Estimates of the COVID-19 Infection Fatality Rate for 48 African Countries: A Model-Based Analysis (original) (raw)
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Dynamics of factors associated with rates of COVID-19 cases and deaths in African countries
Globalization and Health
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Frontiers in Public Health, 2021
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 C...
The Lancet Global Health
Background COVID-19 has affected the African region in many ways. We aimed to generate robust information on the transmission dynamics of COVID-19 in this region since the beginning of the pandemic and throughout 2022. Methods For each of the 47 countries of the WHO African region, we consolidated COVID-19 data from reported infections and deaths (from WHO statistics); published literature on socioecological, biophysical, and public health interventions; and immunity status and variants of concern, to build a dynamic and comprehensive picture of COVID-19 burden. The model is consolidated through a partially observed Markov decision process, with a Fourier series to produce observed patterns over time based on the SEIRD (denoting susceptible, exposed, infected, recovered, and dead) modelling framework. The model was set up to run weekly, by country, from the date the first infection was reported in each country until Dec 31, 2021. New variants were introduced into the model based on sequenced data reported by countries. The models were then extrapolated until the end of 2022 and included three scenarios based on possible new variants with varying transmissibility, severity, or immunogenicity.
A study of COVID-19 data from African countries
arXiv: Populations and Evolution, 2020
COVID-19 is a new pandemic disease that is affecting almost every country with a negative impact on social life and economic activities. The number of infected and deceased patients continues to increase globally. Mathematical models can help in developing better strategies to contain a pandemic. Considering multiple measures taken by African governments and challenging socio-economic factors, simple models cannot fit the data. We studied the dynamical evolution of COVID-19 in selected African countries. We derived a time-dependent reproduction number for each country studied to offer further insights into the spread of COVID-19 in Africa.
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...
Assessing the Accuracy of Early COVID-19 Case and Fatality Model Projections in Africa
Research Square (Research Square), 2022
Objective We compared reported COVID-19 case, fatality, and peak date data for Africa Union (AU) member states with estimates and projections produced by various mathematical models to assess their accuracy in the context of an ongoing pandemic and identify key gaps to improve the utility of models in the future. Methods We conducted a systematic literature review to identify studies published in any language between January and December 2020 that reported results of COVID-19 modeling analyses for any AU member state. Reported COVID-19 case, fatality, peak date, and testing rate data were obtained. Descriptive, bivariate, and meta-analyses were conducted to compare reported data to model-generated estimates. Findings For included countries in the respective model simulation periods, model-predicted cumulative cases ranged from 2 to 76,213,155 while model-predicted cumulative deaths ranged from 8 to 700,000. The difference between reported and predicted cumulative COVID-19 cases was between-99.3 % to 1.44×10 6 % with most values being above 24.7%, and the difference between reported and predicted cumulative COVID-19 deaths for models reviewed was between-2.0 % to 2.73×10 5 % with most values being above 50.0%. The difference in the predicted and reported dates for the rst epidemic wave peak was between-242 Days to 249 Days. Conclusion For the rst COVID-19 epidemic wave, epidemiological model results were observed to have high precision but low accuracy when compared to reported peak case date and cumulative cases and deaths indicating that these data were either under-reported or model-overestimated.
International Journal of Infectious Diseases, 2021
To date, SARS-CoV-2 (the virus that causes COVID-19) has spread to almost every region of the world, infecting millions and resulting in the deaths of hundreds of thousands of people. Although it was predicted that Africa would suffer a massive loss of life due to this pandemic, the number of COVID-19 cases has been relatively low across the continent. Researchers have speculated that several factors may be responsible for this outcome in Africa, including the extensive experience that countries have with infectious diseases and the young median age of their populations. However, it is still important for African countries to adopt aggressive and bold approaches against COVID-19, in case the nature of the pandemic changes. This short review will summarize the status of the outbreak in Africa and propose possible reasons for current trends, as well as discuss interventions aimed at preventing a rapid increase in the number of COVID-19 cases in the future.
Epidemiology of COVID-19 in Africa - daily cumulative index and mortality rate
International Journal of Infection Control
COVID-19 outbreak which originated from Wuhan, a city in China has spread to over 180 countries in the world, disrupting several sectors of the human life, and causing deaths. This unprecedented event has affected 55 countries in Africa in different ways. This study aims to outline the current epidemiological data of COVID-19 in Africa. The number of confirmed cases and deaths in Africa was obtained from COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Mortality rate and daily cumulative index were calculated for each country. The mortality rate in Africa is low compared to other Continents regardless of the high Daily Cumulative Index recorded.
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.
The Conundrum of Low COVID-19 Mortality Burden in sub-Saharan Africa: Myth or Reality?
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Evidence suggests the demographic age structure of sub-Saharan Africa is the leading factor of the low morbidity and mortality of COVID-19 compared to other regions of the world. n Widespread social mitigation strategies, such as lockdowns, have resulted in severe economic and societal consequences in terms of food security, adolescent pregnancy, gender-based violence, and disruptions in treating other diseases. n It is imperative to weigh the risks and benefits of social mitigation strategies for future waves.