scholarly journals Vaginal microbiome topic modeling of laboring Ugandan women with and without fever

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mercedeh Movassagh ◽  
Lisa M. Bebell ◽  
Kathy Burgoine ◽  
Christine Hehnly ◽  
Lijun Zhang ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Sub Saharan Africa ◽  
Vaginal Microbiome ◽  
Clustering Methods ◽  
Clinical Variables ◽  
Hypervariable Regions ◽  
Microbiome Research ◽  
Hierarchical Clustering Methods ◽  
Sub Saharan ◽  
The Impact

AbstractThe composition of the maternal vaginal microbiome influences the duration of pregnancy, onset of labor, and even neonatal outcomes. Maternal microbiome research in sub-Saharan Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. Here we aimed to illustrate the relationship between the vaginal microbiome of 99 laboring Ugandan women and intrapartum fever using routine microbiology and 16S ribosomal RNA gene sequencing from two hypervariable regions (V1–V2 and V3–V4). To describe the vaginal microbes associated with vaginal microbial communities, we pursued two approaches: hierarchical clustering methods and a novel Grades of Membership (GoM) modeling approach for vaginal microbiome characterization. Leveraging GoM models, we created a basis composed of a preassigned number of microbial topics whose linear combination optimally represents each patient yielding more comprehensive associations and characterization between maternal clinical features and the microbial communities. Using a random forest model, we showed that by including microbial topic models we improved upon clinical variables to predict maternal fever. Overall, we found a higher prevalence of Granulicatella, Streptococcus, Fusobacterium, Anaerococcus, Sneathia, Clostridium, Gemella, Mobiluncus, and Veillonella genera in febrile mothers, and higher prevalence of Lactobacillus genera (in particular L. crispatus and L. jensenii), Acinobacter, Aerococcus, and Prevotella species in afebrile mothers. By including clinical variables with microbial topics in this model, we observed young maternal age, fever reported earlier in the pregnancy, longer labor duration, and microbial communities with reduced Lactobacillus diversity were associated with intrapartum fever. These results better defined relationships between the presence or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial topics, and expanded our understanding of the impact of the microbiome on maternal and potentially neonatal outcome risk.

scholarly journals Vaginal Microbiome Topic Modelling of Laboring Ugandan Women With and Without Fever

2020 ◽  
Author(s):  
Mercedeh Movassagh ◽  
Lisa M. Bebell ◽  
Kathy Burgoine ◽  
Christine Hehnly ◽  
Lijun Zhang ◽  
...  
Keyword(s):  
Topic Model ◽  
Neonatal Infection ◽  
Sub Saharan Africa ◽  
Mining Machine ◽  
Vaginal Microbiome ◽  
Microbiome Composition ◽  
Clinical Variables ◽  
Microbiome Research ◽  
Sub Saharan ◽  
The Impact

AbstractThe composition of the maternal vaginal microbiome may influence the duration of pregnancy, onset of labor and even neonatal outcomes. Maternal microbiome research in sub Saharan-Africa has focused on non-pregnant and postpartum composition of the vaginal microbiome. We examined the vaginal microbiome composition of 99 laboring Ugandan women using routine microbiology and 16S ribosomal DNA sequencing from two hypervariable regions (V1-V2 and V3-V4), using standard hierarchical methods. We then introduce Grades of Membership (GoM) modeling for the vaginal microbiome, a method often used in the text mining machine learning literature. Leveraging GoM models, we create a basis composed of a small number of microbial ‘topic’s whose linear combination optimally represents each patient yielding more accurate associations. We identified relationships between defined communities and the presentation or absence of intrapartum fever. Using a random forest model we showed that by including novel microbial topic models we improved upon clinical variables to predict maternal fever. We also show by integrating clinical variables with a microbial topic model into this model found young maternal age, fever report earlier in the current pregnancy, and longer labors, as well as a more diverse, less Lactobacillus dominated microbiome were features of labor associated with intrapartum fever. These results better define relationships between presentation or absence of intrapartum fever, demographics, peripartum course, and vaginal microbial communities, and improve our understanding of the impact of the microbiome on maternal and neonatal infection risk.

Conflicts in Biafra, Katanga and Cabinda as a result of the geopolitical legacy of colonialism

2020 ◽  
Vol 2020 (10-3) ◽  
pp. 238-246
Author(s):  
Olga Dzhenchakova
Keyword(s):  
Democratic Republic ◽  
Economic Factor ◽  
Colonial Period ◽  
Sub Saharan Africa ◽  
Negative Consequences ◽  
Post Colonial ◽  
Republic Of The Congo ◽  
Sub Saharan ◽  
The Republic ◽  
The Impact

The article considers the impact of the colonial past of some countries in sub-Saharan Africa and its effect on their development during the post-colonial period. The negative consequences of the geopolitical legacy of colonialism are shown on the example of three countries: Nigeria, the Democratic Republic of the Congo and the Republic of Angola, expressed in the emergence of conflicts in these countries based on ethno-cultural, religious and socio-economic contradictions. At the same time, the focus is made on the economic factor and the consequences of the consumer policy of the former metropolises pursuing their mercantile interests were mixed.

scholarly journals The impact and cost‐effectiveness of community‐basedHIVself‐testing in sub‐Saharan Africa: a health economic and modelling analysis

2019 ◽  
Vol 22 (S1) ◽  
pp. e25243 ◽  
Author(s):  
Valentina Cambiano ◽  
Cheryl C Johnson ◽  
Karin Hatzold ◽  
Fern Terris‐Prestholt ◽  
Hendy Maheswaran ◽  
...  
Keyword(s):  
Health Economic ◽  
Cost Effectiveness ◽  
Sub Saharan Africa ◽  
Modelling Analysis ◽  
Sub Saharan ◽  
The Impact

scholarly journals Financial Inclusion, Income Inequality and Sustainable Economic Growth in Sub-Saharan African Countries

2021 ◽  
Vol 13 (4) ◽  
pp. 1780
Author(s):  
Chima M. Menyelim ◽  
Abiola A. Babajide ◽  
Alexander E. Omankhanlen ◽  
Benjamin I. Ehikioya
Keyword(s):  
Economic Growth ◽  
Income Inequality ◽  
Financial Services ◽  
Sub Saharan Africa ◽  
Kuznets Curve ◽  
African Countries ◽  
Financial Access ◽  
Sub Saharan ◽  
Sustainable Economic Growth ◽  
The Impact

This study evaluates the relevance of inclusive financial access in moderating the effect of income inequality on economic growth in 48 countries in Sub-Saharan Africa (SSA) for the period 1995 to 2017. The findings using the Generalised Method of Moments (sys-GMM) technique show that inclusive financial access contributes to reducing inequality in the short run, contrary to the Kuznets curve. The result reveals a negative effect of financial access on the relationship between income inequality and economic growth. There is a positive net effect of inclusive financial access in moderating the impact of income inequality on economic growth. Given the need to achieve the Sustainable Development Targets in the sub-region, policymakers and other stakeholders of the economy must design policies and programmes that would enhance access to financial services as an essential mechanism to reduce income disparity and enhance sustainable economic growth.

scholarly journals Mapping 20 Years of Urban Expansion in 45 Urban Areas of Sub-Saharan Africa

2021 ◽  
Vol 13 (3) ◽  
pp. 525
Author(s):  
Yann Forget ◽  
Michal Shimoni ◽  
Marius Gilbert ◽  
Catherine Linard
Keyword(s):  
Case Studies ◽  
Urban Areas ◽  
Urban Expansion ◽  
Local Population ◽  
Sub Saharan Africa ◽  
Annual Growth Rate ◽  
Urban Dynamics ◽  
Mapping Approach ◽  
Sub Saharan ◽  
The Impact

By 2050, half of the net increase in the world’s population is expected to reside in sub-Saharan Africa (SSA), driving high urbanization rates and drastic land cover changes. However, the data-scarce environment of SSA limits our understanding of the urban dynamics in the region. In this context, Earth Observation (EO) is an opportunity to gather accurate and up-to-date spatial information on urban extents. During the last decade, the adoption of open-access policies by major EO programs (CBERS, Landsat, Sentinel) has allowed the production of several global high resolution (10–30 m) maps of human settlements. However, mapping accuracies in SSA are usually lower, limited by the lack of reference datasets to support the training and the validation of the classification models. Here we propose a mapping approach based on multi-sensor satellite imagery (Landsat, Sentinel-1, Envisat, ERS) and volunteered geographic information (OpenStreetMap) to solve the challenges of urban remote sensing in SSA. The proposed mapping approach is assessed in 17 case studies for an average F1-score of 0.93, and applied in 45 urban areas of SSA to produce a dataset of urban expansion from 1995 to 2015. Across the case studies, built-up areas averaged a compound annual growth rate of 5.5% between 1995 and 2015. The comparison with local population dynamics reveals the heterogeneity of urban dynamics in SSA. Overall, population densities in built-up areas are decreasing. However, the impact of population growth on urban expansion differs depending on the size of the urban area and its income class.

scholarly journals Prevalence of mastitis in Nigerian livestock: a Review

2020 ◽  
Vol 1 (1) ◽  
pp. 20-29
Author(s):  
Hussaini Ojagefu Adamu ◽  
Rahimat Oshuwa Hussaini ◽  
Cedric Obasuyi ◽  
Linus Irefo Anagha ◽  
Gabriel Oscy Okoduwa
Keyword(s):  
Control Strategies ◽  
Dairy Farms ◽  
Livestock Production ◽  
Sub Saharan Africa ◽  
Economic Losses ◽  
Ecological Development ◽  
Management Plans ◽  
Sub Saharan ◽  
Control And Management ◽  
The Impact

AbstractMastitis is a disease of livestock that directly impede livestock production and thus hindering the socio-ecological development of sub-Saharan Africa. Studies have estimated the prevalence of this disease in 30% of Africa countries, with Ethiopia having the highest prevalence. The coverage is low, despite the wide livestock and dairy farms distribution in Africa. Furthermore, estimated economic losses due to the impact of mastitis are lacking in Nigeria. The disease is endemic in Nigeria as indicated by the available data and there are no proposed management plans or control strategies. This review is thus presented to serve as a wakeup call to all parties involved to intensify efforts towards the diagnosis, control, and management of the disease in Nigeria.

scholarly journals Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Verónica Lloréns-Rico ◽  
Sara Vieira-Silva ◽  
Pedro J. Gonçalves ◽  
Gwen Falony ◽  
Jeroen Raes
Keyword(s):  
Microbial Communities ◽  
Quantitative Methods ◽  
Microbial Load ◽  
Metagenomic Sequencing ◽  
Sampling Depth ◽  
Microbiome Research ◽  
Microbiome Data ◽  
The Impact ◽  
Analytical Approaches ◽  
Quantitative Approaches

AbstractWhile metagenomic sequencing has become the tool of preference to study host-associated microbial communities, downstream analyses and clinical interpretation of microbiome data remains challenging due to the sparsity and compositionality of sequence matrices. Here, we evaluate both computational and experimental approaches proposed to mitigate the impact of these outstanding issues. Generating fecal metagenomes drawn from simulated microbial communities, we benchmark the performance of thirteen commonly used analytical approaches in terms of diversity estimation, identification of taxon-taxon associations, and assessment of taxon-metadata correlations under the challenge of varying microbial ecosystem loads. We find quantitative approaches including experimental procedures to incorporate microbial load variation in downstream analyses to perform significantly better than computational strategies designed to mitigate data compositionality and sparsity, not only improving the identification of true positive associations, but also reducing false positive detection. When analyzing simulated scenarios of low microbial load dysbiosis as observed in inflammatory pathologies, quantitative methods correcting for sampling depth show higher precision compared to uncorrected scaling. Overall, our findings advocate for a wider adoption of experimental quantitative approaches in microbiome research, yet also suggest preferred transformations for specific cases where determination of microbial load of samples is not feasible.

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