indicators, climatic, pollution, and radiation variables, and use of social media. The collinearities were corrected using variance inflation factor (VIF) and selected variables were fitted to a multiple regression model using the R statistical package. Results: Our model (adjusted R-squared: 0.7) found that the number of COVID-19 tests per 1 million population, GINI index, global health security (GHS) index, and mean body mass index (BMI) were significantly associated (P < 0.05) with COVID-19 cases per 1 million population. No association was found between the median life expectancy, the proportion of the rural population, and Bacillus Calmette–Guérin (BCG) coverage rate. On the other hand, diabetes prevalence, number of nurses, and GHS index were found to be significantly associated with COVID-19 deaths per 1 million population (adjusted R-squared of 0.5). Moreover, the median life expectancy and lower respiratory infections rate showed a trend towards significance. No association was found with the BCG coverage or communicable disease burden. Conclusions: Low health system capacity, together with some clinical and socio-economic factors were the predictors of the reported burden of COVID-19 in Africa. Our results emphasize the need for Africa to strengthen its overall health system capacity to efficiently detect and respond to public health crises.

SUBMITTER: Bouba Y

PROVIDER: S-EPMC8568130 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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. 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 through September 30, 2021. Country-level population health characteristics, economic, human development, and habitat-related indicators were extracted from several publicly available online sources of international organizations. Results were tabulated according to world zones and country economies. Unadjusted and adjusted multiple imputation linear regression analyses were performed to examine the association between country-level variables (per 1-standard deviation [SD] increase) and COVID-19 case and death rates. To satisfy the linear regression model assumptions of normality of residuals, we used the square root transformation of both outcomes. A total of 187 countries and territories were analyzed, with a median (25th, 75th percentiles) aggregate COVID-19 case rate of 3,605 (463, 8,228) per 100,000, a COVID-19 death rate of 45.9 (8.9, 137.1) per 100,000, and a case-fatality rate of 1.6% (1.2%, 2.6%). On multivariable analyses, each country-level 1-SD higher percentage of adults with obesity (β coefficient 13.7; 95% confidence interval [CI] 13.7; 8.9, 18.4), percentage of smokers (5.8; 95% CI 1.2, 10.5), percentage of adults with high blood pressure (4.9; 95% CI 0.3, 9.6), and gross national income (GNI) per capita (9.5; 95% CI 4.6, 14.5) was independently associated with higher square root of COVID-19 case rate, while average household size (-1.7; 95% CI -12.3, -3.2) was independently associated with lower square root of COVID-19 case rate. Similarly, each 1-SD higher percentage of adults with obesity (1.76; 95% CI 0.99, 2.52), percentage of adults with high blood pressure (1.11; 95% CI 0.48, 1.74), percentage of adults with physical inactivity (1.01; 95% CI 0.10, 1.191), and travel & tourism competitiveness index (1.05; 95% CI 0.06, 2.04) was independently associated with higher square root of COVID-19 death rate, whereas GNI per capita (-0.92; 95% CI -1.81, -0.03), and average household size (-1.07; 95% CI -1.87, -0.27) was independently associated with lower square root of COVID-19 death rate. 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 interventions to prevent transmission of SARS-CoV-2, taking into consideration cross-country differences in population health characteristics, and economic, human development and habitat-related factors.

Project description:Background and aimsClinical characteristics and factors associated with mortality in patients admitted to the intensive care unit (ICU) in countries with low case fatality rates (CFR) are unknown. We sought to determine these in a large cohort of critically ill COVID-19 patients in Qatar and explore the early mortality predictors.MethodsWe retrospectively studied the clinical characteristics and outcomes in patients admitted to the ICU at the national referral hospital for COVID-19 patients in Qatar. Logistic regression analysis was used to determine factors associated with mortality.ResultsBetween March 7 and July 16, 2020, a total of 1079 patients with COVID-19 were admitted to the ICU. The median (IQR) age of patients was 50 (41-59) years. Diabetes (47.3%) and hypertension (42.6%) were the most common comorbidities. In-hospital mortality was 12.6% overall and 25.9% among those requiring mechanical ventilation. Factors independently associated with mortality included older age ([OR]; 2.3 [95% CI; 1.92-2.75] for each 10-year increase in age, p < 0.001), chronic kidney disease (OR; 1.9 [95% CI; 1.02-3.54], p = 0.04), active malignancy (OR; 6.15 [95% CI; 1.79-21.12], p = 0.004), lower platelet count at ICU admission (OR; 1.41 [95% CI; 1.13-1.75] for each 100 × 103/µl decrease, p = 0.002), higher neutrophil-to-lymphocyte ratio at admission (OR; 1.01 [95% CI; 1-1.02] for each 1- point increase, p = 0.016), higher serum ferritin level at admission (OR; 1.05 [(95% CI; 1.02-1.08] for each 500 µg/L increase, p = 0.002), and higher serum bilirubin level at admission (OR; 1.19 [95% CI; 1.04-1.36] for each 10 μmol/L increase, p = 0.01).ConclusionsThe mortality rate among critically ill COVID-19 patients is low in Qatar compared to other countries. Older age, chronic kidney disease, active malignancy, higher neutrophil-to-lymphocyte ratios, lower platelet counts, higher serum ferritin levels, and higher serum bilirubin levels are independent predictors of in-hospital mortality.

Project description:BackgroundMultiple COVID-19 vaccines have now been licensed for human use, with other candidate vaccines in different stages of development. Effective and safe vaccines against COVID-19 have been essential in achieving global reductions in severe disease caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), but multiple factors, including vaccine supply and vaccine confidence, continue to impact global uptake of COVID-19 vaccines. In this study, we explore determinants of COVID-19 vaccination intent across17 countries worldwide.MethodsIn this large-scale multi-country study, we explored intent to accept a COVID-19 vaccine and the socio-demographic and emotional determinants of uptake for 17 countries and over 19,000 individuals surveyed in June and July 2020 via nationally representative samples. We used Bayesian ordinal logistic regressions to probe the relationship between intent to accept a COVID-19 vaccine and individuals' socio-demographic status, their confidence in COVID-19 vaccines, and their recent emotional status. Gibbs sampling was used for Bayesian model inference, with 95% Bayesian highest posterior density intervals used to capture uncertainty.FindingsIntent to accept a COVID-19 vaccine was found to be highest in India, where 77⋅8% (95% HPD, 75⋅5 to 80⋅0%) of respondents strongly agreeing that they would take a new COVID-19 vaccine if it were available. The Democratic Republic of Congo (15⋅5%, 12⋅2 to 18⋅6%) and France (26⋅4%, 23⋅7 to 29⋅2%) had the lowest share of respondents who strongly agreed that they would accept a COVID-19. Confidence in the safety, importance, and effectiveness of COVID-19 vaccines are the most widely informative determinants of vaccination intent. Socio-demographic and emotional determinants played a lesser role, with being male and having higher education associated with increased uptake intent in five countries and being fearful of catching COVID-19 also a strong determinant of uptake intent.InterpretationBarriers to COVID-19 vaccine acceptance are found to be country and context dependent. These findings highlight the importance of regular monitoring of COVID-19 vaccine confidence to identify groups less likely to vaccinate.

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The Determinants of the Low COVID-19 Transmission and Mortality Rates in Africa: A Cross-Country Analysis

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