With increasing prevalence and an expected rise in disease burden, cancer is a cause of concern for African healthcare. The cancer burden in Africa is expected to rise to 2.1 million new cases per year and 1.4 million deaths annually by the year 2040. Even though efforts are being made to improve the standard of oncology service delivery in Africa, the current state of cancer care is not yet on par with the rise in the cancer burden. Cutting-edge technologies and innovations are being developed across the globe to augment the battle against cancer; however, many of them are beyond the reach of African countries. Modern oncology innovations targeted to ward Africa would be promising to address the high cancer mortality rates. The innovations should be cost-effective and widely accessible to tackle the rapidly rising mortality rate on the African continent. Though it may seem promising, a multidisciplinary approach is required to overcome the challenges associated with the development and implementation of modern oncology innovations in Africa.
The vast majority of its population being a pastoralist community, the Somali region in Ethiopia shares the longest border with its neighboring east African countries. These communities face a high risk for transmission of imported COVID-19 cases and remain vulnerable due to lack of access to health delivery and low utilisation of services. Valuable lessons from other countries, has placed the One Health Approach as an appropriate, feasible and applicable preventive and control measure for COVID-19. This paper discusses the epidemiological and social susceptibility of pastoral communities in the transmission of COVID-19 and the introduction of One Health Approach as an effective inter-disciplinary response and management.
Tilapia are among the most important farmed fish species worldwide, and are fundamental for the food security of many developing countries. Several genetically improved Nile tilapia (Oreochromis niloticus) strains exist, such as the iconic Genetically Improved Farmed Tilapia (GIFT), and breeding programs typically follow classical pedigree-based selection. The use of genome-wide single-nucleotide polymorphism (SNP) data can enable an understanding of the genetic architecture of economically important traits and the acceleration of genetic gain via genomic selection. Due to the global importance and diversity of Nile tilapia, an open access SNP array would be beneficial for aquaculture research and production. In the current study, a ∼65K SNP array was designed based on SNPs discovered from whole-genome sequence data from a GIFT breeding nucleus population and the overlap with SNP datasets from wild fish populations and several other farmed Nile tilapia strains. The SNP array was applied to clearly distinguish between different tilapia populations across Asia and Africa, with at least ∼30,000 SNPs segregating in each of the diverse population samples tested. It is anticipated that this SNP array will be an enabling tool for population genetics and tilapia breeding research, facilitating consistency and comparison of results across studies.
To ensure the safe discharge of treated wastewater to the environment, continuous efforts are vital to enhance the modelling accuracy of wastewater treatment plants (WWTPs) through utilizing state-of-art techniques and algorithms. The integration of metaheuristic modern optimization algorithms that are natlurally inspired with the Fussy Inference Systems (FIS) to improve the modelling performance is a promising and mathematically suitable approach. This study integrates four population-based algorithms, namely: Particle swarm optimization (PSO), Genetic algorithm (GA), Hybrid GA-PSO, and Mutating invasive weed optimization (M-IWO) with FIS system. A full-scale WWTP in South Africa (SA) was selected to assess the validity of the proposed algorithms, where six wastewater effluent parameters were modeled, i.e., Alkalinity (ALK), Sulphate (SLP), Phosphate (PHS), Total Kjeldahl Nitrogen (TKN), Total Suspended Solids (TSS), and Chemical Oxygen Demand (COD). The results from this study showed that the hybrid PSO-GA algorithm outperforms the PSO and GA algorithms when used individually, in modelling all wastewater effluent parameters. PSO performed better for SLP and TKN compared to GA, while the M-IWO algorithm failed to provide an acceptable modelling convergence for all the studied parameters. However, three out of four algorithms applied in this study proven beneficial to be optimized in enhancing the modelling accuracy of wastewater quality parameters.
Background: In Africa high prevalence of overweight and obesity was found in regions of East Africa (0.3%),
West Africa (0.7%), Central Africa (0.2%), South Africa (3.8%), and North Africa (12.5%).
Aims: This meta-analysis aimed to analyze the prevalence of obesity among young adults, aged 18-25 years
from five African countries.
Methods: The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were applied to
search published studies. of the 100 studies published as found in scientific databases from 2010 to 2017, only
five were selected. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)
checklist was used to eliminate other studies.
Outcomes: A total of 22,320 obese young adults were analyzed to be prevalent. The obesity among adults in
SouthAfrica was found to be correlated with less physical activities. In Uganda, the prevalence of obesity is
683 which relates with their sedentary lifestyle and socio-demography. Among 371 young adults in Nigeria, the
prevalence of obesity was 5.1% among male and 10% among female related to diet and other consumptions.
Among 646 adults in Ghana, the prevalence of general obesity was observed to be related to genetics.
Conclusion: Prevalence of the male gender was 9,509 having a p=0.284 (at 95% C.I.±4,440.87845-
8,788.87845) with a mean score of 1,251, and a SD= 61,066. While the prevalence of obesity on females was
10,874 having a p= 0.00019, (at 95% C.I.±3,592.07-6,094.07) with a mean score of 2,174, and SD= 3,375.
Palms are iconic plants. Oil palms are very important economically and originate in Africa where they can act as a model for palms in general. The effect of future climate on the growth of oil palm will be very detrimental. Latitudinal migration of tropical crops to climate refuges may be impossible, and longitudinal migration has only been confirmed for oil palm, of all the tropical crops. The previous method to determine the longitudinal trend for oil palm used the longitudes of various countries in Africa and plotted these against the percentage suitable climate for growing oil palms in each country. An increasing longitudinal trend was observed from west to east. However, the longitudes of the countries were randomly distributed which may have introduced bias and the procedure was time consuming. The present report presents an optimised and systematic procedure that divided the regions, as presented on a map derived from a CLIMEX model, into ten equal sectors and the percentage suitable climates for growing oil palm were determined for each sector. This approach was quicker, systematic and straight forward and will be useful for management of oil palm plantations under climate change. The method confirmed and validated the trends reported in the original method although the suitability values were often lower and there was less spread of values around the trend. The values for the CSIRO MK3.0 and MIROC H models demonstrated considerable similarities to each other, contributing to validation of the method. The procedure of dividing maps equally into sectors derived from models, could be used for other crops, regions, or systems more generally, where the alternative may be a more superficial visual examination of the maps. Methods are required to mitigate the effects of climate change and stakeholders need to contribute more actively to the current climate debate with tangible actions.
The generic name Lanchnophorus Reuter, 1887, deemed for a long time to be unavailable as incorrect original spelling of Lachnophorus (in fact Lachnophorus Distant, 1903 is an unjustified emendation of the former), is restored as a valid name of the genus. Lachnesthus Bergroth, 1915, syn. nov. (new name for the preoccupied Lachnophorus Distant, 1903) is considered junior synonym of Lanchnophorus. The following nomenclatural changes are proposed: Lanchnophorus flavus (Scudder, 1971) comb. nov. = Lachnesthus chinai Scudder, nomen nudum; Lanchnophorus guttulatus Reuter, 1887, comb. restit. = Lachnophorus albidomaculatus Distant, 1913, syn. nov. = Lachnesthus rodriguezensis China, 1925, syn. nov.; Lanchnophorus leucospilus (Walker, 1872) comb. nov.; Lanchnophorus merula (Distant, 1903) comb. nov.; and Lanchnophorus singalensis (Dohrn, 1860) comb. nov. Three new species are described: Lanchnophorus gaoqingae Kment & Jindra sp. nov. from China (Yunnan), Lanchnophorus seminitens Kment & Carapezza sp. nov. from Socotra Island (Yemen), and Lanchnophorus webbi Kondorosy sp. nov. from India: Tamil Nadu. Bibliographies and known distribution of all the included species are reviewed. The following new country and state records are provided: L. flavus from Central African Republic, Ethiopia, Ghana, Mali, Malawi, Niger, Zambia and Zimbabwe; L. leucospilus from China (Yunnan) and Laos, L. merula from India (Kerala/Tamil Nadu) and Thailand; L. singalensis from Angola, Benin, Mozambique, Namibia, Senegal, Sierra Leone, Tanzania, Togo, Uganda, Zambia, Zimbabwe, China (Hainan), Iran (Sistan and Ba-luchestan), Oman, Pakistan, India (Himachal Pradesh, Karnataka, Kerala, Rajasthan), Malaysia, Philippines, and Thailand.
This paper deals with the analysis of mean reversion and convergence of the ecological footprint (EF) in the MENA region. Using a long memory model based on fractional integration, we find that the results are very heterogeneous across countries depending on the assumptions made on the error term and the use of original versus logged data. Nevertheless, some conclusions can be obtained. Thus, mean reversion is decisively found in the case of Tunisia, and other countries showing some degree of reversion to the mean include Israel, Syria, Yemen, and Iran. Dealing with the issue of convergence within the MENA countries, similar conclusions hold and only Tunisia reports statistical evidence of convergence for the two types of errors. Additional evidence is found in the case of Syria, Yemen, and Jordan with uncorrelated errors and for Iran with autocorrelation. It is recommended that environmental policies targeted at stabilizing the trends in EF in the MENA region should not be indiscriminately applied in consideration of the heterogeneous nature of the series in the region.
Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.
This paper examines the pattern of convergence in electricity intensity in a sample of 79 countries. We apply the residual augmented least squares regression to the convergence of energy intensity. This method has been used in the convergence of per capita energy consumption but not convergence of energy intensity. Furthermore, in contrast to the previous studies which mainly used the conventional beta convergence approach to examine conditional convergence, we use a beta convergence method that is capable of identifying the actual number of countries that contribute to conditional convergence. The sigma and gamma convergences of electricity intensity are also examined. In addition to the full sample of countries, we also examine convergence in African countries, Asian and Oceanic countries, American countries and European countries, separately. Convergences in OECD and non-OECD countries are also examined, separately. In the full sample, the results show convergence exists in 54% of the countries in the total sample. There is convergence in 65% of the African countries, 61% of the American countries, 43% of the Asian and Oceanic countries and 33% of the European countries. In terms of the regional classification, it is also observed that convergence exists for 58% of the non-OECD countries and 31% of the OECD countries. There is evidence for sigma convergence in all the blocs with the exception of European and non-OECD countries. With the exception of African countries, there is evidence for gamma convergence in all the countries and the various blocs. The policy implications of the results are discussed.
The broad purpose of this study is to empirically explore the impact of globalization and financial development on environmental pollution by carbon (CO2) emissions in the six Middle East and North Africa (MENA) countries using balanced panel data from 1971 to 2015. We also aimed to test the legitimacy of the environmental Kuznets curve (EKC) hypothesis for this region. The fixed-effects approach preferred by the Hausman specification test is used to estimate the empirical model, and the feasible generalized least squares (F.G.L.S.) estimator is employed to cope with any issue of heteroscedasticity and serial correlation. This study found that globalization and financial development have adverse and significant effects on environmental degradation and affirm the legitimacy of the EKC hypothesis for these countries. The finding of this study suggests that the governments of MENA countries should design and implement appropriate policies for strengthening the renewable sources of energy like wind, solar, bio-fuel, and thermal to decrease CO2 emissions and boost sustainable economic development. The policymakers should focus on the efficiency of institutions and enhancement of energy-saving projects in this region.
As part of a public health behavior change and communication strategy related to the identification of a novel ebolavirus in bats in Sierra Leone in 2016, a consortium of experts launched an effort to create a widely accessible resource for community awareness and education on reducing disease risk. The resulting picture book, Living Safely With Bats, includes technical content developed by a consortium of experts in public health, animal health, conservation, bats, and disease ecology from 30 countries. The book has now been adapted, translated, and used in more than 20 countries in Africa and Asia. We review the processes used to integrate feedback from local stakeholders and multidisciplinary experts. We also provide recommendations for One Health and other practitioners who choose to pursue the development and evaluation of this or similar zoonotic disease risk mitigation tools.
Automatic text summarization is one of the most promising solutions to the ever-growing challenges of textual data as it produces a shorter version of the original document with fewer bytes, but the same information as the original document. Despite the advancements in automatic text summarization research, research involving the development of automatic text summarization methods for documents written in Hausa, a Chadic language widely spoken in West Africa by approximately 150,000,000 people as either their first or second language, is still in early stages of development. This study proposes a novel graph-based extractive single-document summarization method for Hausa text by modifying the existing PageRank algorithm using the normalized common bigrams count between adjacent sentences as the initial vertex score. The proposed method is evaluated using a primarily collected Hausa summarization evaluation dataset comprising of 113 Hausa news articles on ROUGE evaluation toolkits. The proposed approach outperformed the standard methods using the same datasets. It outperformed the TextRank method by 2.1%, LexRank by 12.3%, centroid-based method by 19.5%, and BM25 method by 17.4%.
Monkeypox (MPX) is a zoonotic disease caused by the MPX virus from the poxviridae family of orthopoxviruses. Typically, endemic in central and west Africa, it has now become a matter of concern since cases have been reported in non-endemic countries around mid-June 2022, especially in the European region, with the transmission not related to travel. The diagnosis is made by PCR testing of the skin lesions. Even though treatment is symptomatic, antiretrovirals, such as tecovirimat, are used in severe cases. Vaccination with second and third generation vaccines is approved for prophylaxis in high risk individuals. Unfortunately, these options of treatment and prevention are only available in high income countries at the moment. This review, through a thorough literature search of articles from 2017 onward, focuses on epidemiology, clinical manifestations, challenges, treatment, prevention and control of MPX virus and how they can be corelated with other viral outbreaks including COVID-19, Acute Hepatitis of unknown origin, Measles and Dengue, to better predict and therefore prevent its transmission. The previous COVID-19 pandemic increased the disease burden on healthcare infrastructure of low-middle income countries, therefore, this recent MPX outbreak calls for a joint effort from healthcare authorities, political figures, and NGOs to combat the disease and prevent its further spread not only in high income but also in middle- and low-income countries.