http://localhost/xmlui/handle/123456789/1154 2026-04-06T17:17:30Z http://localhost/xmlui/handle/123456789/6930 Mutational and Phylogenetic Analyses of Antifolate and Artemisinin Resistance in Plasmodium falciparum Dried Blood Spots Obtained from Patients Attending Three Hospitals of Eritrea Mukhongo, Harriet Natabona Malaria causes approximately 200 million infections and 500,000 deaths yearly. The emergence and spread of antimalarial drug resistance is a major challenge towards control efforts globally. Nonetheless, integrated vector control methods have reduced malaria transmission, resulting in decreased human-parasite reservoirs and lessened spread of antimalarial drug resistance. Eritrea, located in the horn of Africa, has witnessed a considerable reduction in malaria deaths from 405 to 4 between 1998 and 2023. This is attributed to a combination of community health campaigns, prompt case management, and integrated vector management. In Eritrea, Sulfadoxine-Pyrimethamine was previously used as a first-line antifolate treatment, and currently, artesunate is the first-line artemisinin treatment. Due to limited molecular data on these antifolate and artemisinin treatments, the first objective of this study, was to determine antifolate resistance-associated genetic mutations in codon position K540E of Pf-DHPS gene, and codon positions N51I, C59R and S108N of Pf-DHFR gene. The second objective, was to determine artemisinin resistance-associated genetic mutations in codon positions Y493H, R539T, I543T, and C580Y of Pf-K13 gene. The third objective, was to determine the phylogenetic relationships between the genetic markers sampled in this study, and corresponding globally identified genetic markers from other studies. Sample size was determined using Fisher’s formula, and based on patient availability, inclusion and exclusion criteria. Nineteen dried blood spot samples were collected from patients infected with P. falciparum mono-infection, visiting Adi Quala, Keren, and Gash Barka hospitals. Genomic DNA extraction, nested-PCR amplification and Sanger-sequencing of Pf-DHFR, Pf-DHPS, and Pf-K13 partial gene regions was achieved for nine dried blood spots. Sequence contig assembly, genetic mutation visualization, and phylogenetic analyses were performed in CLC main workbench v21.0.4, Jalview v2.11.1.4, and MEGAv7.0. Mutational analyses identified the single-mutant K540E of Pf-DHPS in Adi Quala (n=1), Keren (n=1), and Gash Barka (n=1); double-mutant N51I+S108NI of Pf-DHFR in Adi Quala (n=2); triple-mutant S108N+C59R+N51I of Pf-DHFR in Keren (n=1); mixed-mutant (S108N+N51I+K540E) of Pf-DHFR and Pf-DHPS in Gash Barka (n=1). These findings suggested the likely presence of the quintuple-mutant (S108N, C59R, N51I+A437G, K540E) of Pf-DHFR and Pf-DHPS, associated with full resistance, and used to predict Sulfadoxine-Pyrimethamine treatment failure. Mutational analyses of Pf-K13 identified wild-type haplotypes of Y493Y+R539R+I543I+C580C in Adi Quala (n=2) and wild-types of C580C in Keren (n=1) and Gash Barka (n=3). These findings suggested the likely absence of artemisinin resistance, and predicted artesunate was still effective for malaria treatment. The Dhfr phylogeny predominantly identified the double-mutant haplotype (N51I + S108N) at an estimated distribution ranging from low to high prevalence in Western Kenya (p=0.3%), Myanmar (p=2.5%), India (p=7%) and Sudan (p=80%). The K540E mutation was predominantly identified in the Dhps phylogeny, at an estimated distribution ranging from low to moderate prevalence in Ghana (p=3.4%), Equatorial Guinea (p=5.1%), and Sudan (p=65.7%). These analyses suggested a low to moderate spread of antifolate resistance. The K13 phylogeny predominantly identified wild-type haplotype (Y493Y+R539R +I543I +C580C) at an estimated distribution of high prevalence in Ghana (p=100%), Nigeria (p=96.9%), Niger (p=90%) and Angola (p=>80%). This suggested a limited spread of artemisinin resistance. Future recommendations from this study should estimate the mutational prevalence and phylogenetic distribution of antifolate and artemisinin resistance in a larger sample population. MSc in Bioinformatics and Molecular Biology 2026-03-31T00:00:00Z http://localhost/xmlui/handle/123456789/6929 Devolved Governance and Social Transformation in North Eastern Region, Kenya Adan, Abdirahman Mohamed Social change is increasingly recognized as a critical phenomenon in public administration, influenced by shifts in social, fiscal, and political structures that move governance from centralized to decentralized systems. Despite its significance, limited research exists in the Kenyan context examining the relationship between governance structures and community social transformation. The general objective of the study was to investigate the influence of devolved governance on social transformation in the North Eastern region in Kenya. The study also sought to determine the influence of administrative structure, fiscal structure, political structure and socio-cultural structure on social transformation in North Eastern region in Kenya. The study further sought to assess the moderating influence of leadership on the relationship between devolved governance structure and social transformation in North Eastern region in Kenya. The study was guided by the theory of change, alongside management, cognitive engagement, sequential decentralization, souffle, and general systems theories. Adopting a positivist philosophical framework, the research employed an explanatory and descriptive cross-sectional design. The unit of analysis comprised the counties of Garissa, Wajir, and Mandera, while the unit of observation included senior county employees in Job Groups M to S involved in strategic decision-making. Primary data were collected using self-administered questionnaires and analyzed using SPSS version 25. Normality, heteroscedasticity, and autocorrelation were tested with the Jarque-Bera statistic, while exploratory factor analysis and moderated multiple regression were applied to examine relationships between devolved governance, leadership, and social transformation. The findings revealed that administrative, fiscal, political, and socio-cultural structures each have a positive and significant effect on social transformation in the North Eastern region. Leadership was found to positively moderate the relationship between governance structures and social transformation. Specifically, administrative autonomy in contracts, recruitment, and strategic decision-making, robust fiscal structures, accountable political systems, and culturally sensitive socio-cultural structures all contributed to promoting social transformation. Overall, the study concludes that devolved governance is a critical driver of social transformation in the North Eastern region of Kenya, and its impact is enhanced by effective leadership. The study recommends strengthening administrative, fiscal, political, and socio-cultural structures to enhance social transformation in North Eastern Kenya through improved autonomy, transparency, inclusivity, and community participation. Capacity-building, clear policies, accountable financial practices, and culturally responsive programs are essential for effective implementation and sustainable development outcomes. The study further recommends that future research adopt longitudinal or mixed-method designs to examine how governance and leadership reforms influence social transformation over time. Further, the study recommends that future research conduct comparative, multidisciplinary investigations across regions to examine broader dimensions of devolved governance, beyond social transformation, to generate comprehensive evidence for informed policy decisions. PhD in Leadership and Governance 2026-03-31T00:00:00Z http://localhost/xmlui/handle/123456789/6927 Determinants of Surgical Site Infections among Post Caesarean Section Women at Thika Level 5 Hospital, Kiambu County Ndege, Jane Wanjiku Surgical site infection refers to an infection that occurs at or near a surgical incision site within 30 days post operation. Caesarean section is one of the most performed surgical procedures carried out in obstetrics and constitutes about 15% of all deliveries globally, with Latin America being the highest at 29.2%. The study aimed to assess the determinants of surgical site infection following caesarean section among women at Thika level 5 hospital. The study design was a mixed unmatched case-control study which followed women who had undergone caesarean section in maternity unit at Thika Level 5 Hospital and who had or did not have surgical site infection from delivery up to two weeks post-delivery and nurse in-charges of maternity unit. The researcher adopted a census technique to sample clients who came for review at maternal child health clinic at 14th day post caesarean section. Study participants who met the inclusion criteria were recruited into the study as they sought the routine clinical care services in the clinic. Purposive sampling was used for the nurse in charges in maternity unit and maternal child health clinic. They provided qualitative data for the study. The findings revealed that factors associated with surgical site infections among post caesarean section women at Thika Level 5 Hospital were; age, duration of labor, duration of ruptured membrane and indication of CS. Women who were aged more than 35 years were 3.82 times more likely to have surgical site infections compared to those who were aged less than 35 years [3.82 95%CI=2.67 – 11.21, p=0.007]. Women who had labor more than 8 hours were 3.12 times more likely to have surgical site infections compared to those who had labor for a period of 4 to 8 hours [OR=3.12; 95%CI=1.88 – 8.28, p=0.003]. Also, women who experienced rupture of the membrane for more than 24 hours were 3.85 times more likely to have surgical site infections compared to women that experienced membrane rapture for 24 hours or less [OR=3.85; 95%CI=2.81 – 12.03, p=0.010]. Furthermore, women who experienced prolonged labor were 6.19 times more likely to have surgical site infections compared to women who did not have prolonged labor [OR=6.19; 95%CI=3.11 – 9.54, p=0.009]. Management of Thika Level 5 Hospital should pay a close attention to the maternal, labor and health systems related factors that are likely to cause surgical site infections among post caesarean section women admitted in the facility. Also, a continuous education program for healthcare workers and young new women is necessary and can be feasible and potentially successful, given the interest expressed by healthcare workers in the management of surgical site infections. MSc in Nursing (Midwifery and Reproductive Health) 2026-03-31T00:00:00Z http://localhost/xmlui/handle/123456789/6926 An Enhanced K-Means Clustering Information Mining Model for Selective Dissemination of Information for Library Users Too, Titus Kiprugut Rotich The amount of information materials held by academic libraries is enormous and ever increasing at an astonishing rate as new pieces of information are now not only present in the physical form but also in digital sources. These large numbers of information resources are a challenge to librarians’ on how they can effectively and efficiently provide such relevant information resources to users. This abundance of information has created a twofold challenge. First, users have to navigate through huge information to locate what they need and that is relevant. Secondly, the challenge in computational problems where most human errors go unidentified and corrected. Mining of information is essential, as looking for data is in itself a troublesome process. Clustering is concerned with the grouping of unlabeled feature vectors into clusters, such that samples within a cluster are more similar to each other than samples belonging to different clusters. Usually, it is assumed that the number of clusters is known in advance, but otherwise no prior information is given about the data. Clustering can be used for information mining in the library. K-means is an algorithm for clustering a set of unlabeled feature vectors X: {x1, …, xn} that are drawn independently from the mixture density p(X|θ) with a parameter set θ. The main objective of this study implemented and evaluated a clustering mining model for selective dissemination of information at an academic library. The research methodology approach that was used was quantitative experimental research design. The dataset population was obtained from an online open-source repository containing datasets that was acquired by scrapping goodreads.com. That dataset was 48 MB in size. The research was based on purposive sampling technique, a form of non-probability sampling. The K-means model for clustering used a set of unlabeled feature vectors X:{x1, … , xn} that were drawn independently from the mixture density p(X|θ) with a parameter set θ. The dataset was divided into two-dimensional with P = 12 data points naturally clustered into K = 3 clusters. The dataset was imported online from a CSV file using python import library function numpy. The dataset contained both training and test data that provided an enhanced validation of the model. Once the training dataset was created, it was time to train the model. AutoML Google Colab was used to train the model that got an RMSE of 0.198. AutoML used a number of sophisticated models such as neural architecture search, which build a learning networks one layer at a time. The comparison results from the experiments prove that the implemented recommendation k-mean clustering model approach for clustering information mining model to enhance selective dissemination of information for library users has the least percentage of mean vector and covariance matrix which resulted in a higher accuracy of 71%. When matrix vector and covariance vector are low, it brings an impression of an efficient model approach to clustering information mining model. In future, work may be extended by adding suitable pre-processing approaches to improve the datasets as well as features selection approach to improve the classification accuracy. Future work should also extend on time series dynamic data that are in real time, thereby developing new technique against improved hybrid approaches. MSc in Information Technology 2026-03-26T00:00:00Z