The significance of daily incidence and mortality cases due to COVID-19 in some African countries

Makinde, Olusola Samuel; Oseni, Bamidele Mustapha; Adepetun, Akinola Oladiran; Olusola-Makinde, Olubukola; Abiodun, Gbenga J.

doi:10.1016/b978-0-323-90769-9.00013-x

Cited by 3 publications

(3 citation statements)

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“…The length of the data series used for each method was also based on that generally used by researchers using these approaches. Recently published papers on the topic have, in fact, quantified excess deaths by estimating expected mortality in 2020 by using a simple average of the previous years as a reference [7-9] or more sophisticated approaches, including average standardized mortality rates [10,11], the SARIMA [12] and GEE models [13,14], as well as other methodologies [21][22][23][24][25][26]. COVID-19 has affected mortality in different aspects and at different times, thus disentangling this effect from the distortion introduced by the application of different methods can be complex [2].…”

Section: Discussionmentioning

confidence: 99%

“…In this article, we will compare four different approaches to estimate excess mortality among those most commonly applied in recent literature. These comprise: the use of a simple monthly average of the preceding years as reference (1) [7][8][9]; more sophisticated approaches, based on average-standardized mortality rates (2) [10,11]; models that forecast values based on previous trends and seasonality (Seasonal Autoregressive Integrated Moving Average-SARIMA) (3) [12]; or other models, where further variables can be implemented (Generalized Estimating Equations-GEE models) (4) [13,14]. Given the relevance of correctly quantifying the COVID-19 mortality burden, the importance of accurately assessing the impact of public health policies, and the benefits of mass vaccination on mortality reduction, awareness of the effects of the methodological differences on excess mortality estimates is of crucial importance, along with the promotion of a methodological gold standard.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

Amidei

Fedeli

Gennaro

et al. 2023

IJERPH

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During the COVID-19 pandemic, excess mortality has been reported worldwide, but its magnitude has varied depending on methodological differences that hinder between-study comparability. Our aim was to estimate variability attributable to different methods, focusing on specific causes of death with different pre-pandemic trends. Monthly mortality figures observed in 2020 in the Veneto Region (Italy) were compared with those forecasted using: (1) 2018–2019 monthly average number of deaths; (2) 2015–2019 monthly average age-standardized mortality rates; (3) Seasonal Autoregressive Integrated Moving Average (SARIMA) models; (4) Generalized Estimating Equations (GEE) models. We analyzed deaths due to all-causes, circulatory diseases, cancer, and neurologic/mental disorders. Excess all-cause mortality estimates in 2020 across the four approaches were: +17.2% (2018–2019 average number of deaths), +9.5% (five-year average age-standardized rates), +15.2% (SARIMA), and +15.7% (GEE). For circulatory diseases (strong pre-pandemic decreasing trend), estimates were +7.1%, −4.4%, +8.4%, and +7.2%, respectively. Cancer mortality showed no relevant variations (ranging from −1.6% to −0.1%), except for the simple comparison of age-standardized mortality rates (−5.5%). The neurologic/mental disorders (with a pre-pandemic growing trend) estimated excess corresponded to +4.0%/+5.1% based on the first two approaches, while no major change could be detected based on the SARIMA and GEE models (−1.3%/+0.3%). The magnitude of excess mortality varied largely based on the methods applied to forecast mortality figures. The comparison with average age-standardized mortality rates in the previous five years diverged from the other approaches due to the lack of control over pre-existing trends. Differences across other methods were more limited, with GEE models probably representing the most versatile option.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

Amidei

Fedeli

Gennaro

et al. 2023

IJERPH

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“…It was reported on 4 January 2022 that COVID-19 has infected up to two hundred and eighty-one million eight hundred and eight thousand two hundred and seventy (281, 808, 270) persons globally with five million, four hundred and eleven thousand seven hundred and fifty-nine (5,411,759) deaths recorded. In Africa, seven million, one hundred and sixty-four thousand four hundred and eighty-five (7,164,485) infections were recorded while one hundred and fifty-five thousand six hundred and seventy-five (155,675) deaths mortalities were recorded ( Makinde et al, 2022 ). Despite the lowest number of COVID-19 confirmed cases in Africa, Africa has a long history of severe and re-emerging infectious disease upsurges such as malaria and ebola ( Fenollar and Mediannikov, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Ganoderma lucidum: Unutilized natural medicine and promising future solution to emerging diseases in Africa

et al. 2022

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Ganoderma lucidum is a well-known medicinal mushroom that has been used for the prevention and treatment of different ailments to enhance longevity and health specifically in China, Japan, and Korea. It was known as “God’s herb” in ancient China as it was believed to prolong life, enhance the youthful spirit and sustain/preserve vitality. G. lucidum is seldom collected from nature and is substantially cultivated on wood logs and sawdust in plastic bags or bottles to meet the international market demand. Both in vitro and in vivo studies on the copious metabolic activities of G. lucidum have been carried out. Varied groups of chemical compounds including triterpenoids, polysaccharides, proteins, amino acids, nucleosides, alkaloids, steroids, lactones, lectins, fatty acids, and enzymes with potent pharmacological activities have been isolated from the mycelia and fruiting bodies of G. lucidum. Several researchers have reported the abundance and diversification of its biological actions triggered by these chemical compounds. Triterpenoids and polysaccharides of G. lucidum have been reported to possess cytotoxic, hepatoprotective, antihypertensive, hypocholesterolemic, antihistaminic effects, antioxidant, antimicrobial, anti-inflammatory, hypoglycemic antiallergic, neuroprotective, antitumor, immunomodulatory and antiangiogenic activities. Various formulations have been developed, patented, and utilized as nutraceuticals, cosmeceuticals, and pharmaceuticals from G. lucidum extracts and active compounds. Thus, this review presents current updates on emerging infectious diseases and highlights the scope, dynamics, and advances in infectious disease management with a particular focus on Ganoderma lucidum, an unutilized natural medicine as a promising future solution to emerging diseases in Africa. However, details such as the chemical compound and mode of action of each bioactive against different emerging diseases were not discussed in this study.

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Modeling the Impact of Air Pollution and Meteorological Variables on COVID-19 Transmission in Western Cape, South Africa

Mutinda,

Langat

2024

International Journal of Mathematics and Mathematical Sciences

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Understanding the factors that influence COVID-19 transmission is essential in assessing and mitigating the spread of the pandemic. This study focuses on modeling the impact of air pollution and meteorological parameters on the risk of COVID-19 transmission in Western Cape Province, South Africa. The data used in this study consist of air pollution parameters, meteorological variables, and COVID-19 incidence observed for 262 days from April 26, 2020, to January 12, 2021. Lagged data were prepared for modeling based on a 6-day incubation period for COVID-19 disease. Based on the overdispersion property of the incidence, negative binomial (NB) and generalised Poisson (GP) regression models were fitted. Stepwise regression was used to select the significant predictors in both models based on the Akaike information criterion (AIC). The residuals of both NB and GB regression models were autocorrelated. An autoregressive integrated moving average (ARIMA) model was fitted to the residuals of both models. ARIMA (7, 1, 5) was fitted to the residuals of the NB model while ARIMA (1, 1, 6) was fitted for the residuals of the GP model. NB + ARIMA (7, 1, 5) and GP + ARIMA (1, 1, 6) models were tested for performance using root mean square error (RSME). GP + ARIMA (1, 1, 6) was selected as the optimal model. The results from the optimal model suggest that minimum temperature, ambient relative humidity, ambient wind speed, PM2.5, and NO2 at various lags are positively associated with COVID-19 incidence while maximum relative humidity, minimum relative humidity, solar radiation, maximum temperature, NO, PM load, PM10, SO2, and NOX at various lags have a negative association with COVID-19 incidence. Ambient wind direction and temperature showed a nonsignificant association with COVID-19 at all lags. This study suggests that meteorological and pollution parameters play a vital independent role in the transmission of the SARS-CoV-2 virus.

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The significance of daily incidence and mortality cases due to COVID-19 in some African countries

Cited by 3 publications

References 25 publications

Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

Estimating Overall and Cause-Specific Excess Mortality during the COVID-19 Pandemic: Methodological Approaches Compared

Ganoderma lucidum: Unutilized natural medicine and promising future solution to emerging diseases in Africa

Modeling the Impact of Air Pollution and Meteorological Variables on COVID-19 Transmission in Western Cape, South Africa

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