CHALLENGES IN THE SUPPLY OF SCIENCE AND TECHNOLOGY EDUCATION TRAINING PROGRAMS IN THE TVET INSTITUTIONS IN NYANZA REGION, KENYA

The supply of TVET education refers to the amount of education that the stakeholders are willing to supply to its people. The relevance of the supply of TVET education must transform into labour market, which enables people, to renew old skills and develop new ones. The supply of TVET education has been increasing rapidly in relation to meagre resources. The enrollment has been doubling in every five years which is the fastest rate of increase in the world. This has been prompted by the economic growth in respective African countries which needs TVET education. The question is: what are the challenges facing this sector in terms of infrastructure, teachers, students and programmes? The study adopted a descriptive research survey paradigm and the theoretical perspectives are guided by the law of supply of education. The results of the study show that the supply of infrastructure, teachers, students and programmes is inadequate. For example, the adequacy of the training facilities has a mean of 3.175 and a standard deviation of 1.022 also the average score of the respondents’ views on the adequacy of teachers in the departments have a mean of 2.93 and a standard deviation of 1.334 while there is an upward trend in the supply of students. The main challenges were: Inability to pay college fees; Poor entry behavior; Market demand; Negative attitude; Inadequate training facilities; Inadequate teaching staff. The study concluded that the supply of science and technology education in Nyanza region of Kenya remains a serious challenge. The study recommended that all stakeholders should increase their participation in marketing the supply of TVET programs for the benefit of the local communities.  Article visualizations

Optimal Control Problem for Cholera Epidemiology

In this paper, the major objective was to theoretically investigate, proof the existence and local optimality state of singular control by applying L1 type objective function. The objective function L1 has been applied in a Compartmental model since it is linear in the control variables. Generalized Legendre-Clebsch Condition applied showed the existence of singular control for both vaccination and sanitation that are optimal. The condition for local stability of the model was also established and the basic reproductive number assimilated. The disease-free equilibrium of the model is locally asymptotically stable if < 1, and unstable if >1. This means that all interventions applied need to reduce the basic reproductive number to reduce the force of infection

CHALLENGES OF THE INTERNAL EFFICIENCY OF SCIENCE AND TECHNOLOGY EDUCATION TRAINING PROGRAMS IN THE TVET INSTITUTIONS IN NYANZA REGION, KENYA

Globally technical training institutions have been established to promote quality academic and technical-oriented programs. This study was motivated by persistent low enrolment in most TVET programs despite reforms being undertaken by the government to support TVET. The purpose of the study was to analyze the challenges facing leaner’s demand for the science and technology courses in Nyanza Region. The results show that the average teaching workload in the TVET institutions is high at 24 hours per week against the recommended 15hour per week and this has compromised the quality and internal efficiency. The highest teacher/ student ratio was 1:50. This indicated that teachers were overburdened in most cases. In terms of dropout rate; 187 (52.8%) students consider the inability to pay college fees and low entry behavior as the most common challenge causing students to drop out of their training programs in the TVET institutions; more than three-quarters of the training programs have shown moderate average pass-rate and above for the last seven years (2010 to 2016) under study, the highest average pass-rate of 69.0876% was attained by the Institutional Management; with Building and Civil Engineering with an average pass-rate of 54.9487%, Automotive Engineering with an average pass-rate of 42.0523%, Electrical and Electronics Engineering with an average pass-rate of 41.2465% and Mechanical Engineering with the lowest average pass-rate of 33.9714%. Factors affecting academic performance included inadequate teaching staff, inadequate training facilities; low entry behavior. Strategies to improve internal efficiency included hiring more staff and the use of HELB to finance education programmes. The study concluded that there exists inefficiency in the TVET sector and recommends that the government should provide additional resources to the TVET sector.  Article visualizations

Strengthening capacity for monitoring and evaluation through short course training in Kenya

Background: Weak monitoring and evaluation (M&E) systems and limited supply of M&E human resources in Africa signal the need to strengthen M&E capacity. Objectives: This exploratory study evaluated the effect of short course training on professionals’ knowledge and skills in the areas of mixed methods research, systematic review and meta-analysis and general principles of M&E. Methods: A partially mixed concurrent dominant status design including quantitative (multilevel modelling and meta-analyses) and qualitative (thematic content analysis) components was employed to evaluate the impact of a 4-day short course training focusing on these areas. Results: Thirty-five participants participated in the training. Participants experienced an increase in knowledge in the three areas; however, average change in knowledge did not differ across participants’ employment settings. Participants’ self-stated objectives considered as SMART and belonging to a higher level in Bloom’s taxonomy were associated with change in knowledge. Based on comments made by participants, majority intended to apply what they learned to their work; clarity of content delivery was the most liked aspect of the training, and the use of more practical sessions was recommended as a way to improve the training. Conclusions: This study provides preliminary evidence of potential of the use of short course training as an approach to strengthening capacity in M&E in less-developed countries such as Kenya. It underscores the importance of participants’ self-stated objective(s) as an element to be considered in the enhancement of knowledge, attitudes and skills needed for acceptable capacity building in M&E

Modeling the Interruption of the Transmission of Soil-Transmitted Helminths Infections in Kenya: Modeling Deworming, Water, and Sanitation Impacts.

Kenya, just like other countries with endemic soil-transmitted helminths (STH), has conducted regular mass drug administration (MDA) program for the last 5 years among school aged children as a way to reduce STH infections burden in the country. However, the point of interruption of transmission of these infections still remains unclear. In this study, we developed and analyzed an age structured mathematical model to predict the elimination period (i.e., time taken to interrupt STH transmission) of these infections in Kenya. The study utilized a deterministic age structured model of the STH population dynamics under a regular treatment program. The model was applied to three main age groups: pre-school age children (2-4 years), school age children (5-14 years), and adult populations (≥15 years) and compared the impact of two interventions on worm burden and elimination period. The model-simulated results were compared with the 5 year field data from the Kenyan deworming program for all the three types of STH (Ascaris lumbricoides, Trichuris trichiura, and hookworm). The model demonstrated that the reduction of worm burden and elimination period depended heavily on four parameter groups; drug efficacy, number of treatment rounds, MDA and water, sanitation and hygiene (WASH) coverage. The analysis showed that for STH infections to be eliminated using MDA alone in a short time period, 3-monthly MDA plan is desired. However, complementation of MDA with WASH at an optimal (95%) coverage level was most effective. These results are important to the Kenyan STH control program as it will guide the recently launched Breaking Transmission Strategy

Understanding the Risks Factors of Under-Five Child Mortality in Kenya: Random Survival Forest and Accelerated Failure Time Shared Frailty Models

Under-five mortality rates is one of the health indicators of great importance to any country. Kenya is among the countries in the Sub-Saharan Africa with high Under-Five Child Mortality (U5CM) rates. It is therefore important to apply best statistical approaches to establish which factors influence child mortality. This will go a long way to inform the optimal design of health intervention strategies within the country and globally. In this study, Random Survival Forest (RSF) and Accelerated Failure Time Shared Frailty Models have been used to analyze U5CM based on the Kenya Demographic Health Survey (KDHS, 2014) dataset. Akaike Information Criterion (AIC) statistics was used to select the model of best fit. Results obtained from fitting the AFT-shared frailty model, showed that there was presence of unobserved heterogeneity at community level. However, there was no evidence to conclude the existence of unobserved heterogeneity at the household level. Among the variants of the AFT Shared Frailty models analysed, the Log-logistic AFT- model showed that “the sons who have died,” “daughters who have died,” “duration of breastfeeding,” and “months of breastfeeding” had significant influence on the U5CM (p <0.05). The Log-logistic AFT model with Gaussian frailty emerged to be the best model for the U5CM since it had the least Akaike Information Criterion (AIC) statistic. On the other hand, the results from Random Survival Forest, “sons who have died,” “daughters who have died,” “living children plus current pregnancy,” “sex of child,” “duration of breastfeeding,” “number of living children,” and “months of breastfeeding” were ranked as important factors that have influence on the under-five mortality. Furthermore, this study also found out that there was presence of unobserved heterogeneity at community level of clustering. At the household level however, there was no unobserved heterogeneity, hence there was no need for household frailty term

Predictors of HIV prevention knowledge and sexual behaviors among students at Makerere University Kampala, Uganda

Background: Prior reviews argue that unsafe sexual behaviors and poor HIV knowledge significantly increase the probability of acquiring HIV infections among adolescents. This study assessed the predictors of HIV prevention knowledge and sexual behaviors among Makerere university students in Uganda.   Methods: We performed a cross-sectional survey. We performed a normality test using Shapiro Wilk test on knowledge score. Results revealed that knowledge score was not normally distributed. The study used two sample Wilcoxon Rank Sum and Kruskal Wallis Rank tests to assess the effect of HIV knowledge on demographic characteristics and sexual behaviors. Post-hoc tests were conducted using Bonferroni correction. Spearman rank correlation test was used for continuous variables while Chi-square and Fisher’s tests were used for categorical variables to assess the relationship between demographic characteristics and sexual behaviors.     Results: We report results for 1337 students. The mean age was 21.2SD (1.6) and more than half 700(52.4%) were male students. The median HIV prevention knowledge score of students was 13 IQR (11-15) in the range of 0 to 18. Males significantly scored higher than females (13.0 IQR (12-15) vs. 12.0 IQR (10-14) p=0.000), an increase in age was associated with higher knowledge scores (Rho = 0.101, p = 0.000).   Students in the third year of study significantly scored higher than those in the first year, and government-sponsored students scored higher than the privately sponsored students. HIV knowledge was also significantly associated with sexual experience, and condom use at univariate level but insignificant at multiple level analysis. Males were more likely to have ever had sex (31.7% vs. 12.7%) and ever used a condom (63% vs. 55%) than females respectively   Conclusion: Our findings suggest that Makerere University students possessed good knowledge on HIV. There is evidence of an association between student’s knowledge, and demographic characteristics and a few sexual behaviors. Future behavioral and educational programs that target both sexually and non-sexually experienced students should address the gender differences

Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya

Aim: Hypertension and diabetes mellitus (DM) are major causes of morbidity andmortality, with growing burdens in low-income countries where they are underdiag-nosed and undertreated. Advances in machine learning may provide opportunities toenhance diagnostics in settings with limited medical infrastructure. Materials and Methods: A non-interventional study was conducted to develop andvalidate a machine learning algorithm to estimate cardiovascular clinical and labora-tory parameters. At two sites in Kenya, digital retinal fundus photographs were col-lected alongside blood pressure (BP), laboratory measures and medical history. Theperformance of machine learning models, originally trained using data from the UKBiobank, were evaluated for their ability to estimate BP, glycated haemoglobin, esti-mated glomerular filtration rate and diagnoses from fundus images. Results: In total, 301 participants were enrolled. Compared with the UK Biobankpopulation used for algorithm development, participants from Kenya were youngerand would probably report Black/African ethnicity, with a higher body mass indexand prevalence of DM and hypertension. The mean absolute error was comparable orslightly greater for systolic BP, diastolic BP, glycated haemoglobin and estimated glo-merular filtration rate. The model trained to identify DM had an area under thereceiver operating curve of 0.762 (0.818 in the UK Biobank) and the hypertensionmodel had an area under the receiver operating curve of 0.765 (0.738 in the UKBiobank). Conclusions: In a Kenyan population, machine learning models estimated cardiovas-cular parameters with comparable or slightly lower accuracy than in the populationwhere they were trained, suggesting model recalibration may be appropriate. Thisstudy represents an incremental step toward leveraging machine learning to makeearly cardiovascular screening more accessible, particularly in resource-limitedsettings

Statistical Regression Model of Water, Sanitation, and Hygiene; Treatment Coverage; and Environmental Influences on School-Level Soil-Transmitted Helminths and Schistosome Prevalence in Kenya: Secondary Analysis of the National Deworming Program Data.

According to the Kenya National School-Based Deworming program launched in 2012 and implemented for the first 5 years (2012-2017), the prevalence of soil-transmitted helminths (STH) and schistosomiasis substantially reduced over the mentioned period among the surveyed schools. However, this reduction is heterogeneous. In this study, we aimed to determine the factors associated with the 5-year school-level infection prevalence and relative reduction (RR) in prevalence in Kenya following the implementation of the program. Multiple variables related to treatment, water, sanitation, and hygiene (WASH) and environmental factors were assembled and included in mixed-effects linear regression models to identify key determinants of the school location STH and schistosomiasis prevalence and RR. Reduced prevalence of Ascaris lumbricoides was associated with low ( 75%) reported coverage of a household improved water source. Reduced Schistosoma haematobium was associated with high aridity index. Analysis indicated that a combination of factors, including the number of treatment rounds, multiple related program interventions, community- and school-level WASH, and several environmental factors had a major influence on the school-level infection transmission and reduction

Comparison of least absolute shrinkage and selection operator and maximum likelihood estimators to establish determinants of immunization in Trans - Nzoia County

The client factors that influence under-five child guardian compliance to the immunization schedule are interlinked based on household characteristics, socioeconomic status, and maternal health practices. An incentive to motivate the mothers to prioritize their child’s health practices especially on vaccination, works perfectly towards the achievement of full immunization coverage. A randomly sampled study carried out within Weonia Location–Trans Nzoia County in March 2014 with target population of under-five children showed the vital role an incentive innovation plays towards immunization coverage. Multinomial logistic regression model was used to analyze the determinant of partial or none-immunized and the parameters estimated using the maximum likelihood estimator (MLE) and the shrinkage estimator-Least Absolute Shrinkage and Selection Operator (LASSO). The shrinkage estimator method gave a sparse model that was easy to interpret and increased the estimated predictability accuracy. Maternal health practices and access to a motivating intervention are significant factors that ensure a guardian’s compliance to their child immunization