Tamale Teaching Hospital

Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports. At issue is whether SSA can meet this vast increase in cereal demand without greater reliance on cereal imports or major expansion of agricultural area and associated biodiversity loss and greenhouse gas emissions. Recent studies indicate that the global increase in food demand by 2050 can be met through closing the gap between current farm yield and yield potential on existing cropland. Here, however, we estimate it will not be feasible to meet future SSA cereal demand on existing production area by yield gap closure alone. Our agronomically robust yield gap analysis for 10 countries in SSA using location-specific data and a spatial upscaling approach reveals that, in addition to yield gap closure, other more complex and uncertain components of intensification are also needed, i.e., increasing cropping intensity (the number of crops grown per 12 mo on the same field) and sustainable expansion of irrigated production area. If intensification is not successful and massive cropland land expansion is to be avoided, SSA will depend much more on imports of cereals than it does today.

Abstract Cowpea, Vigna unguiculata (L.), is an important grain legume grown in the tropics where it constitutes a valuable source of protein in the diets of millions of people. Some abiotic and biotic stresses adversely affect its productivity. A review of the genetics, genomics and breeding of cowpea is presented in this article. Cowpea breeding programmes have studied intensively qualitative and quantitative genetics of the crop to better enhance its improvement. A number of initiatives including Tropical Legumes projects have contributed to the development of cowpea genomic resources. Recent progress in the development of consensus genetic map containing 37,372 SNP s mapped to 3,280 bins will strengthen cowpea trait discovery pipeline. Several informative markers associated with quantitative trait loci ( QTL ) related to desirable attributes of cowpea were generated. Cowpea genetic improvement activities aim at the development of drought tolerant, phosphorus use efficient, bacterial blight and virus resistant lines through exploiting available genetic resources as well as deployment of modern breeding tools that will enhance genetic gain when grown by sub‐Saharan Africa farmers.

Brain tumor classification is a very important and the most prominent step for assessing life-threatening abnormal tissues and providing an efficient treatment in patient recovery. To identify pathological conditions in the brain, there exist various medical imaging technologies. Magnetic Resonance Imaging (MRI) is extensively used in medical imaging due to its excellent image quality and independence from ionizing radiations. The significance of deep learning, a subset of artificial intelligence in the area of medical diagnosis applications, has macadamized the path in rapid developments for brain tumor detection from MRI to higher prediction rate. For brain tumor analysis and classification, the convolution neural network (CNN) is the most extensive and widely used deep learning algorithm. In this work, we present a comparative performance analysis of transfer learning-based CNN-pretrained VGG-16, ResNet-50, and Inception-v3 models for automatic prediction of tumor cells in the brain. Pretrained models are demonstrated on the MRI brain tumor images dataset consisting of 233 images. Our paper aims to locate brain tumors with the utilization of the VGG-16 pretrained CNN model. The performance of our model will be evaluated on accuracy. As an outcome, we can estimate that the pretrained model VGG-16 determines highly adequate results with an increase in the accuracy rate of training and validation.

Smallholder farmers in the Guinea savanna practise cereal-legume intercropping to mitigate risks of crop failure in mono-cropping. The productivity of cereal-legume intercrops could be influenced by the spatial arrangement of the intercrops and the soil fertility status. Knowledge on the effect of soil fertility status on intercrop productivity is generally lacking in the Guinea savanna despite the wide variability in soil fertility status in farmers’ fields, and the productivity of within-row spatial arrangement of intercrops relative to the distinct-row systems under on-farm conditions has not been studied in the region. We studied effects of maize-legume spatial intercropping patterns and soil fertility status on resource use efficiency, crop productivity and economic profitability under on-farm conditions in the Guinea savanna. Treatments consisted of maize-legume intercropped within-row, 1 row of maize alternated with one row of legume, 2 rows of maize alternated with 2 rows of legume, a sole maize crop and a sole legume crop. These were assessed in the southern Guinea savanna (SGS) and the northern Guinea savanna (NGS) of northern Ghana for two seasons using three fields differing in soil fertility in each agro-ecological zone. Each treatment received 25 kg P and 30 kg K ha−1 at sowing, while maize received 25 kg (intercrop) or 50 kg (sole) N ha−1 at 3 and 6 weeks after sowing. The experiment was conducted in a randomised complete block design with each block of treatments replicated four times per fertility level at each site. Better soil conditions and rainfall in the SGS resulted in 48, 38 and 9% more maize, soybean and groundnut grain yield, respectively produced than in the NGS, while 11% more cowpea grain yield was produced in the NGS. Sole crops of maize and legumes produced significantly more grain yield per unit area than the respective intercrops of maize and legumes. Land equivalent ratios (LERs) of all intercrop patterns were greater than unity indicating more efficient and productive use of environmental resources by intercrops. Sole legumes intercepted more radiation than sole maize, while the interception by intercrops was in between that of sole legumes and sole maize. The intercrop however converted the intercepted radiation more efficiently into grain yield than the sole crops. Economic returns were greater for intercrops than for either sole crop. The within-row intercrop pattern was the most productive and lucrative system. Larger grain yields in the SGS and in fertile fields led to greater economic returns. However, intercropping systems in poorly fertile fields and in the NGS recorded greater LERs (1.16–1.81) compared with fertile fields (1.07–1.54) and with the SGS. This suggests that intercropping is more beneficial in less fertile fields and in more marginal environments such as the NGS. Cowpea and groundnut performed better than soybean when intercropped with maize, though the larger absolute grain yields of soybean resulted in larger net benefits.

The symptoms of severe malaria and their contribution to mortality were assessed in 290 children in northern Ghana. Common symptoms were severe anemia (55%), prostration (33%), respiratory distress (23%), convulsions (20%), and impaired consciousness (19%). Age influenced this pattern. The fatality rate was 11.2%. In multivariate analysis, circulatory collapse, impaired consciousness, hypoglycemia, and malnutrition independently predicted death. Children with severe malaria by the current World Health Organization (WHO) classification, but not by the previous one (1990), showed relatively mild clinical manifestations and a low case fatality rate (3.2%). In hospitalized children with severe malaria in northern Ghana, severe anemia is the leading manifestation, but itself does not contribute to mortality. In this region, malnutrition and circulatory collapse were important predictors of fatal malaria. The current WHO criteria serve well in identifying life-threatening disease, but also include rather mild cases that may complicate the allocation of immediate care in settings with limited resources.

BACKGROUND: Malaria, anemia, and malnutrition contribute substantially to childhood morbidity in sub-Saharan Africa, but their respective roles and interactions in conferring disease are complex. We aimed to investigate these interactions. METHODS: In 2002, we assessed plasmodial infection, anemia, and nutritional indices in 2 representative surveys comprising >4000 children in northern Ghana. RESULTS: Infection with Plasmodium species was observed in 82% and 75% of children in the rainy and dry season, respectively. The fraction of fever attributable to malaria was 77% in the rainy season and 48% in the dry season and peaked in children of rural residence. Anemia (hemoglobin level, <11 g/dL) was seen in 64% of children and was, in multivariate analysis, associated with young age, season, residence, parasitemia, P. malariae coinfection, and malnutrition (odds ratio [OR], 1.68 [95% confidence interval [CI], 1.38-2.04]). In addition, malnutrition was independently associated with fever (axillary temperature, > or = 37.5 degrees C; OR, 1.59 [95% CI, 1.13-2.23]) and clinical malaria (OR, 1.67 [95% CI, 1.10-2.50]). CONCLUSIONS: Malnutrition is a fundamental factor contributing to malaria-associated morbidity and anemia, even if the latter exhibits multifactorial patterns. Our data demonstrate that malaria-control programs alone may not have the desired impact on childhood morbidity on a large scale without concomitant nutrition programs.

Typologies may be used as tools for dealing with farming system heterogeneity. This is achieved by classifying farms into groups that have common characteristics, i.e. farm types, which can support the implementation of a more tailored approach to agricultural development. This article explored patterns of farming system diversity through the classification of 70 smallholder farm households in two districts (Savelugu-Nanton and Tolon-Kumbungu) of Ghana's Northern Region. Based on 2013 survey data, the typology was constructed using the multivariate statistical techniques of principal component analysis and cluster analysis. Results proposed six farm types, stratified on the basis of household, labour, land use, livestock and income variables, explaining the structural and functional differences between farming systems. Types 1 and 2 were characterized by relatively high levels of resource endowment and oriented towards non-farm activities and crop sales respectively. Types 3 and 4 were moderately resource-endowed with income derived primarily from on-farm activities. Types 5 and 6 were resource constrained, with production oriented towards subsistence. The most salient differences among farm types concerned herd size (largest for Type 1), degree of legume integration (largest for Types 2-4), household size and hired labour (smallest household size for Types 4 and 6, and largest proportion of hired labour for Type 4), degree of diversification into off/non-farm activities (highest for Type 1 and lowest for Type 5) and severity of resource constraints (Type 6 was most constrained with a small farm area and herd comprised mainly of poultry). It was found that livelihood strategies reflected the distinctive characteristics of farm households; with poorly-endowed types restricted to a 'survival strategy' and more affluent types free to pursue a 'development strategy'. This study clearly demonstrates that using the established typology as a practical framework allows identification of type-specific farm household opportunities and constraints for the targeting of agricultural interventions and innovations, which will be further analysed in the research-for-development project. We conclude that a more flexible approach to typology construction, for example through the incorporation of farmer perspectives, might provide further context and insight into the causes, consequences and negotiation of farm diversity.

An integrated Markov Chain and Cellular Automata modelling (CA MARKOV), multicriteria evaluation techniques have been applied to produce transition probability. The unsupervised method was employed to classify the satellite images of year 1985, 1995, 2005 and 2015 to meet the magnitude of LULC change. Results showing the spatial pattern of the sub-basin is largely influenced by the biophysical and socio-economic drivers leading to growth of agricultural lands and built-up area in the basin. Simulated plausible future LULC changes for 2025 which is based on a CA MARKOV that integrates Markovian transition probabilities computed from satellite-derived LULC maps and a CA contiguity spatial filter (5 × 5). Further, the fragmentation analysis was performed to check the fragmentation scenario in the year 2025. The result for year 2025 with reasonably good accuracy will be useful to the planners, policy- and decision-makers.

The high frequency of alpha(+)-thalassemia in malaria-endemic regions may reflect natural selection due to protection from potentially fatal severe malaria. In Africa, bearing 90% of global malaria morbidity and mortality, this has not yet been observed. We tested this hypothesis in an unmatched case-control study among 301 Ghanaian children with severe malaria and 2107 controls (62% parasitemic). In control children, alpha(+)-thalassemia affected neither prevalence nor density of Plasmodium falciparum. However, heterozygous alpha(+)-thalassemia was observed in 32.6% of controls but in only 26.2% of cases (odds ratio [OR], 0.74; 95% confidence interval [CI], 0.56-0.98). Protection against severe malaria was found to be pronounced comparing severe malaria patients with parasitemic controls (adjusted OR in children < 5 years of age, 0.52; 95% CI, 0.34-0.78) and to wane with age. No protective effect was discernible for homozygous children. Our findings provide evidence for natural selection of alpha(+)-thalassemia in Africa due to protection from severe malaria.

This study aims to identify the determinants of adoption of improved maize variety (IMV) among farmers in the northern region of Ghana and subsequently assess the factors influencing the intensity of IMV adoption. The study used two econometric techniques to address its objectives. Firstly, a multinomial logit was employed to identify factors affecting the adoption of IMV. Secondly, Tobit regression was used to analyze the determinants of the intensity of IMV adoption. A fractional regression model through the procedure proposed by Papke and Wooldridge was also used to test the robustness of the results obtained from the Tobit model. Results from the study revealed that variables such as the age of the household head, household size, level of experience, farm workshop attendance, the number of years in formal education, access to agricultural credit, membership of a farmer-based organization, availability of labor and extension contacts influence the adoption of IMV. Moreover, variables such as years in formal education, household size, distance to farm plots, attendance of demonstration fields, membership of a farmer-based organization, farm size, and previous income are significant determinants of the intensity of IMV adoption. The study has implications for achieving food security and poverty reduction through agricultural productivity growth.

Motorcycle crash severity is under-researched in Ghana. Thus, the probable risk factors and association between these factors and motorcycle crash severity outcomes is not known. Traditional statistical models have intrinsic assumptions and pre-defined correlations that, if flouted, can generate inaccurate results. In this study, machine learning based algorithms were employed to predict and classify motorcycle crash severity. Machine learning based techniques are non-parametric models without the presumption of relationships between endogenous and exogenous variables. The main aim of this research is to evaluate and compare different approaches to modeling motorcycle crash severity as well as investigating the effect of risk factors on the injury outcomes of motorcycle crashes. Motorcycle crash dataset between 2011 and 2015 was extracted from the National Road Traffic Crash Database at the Building and Road Research Institute (BRRI) in Ghana. The dataset was classified into four injury severity categories: fatal, hospitalized, injured, and damage-only. Three machine learning based models were developed: J48 Decision Tree Classifier, Random Forest (RF) and Instance-Based learning with parameter k (IBk) were employed to model the severity of injury in a motorcycle crash. These machine learning algorithms were validated using 10-fold cross-validation technique. The three machine learning based algorithms were compared with one another and the statistical model: multinomial logit model (MNLM). Also, the relative importance analysis of the attribute was conducted to determine the impact of these attributes on injury severity outcomes. The results of the study reveal that the predictions of machine learning algorithms are superior to the MNLM in accuracy and effectiveness, and the RF-based algorithms show the overall best agreement with the experimental data out of the three machine learning algorithms, for its global optimization and extrapolation ability. Location type, time of the crash, settlement type, collision partner, collision type, road separation, road surface type, the day of the week, and road shoulder condition were found as the critical determinants of motorcycle crash injury severity.

Nineteen patients from an area of vector control in the savanna region of Northern Ghana, all with moderate to heavy infections with Onchocerca volvulus and some with ocular involvement, were treated with 50, 100, 150 or 200 micrograms kg-1 of ivermectin. Detailed monitoring of clinical and ocular reactions and of alterations in skin microfilarial counts and laboratory indices were carried out during the first 28 days. Microfilarial counts in skin snips and detailed ocular examinations were then repeated at intervals over a period of nine months. Ivermectin slowly eliminated microfilariae from the skin and eye without serious adverse clinical or ocular reactions in all treated groups. There was little difference in efficacy between doses of 100, 150 and 200 micrograms kg-1, and these were more effective than the 50 micrograms kg-1 dose. Very low levels of skin microfilariae were maintained for nine months. Microfilariae were not eliminated from the eye for at least three months. The drug was neither macrofilaricidal nor embryotoxic. However, it produced a dose-dependent stimulation of embryogenesis manifest at one month and succeeded by a suppression of embryogenesis at three months after therapy. In areas where transmission of onchocerciasis has been interrupted, ivermectin may need not be given more often than once a year. The efficacy of the drug on single dosage and the mild adverse reactions produced, if confirmed in subsequent controlled studies, would greatly simplify the treatment of onchocerciasis and would reintroduce new concepts of the role of chemotherapy in the control of onchocerciasis.

INTRODUCTION: The COVID-19 pandemic has compounded the global crisis of stress and burnout among healthcare workers. But few studies have empirically examined the factors driving these outcomes in Africa. Our study examined associations between perceived preparedness to respond to the COVID-19 pandemic and healthcare worker stress and burnout and identified potential mediating factors among healthcare workers in Ghana. METHODS: Healthcare workers in Ghana completed a cross-sectional self-administered online survey from April to May 2020; 414 and 409 completed stress and burnout questions, respectively. Perceived preparedness, stress, and burnout were measured using validated psychosocial scales. We assessed associations using linear regressions with robust standard errors. RESULTS: The average score for preparedness was 24 (SD = 8.8), 16.3 (SD = 5.9) for stress, and 37.4 (SD = 15.5) for burnout. In multivariate analysis, healthcare workers who felt somewhat prepared and prepared had lower stress (β = -1.89, 95% CI: -3.49 to -0.30 and β = -2.66, 95% CI: -4.48 to -0.84) and burnout (β = -7.74, 95% CI: -11.8 to -3.64 and β = -9.25, 95% CI: -14.1 to -4.41) scores than those who did not feel prepared. Appreciation from management and family support were associated with lower stress and burnout, while fear of infection was associated with higher stress and burnout. Fear of infection partially mediated the relationship between perceived preparedness and stress/burnout, accounting for about 16 to 17% of the effect. CONCLUSIONS: Low perceived preparedness to respond to COVID-19 increases stress and burnout, and this is partly through fear of infection. Interventions, incentives, and health systemic changes to increase healthcare workers' morale and capacity to respond to the pandemic are needed.

) was comparable between intercrops (-14 to 21) and sole legumes (-8 to 23) but smaller than that of sole maize receiving N fertiliser (+7 to +34). With other N inputs (aerial deposition) and outputs (leaching and gaseous losses) unaccounted for, there is uncertainty surrounding the actual amount of soil N balances of the cropping systems, indicating that partial N balances are not reliable indicators of the sustainability of cropping systems. Nevertheless, the systems with legumes seem more attractive due to several non-N benefits. Our results suggest that soybean could be targeted in the SGS and cowpea in the NGS for greater productivity while groundnut is suited to both environments. Grain legumes grown in poorly fertile fields contributed more net N to the soil but growing legumes in fertile fields seems more lucrative due to greater grain and stover yields and non-N benefits.

The purpose of this quantitative-deductive paper is to explore the link amongst customer satisfaction and engagement on social media on repurchase intention in the hospitality industry. The study was conducted on social media because, it is the fastest growing media in history. Data was collected from hotels in the three major business hub cities (Accra, Tamale and Kumasi) in Ghana. A total of 504 valid responses were obtained from respondents in the selected cities. SmartPLS software was used to analyze the data using (PLS-SEM) method. The results show that customer satisfaction has a positive and significant relationship on the dimensions of customer engagement. The three dimensions of customer engagement (contribution, consumption and creation) were found to significantly influence repurchase intention. Finally, two dimensions of engagement (contribution and consumption) were found to mediate the relationship between customer satisfactions and repurchase intention. The study is among the few to combine the COBRA model and Social Exchange Theory to assess the nexus between customers' engagement in an online environment and its linkages with satisfaction and repurchase intentions. Marketers should consider creating posts with photos, videos, and animation that consumers find entertaining and enjoyable, as this stimulates their desire to consume, contribute, and create content on social media pages for hotel brands.

Based on qualitative research conducted in Chikwawa and Phalombe in Malawi, this article discusses how gender relations shape men and women’s access to and participation in agricultural training. It also examines how men and women justify or challenge gender inequalities in relation to access to agricultural information and knowledge. Data on gender and recruitment to and participation in training, barriers to training and access to information as well as farmer to farmer extension models were collected and analysed. A gender relations approach, focusing on power and inequality, was used to analyse the data. The data shows that the perception of men as household heads and women as carers or helpers who are also illiterate and ignorant often has implications on women’s ability to access training and information. Negative stereotypical perceptions about women by their husbands and extension workers militate against women’s access to training and information. Institutional biases within extension systems reproduce gender inequality by reinforcing stereotypical gender norms. Extension officers should be targeted with training on gender responsive adult learning methodologies and gender awareness to help them be more inclusive and sensitive to women’s needs.

BACKGROUND: Acute diarrhoea is a major cause of childhood morbidity and mortality in sub-Saharan Africa. Its microbiological causes and clinico-epidemiological aspects were examined during the dry season 2005/6 in Tamale, urban northern Ghana. METHODS: Stool specimens of 243 children with acute diarrhoea and of 124 control children were collected. Patients were clinically examined, and malaria and anaemia were assessed. Rota-, astro-, noro- and adenoviruses were identified by (RT-) PCR assays. Intestinal parasites were diagnosed by microscopy, stool antigen assays and PCR, and bacteria by culturing methods. RESULTS: Watery stools, fever, weakness, and sunken eyes were the most common symptoms in patients (mean age, 10 months). Malaria occurred in 15% and anaemia in 91%; underweight (22%) and wasting (19%) were frequent. Intestinal micro-organisms were isolated from 77% of patients and 53% of controls (P < 0.0001). The most common pathogens in patients were rotavirus (55%), adenovirus (28%) and norovirus (10%); intestinal parasites (5%) and bacteria (5%) were rare. Rotavirus was the only pathogen found significantly more frequently in patients than in controls (odds ratio 7.7; 95%CI, 4.2-14.2), and was associated with young age, fever and watery stools. Patients without an identified cause of diarrhoea more frequently had symptomatic malaria (25%) than those with diagnosed intestinal pathogens (12%, P = 0.02). CONCLUSION: Rotavirus-infection is the predominant cause of acute childhood diarrhoea in urban northern Ghana. The abundance of putative enteropathogens among controls may indicate prolonged excretion or limited pathogenicity. In this population with a high burden of diarrhoeal and other diseases, sanitation, health education, and rotavirus-vaccination can be expected to have substantial impact on childhood morbidity.

The paper examined the relationship between social media and purchase intention and the mediation role of brand equity within Ghana's fashion industry. The study was quantitative and employed the survey methodology to sample the views of 500 fashion customers. Statistical Package for Social Sciences (SPSS) and the structural equation modelling (SEM) technique were used using AMOS software version 22.0 to determine the hypothesized relationships of the study. The study findings revealed that surveillance, Information sharing and remuneration have significant and positive effects on brand equity. However, the relationship between social interaction and entertainment have negative and insignificant on brand equity. The positive significant relationships proposed to exist between brand equity and consumer purchase intention were all accepted. The findings can contribute to the scant empirical works that social media on brand equity and purchase intention in a single study. Recommendations were further made for management in the clothing industry, policy makers, and future researchers.

Groundwater is the main available freshwater resource and therefore its use, management and sustainability are closely related to the Sustainable Development Goals (SDGs). However, Land Use Land Cover (LULC) and climate change are among the factors impacting groundwater recharge. The use of land-use and climate data in conjunction with hydrological models are valuable tools for assessing these impacts on river basins. This systematic review aimed at assessing the integrated modeling approach for evaluating hydrological processes and groundwater recharge based on LULC and climate change. The analysis is based on 200 peer-reviewed articles indexed in Scopus, and the Web of Science. Continuous research and the development of context-specific groundwater recharge models are essential to increase the long-term viability of water resources in any basin. The long-term impacts of natural and anthropogenic drivers on river basin interactions require integrating knowledge and modeling capabilities across biophysical responses, environmental problems, policies, economics, social, and data.

This paper assesses why participation in markets for small ruminants is relatively low in northern Ghana by analysing the technical and institutional constraints to innovation in smallholder small ruminant production and marketing in Lawra and Nadowli Districts. The results show that the limitations experienced by smallholders, i.e., water shortages during the dry season, high mortality and theft of livestock, persist because of institutional constraints. These include structural limitations related to availability of arable lands, weak support systems for animal production and health services delivery, community values that are skewed towards crop production more than animal husbandry, ineffective traditional and formal structures for justice delivery, and gaps in the interaction between communities and district and national level organizations such as the Ministry of Food and Agriculture, district assemblies, rural banks, and non-governmental organizations as well as traders and butchers. Confronted with such constraints, the strategies that most smallholders have adopted to be resilient entail diversified sources of livelihood, low input use in small ruminant production, and maintaining the herd as a capital stock and insurance. Only a few smallholders (i.e., ‘positive deviants’) engage in market or demand-driven production or exhibit successful strategies in small ruminant husbandry. It is argued in this paper that for the majority of smallholders, market production, which requires high levels of external inputs or intensification of resource use, is not a viable option. The main implications of the study are (1) that other institutional constraints than market access constraints should be addressed, (2) that commercial livestock production should not be idealized as the best or only option (as is being done in many contemporary interventions that aim at incorporating smallholders into commodity value chains), and (3) that different types of small ruminant system innovation pathways should be explored by making use of local positive deviants.