A Dimensional student enrollment prediction model: case of Strathmore University

Thesis submitted in partial fulfillment of the requirements for the Degree of Master of Science in Information Technology (MSIT) at Strathmore UniversityThe rate of student admissions within most Kenyan Universities has thus far been met with a corresponding uncertainty in budgetary allocation. Additionally, the increase of most applicants not being enrolled has led to lower institution yield. Due to the uncertainty of the quantity of students to be enrolled, planning and budgetary issues have arisen as stated earlier. Departments in charge of recruiting students are left to speculate the numbers likely to turn up. This in most cases is not accurate since it results into gaps in the allocated budgets and straining of resources. Currently, in Kenya, there is no institutions of higher learning that has a reliable means of predicting the expected institutional yield. Rather, academic management systems exist and are used to manage daily academic routines. These systems are served by transactional databases which are subject to being edited frequently and as such lack the capability of archiving histories of instances of the data within these databases; which makes them unsuitable for carrying out analysis on enrollment prediction. As such, a dimensional enrollment prediction model is proposed so as to aid in forecasting; not only of how many admitted students will be enrolled but also particular individuals who could show up for the purposes of follow-up activities. The inputs to the proposed enrollment prediction system were sourced from dimensional data stored in a data warehouse regarding to student details as per the admission as well as snapshot data of third party satisfaction index from accredited sources. The proposed system then transforms this data into dimensional data by adding a time variant to it and then passing the data through a neural network. The resultant model is then to be used in predicting students’ enrollment. The proposed model was tested for accuracy using the precision, recall ratio and the F-score Measure. The model’s accuracy was considerably high with an accuracy of 71.39% with a precision of 0.72. The average recall ratio was 0.71 and while F-score of 0.71 as well was obtained. In relation to some of the works reviewed the proposed model was a bit lower accuracy due the dataset used that was noisy as fetched from real student transactional databases

The Relationship Between Urbanization and Precipitation in Kisumu City: Co-Integration Analysis

The work done in this study thesis is by empirical analysis. If two series are integrated of the same order, then the two series are said to be co-integrated and this is shown in the two series where the population series being non stationary is made stationary by third differencing and the stationary rainfall series subjected to the same order of differencing to achieve the co-integration rule. The OLS method was used and then the model parameters tested for adequacy. A linear Error Correction Model was fitted and evidence that a short term relationship between the rainfall and population series is seen to exist. Also, a high threshold value is observed at the second lag. A high R squared value of 0.9881 is an indication that the model fits well to the data.  A small p-value also indicates that the model is highly significant. Hence, it is recommended that a close analysis of population growth rates be analyzed to aid in the prediction of the rainfall rates movements. Keywords: OLS, Co-integrated, differencing, Error Correction Model, p-value

Mobile phone-delivered reminders and incentives to improve childhood immunisation coverage and timeliness in Kenya (M-SIMU): a cluster randomised controlled trial

Background As mobile phone access continues to expand globally, opportunities exist to leverage these technologies to support demand for immunisation services and improve vaccine coverage. We aimed to assess whether short message service (SMS) reminders and monetary incentives can improve immunisation uptake in Kenya. Methods In this cluster-randomised controlled trial, villages were randomly and evenly allocated to four groups: control, SMS only, SMS plus a 75 Kenya Shilling (KES) incentive, and SMS plus 200 KES (85 KES = USD$1). Caregivers were eligible if they had a child younger than 5 weeks who had not yet received a first dose of pentavalent vaccine. Participants in the intervention groups received SMS reminders before scheduled pentavalent and measles immunisation visits. Participants in incentive groups, additionally, received money if their child was timely immunised (immunisation within 2 weeks of the due date). Caregivers and interviewers were not masked. The proportion of fully immunised children (receiving BCG, three doses of polio vaccine, three doses of pentavalent vaccine, and measles vaccine) by 12 months of age constituted the primary outcome and was analysed with logbinomial regression and General Estimating Equations to account for correlation within clusters. This trial is registered with ClinicalTrials.gov, number NCT01878435. Findings Between Oct 14, 2013, and Oct 17, 2014, we enrolled 2018 caregivers and their infants from 152 villages into the following four groups: control (n=489), SMS only (n=476), SMS plus 75 KES (n=562), and SMS plus 200 KES (n=491). Overall, 1375 (86%) of 1600 children who were successfully followed up achieved the primary outcome, full immunisation by 12 months of age (296 [82%] of 360 control participants, 332 [86%] of 388 SMS only participants, 383 [86%] of 446 SMS plus 75 KES participants, and 364 [90%] of 406 SMS plus 200 KES participants). Children in the SMS plus 200 KES group were significantly more likely to achieve full immunisation at 12 months of age (relative risk 1·09, 95% CI 1·02–1·16, p=0·014) than children in the control group. Interpretation In a setting with high baseline immunisation coverage levels, SMS reminders coupled with incentives significantly improved immunisation coverage and timeliness. Given that global immunisation coverage levels have stagnated around 85%, the use of incentives might be one option to reach the remaining 15%

Experiences and lessons learned from the real-world implementation of an HIV recent infection testing algorithm in three routine service-delivery settings in Kenya and Zimbabwe.

INTRODUCTION: Testing for recent HIV infection can distinguish recently acquired infection from long-standing infections. Given current interest in the implementation of recent infection testing algorithms (RITA), we report our experiences in implementing a RITA in three pilot studies and highlight important issues to consider when conducting recency testing in routine settings. METHODS: We applied a RITA, incorporating a limited antigen (LAg) avidity assay, in different routine HIV service-delivery settings in 2018: antenatal care clinics in Siaya County, Kenya, HIV testing and counselling facilities in Nairobi, Kenya, and female sex workers clinics in Zimbabwe. Discussions were conducted with study coordinators, laboratory leads, and facility-based stakeholders to evaluate experiences and lessons learned in relation to implementing recency testing. RESULTS: In Siaya County 10/426 (2.3%) of women testing HIV positive were classified as recent, compared to 46/530 (8.7%) of women and men in Nairobi and 33/313 (10.5%) of female sex workers in Zimbabwe. Across the study setting, we observed differences in acceptance, transport and storage of dried blood spot (DBS) or venous blood samples. For example, the acceptance rate when testing venous blood was 11% lower than when using DBS. Integrating our study into existing services ensured a quick start of the study and kept the amount of additional resources required low. From a laboratory perspective, the LAg avidity assay was initially difficult to operationalise, but developing a network of laboratories and experts to work together helped to improve this. A challenge that was not overcome was the returning of RITA test results to clients. This was due to delays in laboratory testing, the need for multiple test results to satisfy the RITA, difficulties in aligning clinic visits, and participants opting not to return for test results. CONCLUSION: We completed three pilot studies using HIV recency testing based on a RITA in Kenya and Zimbabwe. The main lessons we learned were related to sample collection and handling, LAg avidity assay performance, integration into existing services and returning of test results to participants. Our real-world experience could provide helpful guidance to people currently working on the implementation of HIV recency testing in sub-Saharan Africa

Can HIV recent infection surveillance help us better understand where primary prevention efforts should be targeted? Results of three pilots integrating a recent infection testing algorithm into routine programme activities in Kenya and Zimbabwe.

INTRODUCTION: Surveillance of recent HIV infections in national testing services has the potential to inform primary prevention programming activities. Focusing on procedures required to accurately determine recent infection, and the potential for recent infection surveillance to inform prevention efforts, we present the results of three independent but linked pilots of recency testing. METHODS: To distinguish recently acquired HIV infection from long-standing infection, in 2018 we applied a Recent Infection Testing Algorithm that combined a laboratory-based Limiting Antigen Avidity Enzyme Immunoassay with clinical information (viral-load; history of prior HIV diagnosis; antiretroviral therapy-exposure). We explored potential misclassification of test results and analysed the characteristics of participants with recent infection. We applied the algorithm in antenatal clinics providing prevention of mother-to-child transmission services in Siaya County, Kenya, outreach sites serving female sex workers in Zimbabwe, and routine HIV testing and counselling facilities in Nairobi, Kenya. In Nairobi, we also conducted recency testing among partners of HIV-positive participants. RESULTS: In Siaya County, 2.3% (10/426) of HIV-positive pregnant women were classified as recent. A risk factor analysis comparing women testing recent with those testing HIV-negative found women in their first trimester were significantly more likely to test recent than those in their second or third trimester. In Zimbabwe, 10.5% (33/313) of female sex workers testing HIV-positive through the outreach programme were classified recent. A risk factor analysis of women testing recent versus those testing HIV-negative, found no strong evidence of an association with recent infection. In Nairobi, among 532 HIV-positive women and men, 8.6% (46) were classified recent. Among partners of participants, almost a quarter of those who tested HIV-positive were classified as recent (23.8%; 5/21). In all three settings, the inclusion of clinical information helped improve the positive predictive value of recent infection testing by removing cases that were likely misclassified. CONCLUSIONS: We successfully identified recently acquired infections among persons testing HIV-positive in routine testing settings and highlight the importance of incorporating additional information to accurately classify recent infection. We identified a number of groups with a significantly higher proportion of recent infection, suggesting recent infection surveillance, when rolled-out nationally, may help in further targeting primary prevention efforts

Anti-Severe Acute Respiratory Syndrome Coronavirus 2 Immunoglobulin G Antibody Seroprevalence Among Truck Drivers and Assistants in Kenya.

In October 2020, anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin G seroprevalence among truck drivers and their assistants (TDA) in Kenya was 42.3%, higher than among healthcare workers and blood donors. Truck drivers and their assistants transport essential supplies during the coronavirus disease 2019 pandemic, placing them at increased risk of being infected and of transmitting SARS-CoV-2 over a wide geographical area

Rainforest alliance certification of Kenyan tea farms: a contribution to sustainability or tokenism?

An Environmental Management System (EMS) is an approach organisations can use to structure their management to prevent or minimise adverse environmental and social impacts. Rainforest Alliance Certification (RFC), one example of an EMS, was adopted by a number of Kenyan tea farms in 2007 to promote sustainable tea production. It addresses the three pillars of sustainable development (environmental, economic and social) and as such is suited to tea farming which is characterised by job insecurity, strenuous work conditions, child labour and environmental resource degradation. As numbers of EMSs and pressures on organisations to adopt them increase, it is imperative to evaluate their contribution to achieving sustainability. In this study, a mix of methods - qualitative interviews with farm managers and government officials, quantitative interviews with farm workers, biophysical observation and secondary data - were used to compare agri-environmental and socio-economic indicators between certified and non-certified tea farms. Analysis of the results indicates that the RFC brings some important social and environmental benefits, for example, improved work conditions and to a limited extent, natural resource conservation. Certified tea farms maintain riparian strips to protect natural resources and also monitor their water quality more frequently than non-certified tea farms. However, there were no significant differences in some aspects including employees‘ housing conditions and source of cooking energy. Although there are important benefits from adopting the RFC, there are obvious gaps between certification and sustainability which need to be addressed if full benefits are to be achieved

Rainforest Alliance Certification of Kenyan tea farms: a contribution to sustainability or tokenism?

An Environmental Management System (EMS) refers to a set of guidelines that organisations can use to structure their management to prevent or minimise adverse environmental and social impacts. Rainforest Alliance Certification (RFC), one example of an EMS, was adopted by some Kenyan tea farms in 2007 to promote sustainable tea production. RFC addresses the three pillars of sustainable development (environmental, economic and social) and as such is suited to tea farming which has been characterised by environmental resource degradation, job insecurity, strenuous work conditions and child labour. To study the effect of certification, interviews with farm managers, and farm workers on certified and non-certified tea farms were carried out. Sets of agri-environmental and socio-economic indicators were then compared using these data. The results indicate that the RFC brings some important social and environmental benefits to certified tea farms. These benefits include improved work conditions and to a limited extent, natural resource conservation. However, there were no differences between certified and non-certified farms in a number of aspects, including access to health services and employee living conditions. Two main conclusions can be drawn. First, although there are important sustainability benefits from adopting the RFC, more efforts are still needed to achieve sustainability on certified farms. Secondly, there are sufficient benefits to indicate that all tea farms should be encouraged to become certified

Impact of mobile phone delivered reminders and unconditional incentives on measles-containing vaccine timeliness and coverage: a randomised controlled trial in western Kenya

Introduction Short message service (SMS) reminders coupled with a small monetary incentive conditioned on prompt vaccination have been shown to improve first-dose measles-containing vaccine (MCV1) uptake. We assessed whether SMS reminders and unconditional monetary incentives—more amenable to programmatic implementation—can improve MCV1 uptake in Kenya.Methods Caregivers of eligible infants aged 6–8 months were enrolled into an individually randomised controlled trial and assigned to receive either: no intervention (control), two SMS reminders (SMS) sent 3 days, and 1 day before the scheduled MCV1 date, or SMS reminders coupled with a Kenya Shilling (KES) 150 incentive (SMS +150 KES) sent 3 days before the scheduled MCV1 date. Study staff conducted a household follow-up visit at age 12 months to ascertain vaccination status. Log-binomial regression was used to estimate the relative and absolute difference in MCV1 timely coverage (by age 10 months), the primary outcome.Results Between 6 December 2016 and 31 March 2017, 179 infants were enrolled into each of the three study arms. Follow-up visits were completed between 19 April 2017 and 8 October 2017 for control (n=170), SMS (n=157) and SMS + 150 KES (n=158) children. MCV1 timely coverage was 68% among control arm infants compared with 78% in each intervention arm. This represented a non-statistically significant increase in the SMS arm (adjusted relative risk 1.13; 95% CI 0.99 to 1.30; p=0.070; adjusted risk difference 9.2%; 95% CI: −0.6 to 19.0%; p=0.066), but a statistically significant increase in the SMS + 150 KES arm (1.16; 95% CI 1.01 to 1.32; p=0.035; 10.6%; 95% CI 0.8 to 20.3%; p=0.034).Conclusion These findings suggest that the effect of SMS reminders coupled with a small unconditional monetary incentive on MCV1 uptake is comparable to that of SMS reminders alone, limiting their utility. Further studies in the absence of unexpected supply-side constraints are needed.Trial registration number NCT0290464

The Natural Step environmental management system performance : an evaluation of eight organisations in Canterbury, New Zealand

A qualitative evaluation of the performance of The Natural Step (TNS) implemented by eight Canterbury based organisations was undertaken. An evaluative framework containing a series of questions was formulated to facilitate an analysis of the goals, implementation and performance of TNS in the participant organisations. The research identified that TNS is an effective ‘ems’ that provides the framework for improved sustainability performance. It was found to be flexible, adaptable to a variety of organisational structures, however not without limitations in terms of documentation and auditing