Tsetse flies are the sole vectors of human African trypanosomiasis throughout sub-Saharan Africa. Both sexes of adult tsetse feed exclusively on blood and contribute to disease transmission. Notable differences between tsetse and other disease vectors include obligate microbial symbioses, viviparous reproduction, and lactation. Here, we describe the sequence and annotation of the 366-megabase Glossina morsitans morsitans genome. Analysis of the genome and the 12,308 predicted protein–encoding genes led to multiple discoveries, including chromosomal integrations of bacterial (Wolbachia) genome sequences, a family of lactation-specific proteins, reduced complement of host pathogen recognition proteins, and reduced olfaction/chemosensory associated genes. These genome data provide a foundation for research into trypanosomiasis prevention and yield important insights with broad implications for multiple aspects of tsetse biology.

Background and objectives Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a Pan African bioinformatics network, was established to build capacity specifically to enable H3Africa researchers to analyse their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet’s role has evolved in response to changing needs from the consortium and the African bioinformatics community. The network set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage and analysis. Methods and results Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrolment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Since H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System and eBiokits. A set of reproducible, portable and cloud scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for downstream interpretation of prioritized variants. To provide support for these and other bioinformatics queries, an online bioinformatics helpdesk backed by broad consortium expertise has been established. Further support is provided by means of various modes of bioinformatics training. Conclusion For the past 4 years, the development of infrastructure support and human capacity through H3ABioNet, have significantly contributed to the establishment of African scientific networks, data analysis facilities and training programmes. Here, we describe the infrastructure and how it has impacted genomics and bioinformatics research in Africa.

Tuberculosis has the most considerable death rate among diseases caused by a single micro-organism type. The disease is a significant issue for most third-world countries due to poor diagnosis and treatment potentials. Early diagnosis of tuberculosis is the most effective way of managing the disease in patients to reduce the mortality rate of the infection. Despite several methods that exist in diagnosing tuberculosis, the limitations ranging from the cost in carrying out the test to the time taken to obtain the results have hindered early diagnosis of the disease. This work aims to develop a predictive model that would help in the diagnosis of TB using an extended weighted voting ensemble method. The method used to carry out this research involved analyzing tuberculosis gene expression data obtained from GEO (Transcript Expression Omnibus) database and developing a classification model to aid tuberculosis diagnosis. A classifier combination of Naïve Bayes (NB), and Support Vector Machine (SVM) was used to develop the classification model. The weighted voting ensemble technique was used to improve the classification model's performance by combining the classification results of the single classifier and selecting the group with the highest vote based on the weights given to the single classifiers. Experimental analysis indicates a performance accuracy of the enhanced ensemble classifier as 0.95, which showed a better performance than the single classifiers, which had 0.92, and 0.87 obtained from SVM and NB, respectively. The developed model can also assist health practitioners in the timely diagnosis of tuberculosis, which would reduce the mortality rate caused by the disease, especially in developing countries.

BackgroundAnthropometric measures have been widely used for body weight classification in humans. Waist circumference has been advanced as a useful parameter for measuring adiposity. This study evaluated the correlation between body mass index (BMI) and waist circumference and examined their significance as indicators of health status in adults.Design and methodsThe subject included 489 healthy adults from Ota, Nigeria, aged between 20 and 75 years, grouped into early adulthood (20-39 years), middle adulthood (40-59 years) and advanced adulthood (60 years and above). Weight, height and abdominal circumference were measured. BMI was calculated as weight kg/height2 (m2) and World Health Organization cut-offs were used to categorize them into normal, underweight, overweight and obese.ResultsAbnormal weight categories accounted for 60 % of the subjects (underweight 11 %, overweight 31%, and obese 18%). The waist circumference of overweight and obese categories were significantly (P<0.05) higher than the normal weight category. There was no significant difference between waist circumference of underweight and normal subjects. The correlation coefficient values of BMI with waist circumference (r=0.63), body weight (r=0.76) and height (r=-0.31) were significant (P<0.01) for the total subjects.ConclusionsThe study indicates that waist circumference can serve as a positive indicator of overweight and obesity in the selected communities; however, it may not be used to determine underweight in adults. Regular BMI and waist circumference screening is recommended as an easy and effective means of assessing body weight and in the prevention of weight related diseases in adults.Significance for public healthThis manuscript describes the correlation between body mass index, waist circumference and body weight of two communities in Ota, Ogun State, Nigeria and the use of these anthropometric measures for body weight classification in human populations of the selected communities. This was carried out to evaluate the health status of the indigenes of the two communities for proper health awareness and public health intervention programmes.

Objectives To quantify the epidemiology of bladder cancer in Africa to guide a targeted public health response and support research initiatives. Methods We systematically searched publicly available sources for population-based registry studies reporting the incidence of bladder cancer in Africa between January 1980 and June 2017. Crude incidence rates of bladder cancer were extracted. A Bayesian network meta-analysis model was employed to estimate incidence rates. Results The search returned 1,328 studies. Twenty-two studies conducted across 15 African countries met our pre-defined selection criteria. Heterogeneity across studies was high (I2=98.9%, p<0.001). The pooled incidence of bladder cancer in Africa was 7.0 (95% Credible Interval [CI]: 5.8–8.3) per 100,000 population in men and 1.8 (1.2–2.6) per 100,000 in women. The incidence of bladder cancer was consistently higher in North Africa in both sexes. Among men, we estimated a pooled incidence of 10.1 (7.9–11.9) per 100,000 in North Africa and 5.0 (3.8–6.6) per 100,000 in Sub-Saharan Africa (SSA). In women, the pooled incidence was 2.0 (1.0–3.0) per 100,000 and 1.5 (0.9–2.0) per 100,000 in North Africa and SSA, respectively. Incidence rates increased significantly among men from 5.6 (4.2–7.2) in the 1990s to 8.5 (6.9–10.1) per 100,000 in 2010. Conclusions This study suggests a growing incidence of bladder cancer in Africa in recent years, particularly among men and in North Africa. This study also highlights the lack of quality data sources and collection of essential clinical and epidemiological data in several African countries and this maligns public health planning.