Breaking the culture of ethnic hostility in Kenya

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Modalities of Healthcare Payment and their Consequences – A Qualitative Study on Kenyan Doctors

Introduction: The Kenyan government has put a spirited reform to ensure all Kenyans get universal healthcare. This has led to restructuring of several entities among them the health insurance industry. This is geared at alleviating the burden of catastrophic expenditure on health from the poor Kenyans. However, insurance uptake remains at less than a quarter of the population with many Kenyans still paying for healthcare out-of-pocket. These out-of-pocket payers often don’t afford the ever-increasing cost of healthcare in Kenya. This study looked at how doctors deal with patients given their modality of payment. Methodology: This was an online based survey that was distributed to Kenyan doctors via email by Kenya Medical Association. The survey sought information from the respondents on how they dealt with patients given their modality of payment. In addition, respondents were asked to provide an example of a case they had dealt with that touched on each payment modality. Results: Respondents gave their experiences where insurance had influenced their clinical decisions. Codes developed from the prose were; “inability to pay”, “harmful to the patient”, “changed the prescription” among others Health insurance played a crucial role whenever respondents made decisions. Top on the list of things that the majority indicated would be considered is insurance status and/or their ability of patients to pay for the services. Conclusion: Respondents are stuck in a limbo; striving to give the best care to patients but limited by the patients’ inability to pay. In explaining their experiences, respondents explain a situation where they intend to offer the best, but patients cannot afford. This especially so for those without health insurance who end up either not getting services or at the very best, get inferior service

IMPACT OF PROJECT INITIATION ON PERFORMANCE OF OUTPUT-BASED FUNDED SABASABA URBAN WATER SUPPLY PROJECT

Sabasaba urban water supply project was undertaken in order to increase the number of people in low-income areas within Murang’a County with access to improved water supply; to enable them to have clean water at their doorstep. In carrying out the project, World Bank employed Output-Based Aid scheme to make sure the project achieves its goals. Output-Based Aid funds predetermined project outputs unlike the conventional way of funding inputs. It serves to ensure prudent utilization of funds by shifting performance risk to the organization mandated to deliver services; it also does so by linking outputs to the ultimate payments; hence transparency during project implementation. The study sought to examine the influence of project initiation, project planning, project implementation, and project monitoring on the project performance of Output-Based Aid funded Sabasaba urban water supply project. The study adopted value chain and resource-based theories. A predictive correlation design was used. The target population was 56 employees drawn from Murang’a South Water and Sewerage Company which is the implementing agency for Sabasaba water supply project. A structured questionnaire was used to collect data from the respondents. The study results were analysed using SPSS.  The study found that the project initiation had a statistically significant influence on the project performance.  The findings revealed that a unit change in the project initiation would lead to 0.404 changes in the project performance holding the other independent variables constant.  Article visualizations

Using Feature Selection Methods to Discover Common Users’ Preferences for Online Recommender Systems

Recommender systems have taken over user’s choice to choose the items/services they want from online markets, where lots of merchandise is traded. Collaborative filtering-based recommender systems uses user opinions and preferences. Determination of commonly used attributes that influence preferences used for prediction and subsequent recommendation of unknown or new items to users is a significant objective while developing recommender engines.  In conventional systems, study of user behavior to know their dis/like over items would be carried-out. In this paper, presents feature selection methods to mine such preferences through selection of high influencing attributes of the items. In machine learning, feature selection is used as a data pre-processing method but extended its use on this work to achieve two objectives; removal of redundant, uninformative features and for selecting formative, relevant features based on the response variable. The latter objective, was suggested to identify and determine the frequent and shared features that would be preferred mostly by marketplace online users as they express their preferences. The dataset used for experimentation and determination was synthetic dataset.  The Jupyter Notebook™ using python was used to run the experiments. Results showed that given a number of formative features, there were those selected, with high influence to the response variable. Evidence showed that different feature selection methods resulted with different feature scores, and intrinsic method had the best overall results with 85% model accuracy. Selected features were used as frequently preferred attributes that influence users’ preferences

Using Feature Selection Methods to Discover Common Users’ Preferences for Online Recommender Systems

Recommender systems have taken over user’s choice to choose the items/services they want from online markets, where lots of merchandise is traded. Collaborative filtering-based recommender systems uses user opinions and preferences. Determination of commonly used attributes that influence preferences used for prediction and subsequent recommendation of unknown or new items to users is a significant objective while developing recommender engines.  In conventional systems, study of user behavior to know their dis/like over items would be carried-out. In this paper, presents feature selection methods to mine such preferences through selection of high influencing attributes of the items. In machine learning, feature selection is used as a data pre-processing method but extended its use on this work to achieve two objectives; removal of redundant, uninformative features and for selecting formative, relevant features based on the response variable. The latter objective, was suggested to identify and determine the frequent and shared features that would be preferred mostly by marketplace online users as they express their preferences. The dataset used for experimentation and determination was synthetic dataset.  The Jupyter Notebook™ using python was used to run the experiments. Results showed that given a number of formative features, there were those selected, with high influence to the response variable. Evidence showed that different feature selection methods resulted with different feature scores, and intrinsic method had the best overall results with 85% model accuracy. Selected features were used as frequently preferred attributes that influence users’ preferences

Building on illegal value chains to achieve sustainable management of natural resources? The case of indigenous aloe exploitation and trade in Baringo, Kenya: The case of indigenous aloe exploitation and trade in Baringo, Kenya

International audienceThis paper explores the consequences of ignoring pre-existing un-official and illegal networks for external interventions with approaches to sustain-able management of natural resources in marginal-ized areas of the developing world. To do so, it as-sesses the effects of a public Research & Develop-ment (R&D) intervention aimed at promoting sustain-able exploitation and trade of aloe-based products in the semi-arid Baringo County (Kenya), and how it interacted with an existing illegal supply chain dedi-cated to the exploitation of indigenous aloe species. Data were collected through a qualitative and partici-patory assessment that was conducted between April and November 2012, using an analytical framework and guidelines derived from the innovation system perspective. The study shows that geographical dis-parities in the effect of external intervention are the result of unplanned interactions between project stakeholders and actors from the illegal supply chain. The Baringo aloe case suggests that networks in-volved in illegal trade of natural resources should not be ignored or sidelined by R&D interventions but should on the contrary be supported to allow them to evolve towards certified trade

Mieux évaluer et accompagner l'innovation agricole en Afrique. Leçons d'une analyse transversale de 13 cas d'études

Cet article présente les résultats clés tirés de l'analyse transversale de 13 expériences d'innovation agricole menées au Bénin, au Kenya et en Afrique du Sud. L'évaluation a utilisé un cadre analytique commun inspiré de l'approche systèmes d'innovation pour comprendre comment l'innovation a évolué au fil du temps via les interactions entre différents acteurs et sous l'effet d'éléments déclencheurs et moteurs internes et externes. Menée de manière participative par des équipes mixtes de chercheurs, d'étudiants et d'acteurs locaux, elle s'est fondée sur des entretiens semi-structurés, des focus groupes et des ateliers multi-acteurs. Les 13 cas portent sur une diversité d'expériences en termes de domaines, types, échelles, durée, initiateurs de l'innovation et acteurs concernés. Les résultats montrent la multiplicité et le rôle des acteurs impliqués dans l'innovation, la nature des déclencheurs et moteurs de l'innovation. Ils montrent aussi l'importance de la prise en compte du temps long pour comprendre les processus d'innovation. Ils montrent enfin l'influence tant positive que parfois problématique des interventions externes sur les processus d'innovation, et en particulier les difficultés à institutionnaliser l'innovation au-delà des interventions ou à interagir avec les dynamiques locales d'innovation. L'article propose diverses voies pour améliorer tant l'évaluation que l'accompagnement des processus d'innovation. Cela concerne en particulier la conception et le financement des interventions externes. Cela concerne aussi l'acquisition des compétences et capacités indispensables à la mise en oeuvre dans la durée d'approches ouvertes et souples de conception, renforçant chaque fois que possible les initiatives existantes des acteurs locaux. (Résumé d'auteur

Survey of urban mosquitoes species (Diptera: Culicidae) with focus on waste water channels as larval habitats in Nairobi industrial area, Kenya

Background: A cross sectional study to establish the levels of heavy metals and other potentially harmful elements (PHEs)present in samples obtained from selected open waste water channels in Nairobi industrial area (Kenya) was carried out. The waste water channels selected were those near the factories or those directly discharging from factories. The samples collected included mosquitoes (larvae and adults), waste water, green algae, and soil. Unmaintained open waste water channels are among the man made features that enhance the breeding of urban mosquitoes because they tend to have overgrown vegetation and trapped solid wastes which slow or inhibit the waste water flow. Different mosquito species have previously transmitted arboviruses including those responsible for dangerous fevers such as West Nile, Rift Valley, Zika, Dengue, Yellow, and Chikungunya among others in different parts of the world. The study area (Nairobi industrial area) neighbors several densely populated informal human settlements. This paper specifically reports on composition and distribution of mosquito species obtained from the study area.Methods: The fourth instars mosquito larvae were collected from waste water channels using the standard dipping method. Adult mosquitoes were trapped using the center for disease control and prevention (CDC) light traps. Purposive random sampling for mosquito adults and larvae was carried out in industrial premises and waste water channels respectively at seven locations. This involved selecting sampling sites from which mosquito samples were likely to be obtained. The mosquitoes were then microscopically identified using taxonomic keys for the Ethiopian and East African region.Results: Out of 2,926 adult mosquitoes trapped, 12 species were identified including Cx. pipiens (95%); Cx. Vansomereni (2.6%); Cx. zombaensis (1.4%); Cx. univittatus (0.34%); Cx. theileri (0.21%); Ae. aegpti (0.14%); An. maculipalpis (0.03%); An. squamosus (0.03%) and other culicid species (0.20%). Of these adult mosquitoes, 94% (2753/2926) were females and 6% (173/2926) were males giving a male: female ratio of 1: 16 when using CDC traps. Of the 4,679 mosquito larvae scooped from the waste water channels, 4 species were identified including Cx. pipiens (99.34%); Cx. vansomereni (0.51%); Toxorhynchites brevipalpis (0.13%) and Aedes mosquito (0.02%).Conclusion: The majority of mosquito species obtained were culicid, Culex pipiens for both adults and larvae. A few Anopheles and Aedes populations were obtained. Unmaintained open waste water channels seen\med to enhance the breeding of urban mosquitoes in the study area. The ecology of these mosquitoes should be studied further to enhance surveillance and controlin order to minimize the risk of mosquito borne viral infections or any other re-emerging mosquito-borne infections to the residents of Nairobi, in particular those living in the informal settlements near Nairobi industrial area, Kenya.Keywords: urban, mosquitoes, Culex pipiens, waste water, industrial area, NairobiAfr J Health Sci. 2017; 30(2):120-13