Dedan Kimathi University of Technology

Reliable short-term forecasts enable urban health systems to anticipate dengue surges and allocate resources effectively. We assembled monthly dengue case counts for Freetown, Sierra Leone (2015-2024), and compared four probabilistic model families under a leakage-safe, rolling-origin evaluation at 1-3-month horizons: a negative binomial generalized linear model (NB-GLM), a negative binomial INGARCH model (INGARCH-NB), a mechanistic renewal model with negative binomial observations (Renewal-NB), and a bidirectional long short-term memory network with a negative binomial output (BiLSTM-NB). All models used the same seasonal harmonics and autoregressive lags; "light" climate inputs (rainfall, temperature, and relative humidity) were restricted to lag-1 covariates to reflect real-time availability. We evaluated probabilistic performance using mean log score (primary), empirical coverage, and median widths of 50% and 90% predictive intervals, calibration diagnostics based on the probability integral transform, and Diebold-Mariano tests with Newey-West standard errors. For the main comparison, we evaluated models on a strictly matched set of common issue-target pairs within each horizon (n = 32 per horizon). On this aligned set, INGARCH-NB achieved the best mean log score at all horizons, indicating the strongest overall distributional accuracy. BiLSTM-NB remained competitive and provided more conservative upper-tail uncertainty at longer horizons (e.g., 90% interval coverage of 100% at h = 3), at the cost of wider intervals. NB-GLM variants produced the sharpest intervals but were substantially undercovered, indicating overconfidence, while renewal-based forecasts attained nominal coverage largely through uncertainty inflation that degraded sharpness and log score. In a leakage-safe light-climate ablation, adding lag-1 climate covariates yielded small, statistically non-significant gains for NB-GLM and did not improve renewal forecasts. Overall, the results support a horizon-aware toolkit for operational dengue forecasting: INGARCH-NB as a strong default when distributional accuracy is prioritized, complemented by calibrated deep learning (BiLSTM-NB) when conservative tail reliability is preferred. The aligned indices, per-issue forecasts, and code provide a transparent baseline for future work in similar urban settings.

As chia crop (Salvia hispanica L.) expands into new environments in Kenya, its response to moisture stress is only partially understood. This study simulated different soil moisture regimes to determine their effects on chia crop growth and yield, and to identify key traits that influence yield formation. Treatments comprised 40%, 60%, 80%, and 100% field capacity (FC). Watering soil to 40%, 60%, and 80% FC involved maintaining soil moisture at proportions equivalent to 0.40, 0.60, and 0.80 of the water content determined at field capacity, and irrigation was applied when approximately 50% of the assigned treatment moisture level had been depleted. Crop growth traits and yield components were maximized at 80% FC, with significant reductions observed at lower moisture levels, particularly 40% FC. However, in some instances, differences between crops grown under 80% and 100% FC were marginal. This suggests that moderate soil moisture levels may be sufficient in maximizing growth and yield of chia. The key determinants of chia seed yield were the number of panicles per plant and biomass production. These results imply that the introduction of chia into diverse agroecological zones in Kenya could consider not only rainfall amount and distribution patterns but also soil moisture retention capacity. Areas characterized by low rainfall, poor moisture retention, and heavy clay soils may be less suitable for chia production. However, field-based validation across agroecological zones is necessary in refining these recommendations.

Ordinary Portland cement (OPC) remains the most common binder used in construction and accounts for nearly 7%‐8% of the world’s CO 2 emissions due to calcination of limestone and high energy use during clinker production. Reducing OPC content using SCMs is one of the major strategies to achieve sustainable construction. Stone‐cutting dust, coming from quarrying activities and having a very fine particle size with oxide composition, has come out recently as a prospective SCM. Its chemical and mineralogical composition may vary widely depending on the type of parent rock: granite and basalt dusts, rich in silica and alumina, in contrast with marble and limestone dusts, which are mainly composed of crystalline calcium carbonate with low pozzolanic activity. This review aims to compile and discuss the published works concerning the use of SCD as a partial replacement of OPC, providing detailed information about its physicochemical, mechanical, and durability performance. Studies showed that 10%–25% replacement of OPC with SCD results in improvement in compressive strength (10%–20%), reduction of water absorption, and refinement of the pore structure due to the filler effect and limited pozzolanic reactivity. However, the obtained results are still inconsistent because of varying stone type, mix design, and curing conditions. Moreover, some reports show losses of strength or reduced workability when higher replacement levels were applied or in the case of using SCD enriched in carbonates. SEM, XRD, and FTIR studies demonstrated microstructural densification and secondary C–S–H in silica‐rich systems, while calorimetric and long‐term durability studies remain limited. Overall, SCD has the potential to be a promising sustainable supplementary cementitious material; however, its performance is strongly dependent on mineralogy and processing conditions. It is recommended that a standardized testing framework should be developed in order to allow better comparability between the various published studies and to guide safe and effective application in low‐carbon cementitious systems.

This research aimed to characterize the hydrological behavior of the Enguli ephemeral sand river in Makueni, Kenya, using simulation modeling to aid sustainable water management in arid and semi-arid areas. The specific objectives were to analyze streamflow patterns and infiltration rates within the basin employing Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS). The Soil Conservation Service Curve Number (SCS-CN) method was used for streamflow simulation, and infiltration modeling was performed using the Green–Ampt method. Model performance for streamflow simulation during calibration was Nash-Sutcliffe Efficiency (NSE) = 0.78, Percent Bias (PBIAS) = 19.83%, and coefficient of determination (R²) = 0.76, while during validation it was NSE = 0.81, PBIAS = -29.28%, and R² = 0.78. In infiltration simulation, model efficiency was NSE = 0.58, PBIAS = -14.32%, and R² = 0.6 after calibration and validation using field measurements from five sampling locations across the study area. Infiltration in the study area was significant, which points towards the reliability of alluvial aquifers as a water source during dry seasons. The study demonstrates the applicability of employing hydrological models in determining the potential of sand rivers as natural water storage reservoirs in arid and semi-arid lands. It forms part of enhanced water resource management approaches and informs climate-resilient, farmer-led irrigation systems.

Cooperative Learning Approach (CLA) has been widely recognized for enhancing students’ academic achievement. This study examined its effect on students’ perception of their classroom environment and the moderating role of gender. Guided by motivational and cooperative learning theories, the study used a quasi-experimental Solomon Four-Group, Non-equivalent Control Group Design. The target population comprised 766 Form Three students and teachers from four public co-educational secondary schools in Nakuru County, with a sample of 242 students and four English teachers. Two experimental groups (E1, E2) were taught using CLA, while two control groups (C1, C2) used conventional methods. Data were collected through Student Perception Guide (SPG), Teachers Perception Guide (TPG), and Student Interview Guide (SIG). Reliability testing yielded a Cronbach’s alpha of 0.801 for SPG. Data analysis involved descriptive and inferential statistics (t-test, ANOVA, ANCOVA) at α=0.05. Results showed a significant effect of CLA on students’ classroom perception (F(1,126)=2020.828, p<0.05) and a significant moderating effect of gender. The findings recommend integrating CLA in teacher training and encouraging English teachers to adopt it in line with the Competency-Based Curriculum (CBC).

Purpose: Procuring commodities and service is a critical avenue for delivery of public services by the state in any country. Process integrity right from need identification, tendering and eventual provision of services and works or delivery of the goods and their utilization is significant in identifying how robust public service is. Notably, challenges afflict ethical procurement practices in the public sector, leading to public resources losses along the supply chain. Thus, this study’s main goal was to evaluate the relationship between ethical procurement practices and performance of Kenya’s commercial state corporations. Methodology: Descriptive research design was used to study 165 Supply Chain Management staff at the targeted 33 functional corporations. Data was compiled through questionnaires. Pilot study was done to ensure reliability and validity of research instruments. The data was analyzed by use of descriptive statistics that included analysis of frequency, percentages, mean and standard deviation. Inferential statistics were further applied to assess the degree of relationship among the study variables, and results presented through tables and charts. Findings: The study results indicated a positive and significant relationship between ethical procurement practices (tendering, contracting and sourcing) and performance of commercial state corporations. However, ethical practices in specifications development did not have a significant effect. The study therefore concludes that ethical practice in tendering, sourcing and contracting significantly directly affected commercial state corporations’ performance. Unique Contribution to Theory, Practice and Policy: The study recommended that commercial state corporations should invest in staff capacity building on specifications development, inherent ethical standards/practices and their significance in order to improve quality service delivery to the public.

Abstract The Samburu Series magmas of the East African Rift System are a key component of the Early Miocene magmatic resurgence, marking the initiation of plate‐scale volcanic events associated with extension, distinct from the prior continental flood basalt episodes. We present the first flow‐by‐flow petro‐stratigraphic description of the Samburu Series magmas, preserved in a ∼400 m section at Peleketch (Turkana, Kenya). Using new major element geochemistry, petrology, and 40 Ar/ 39 Ar geochronology we reveal three distinct pulses of magmatism: an initial phase with mafic lithologies and relatively high flux, a middle phase with evolved compositions and continuing high flux, and a final waning interval marked by an increase in alkalinity and precipitous decrease in magma flux. Mantle melting models indicate a plate thickness of ∼90 km during the Samburu Series event and elevated mantle potential temperatures due to the influence of a mantle plume. While active upwelling from the plume contributed to melt generation, extension was critical in generating the melt needed for the Samburu Series magmas at Peleketch. The 21.2 to 19.8 Ma Samburu event marks the end of major volcanism within the Lotikipi Basin, coinciding with the cessation of extension and the commencement of the thermal sag component, highlighting the critical role of plate thinning in magma generation during this period.

This paper critically explores the evolving definitions, discursive constructions, and strategic responses to contemporary terrorism in Kenya. Drawing on the securitisation theory and critical terrorism studies, we interrogate how terrorism is framed by state actors, often in ways that marginalise Kenya’s vulnerable populations. We propose a context-specific definition of contemporary terrorism in Kenya as ideologically driven violence by non-state actors that exploits historical grievances, digital platforms, and vulnerable communities to influence governance to respond to their demands through fear. Through a chronological analysis of Al Shabaab’s operations from 1980 to 2024, we identify shifts from transnational attacks to hybrid asymmetric warfare, including digital radicalisation. The study critiques Kenya’s counterterrorism practices—highlighting the securitisation of ethnic identity, human rights violations, and the politicisation of counterterrorism laws—while acknowledging recent reforms and technological innovations. We propose a four-pronged hybrid model of counter-terrorism strategy in Kenya involving community engagement, technological adaptation, and cross-border intelligence collaboration. Ultimately, we argue that Kenya must recalibrate its approach to prioritise rights-based, locally grounded strategies that build resilience and mitigate extremist appeal.

Thermal heat stress is one of the major environmental threats that pose a challenge to agriculture and agrobiodiversity conservation globally. The present study aims to model heat stress in Tharaka-Nithi County and assess its impact on vegetation health across different agro-ecological zones from 2000 to 2023. The study used the vegetation health index, soil moisture index, land surface temperature, aridity index, aspect, area solar radiation, evapotranspiration and albedo as datasets. A GIS ensemble approach, which combined principal component analysis and TOPSIS was used to model thermal heat stress between 2000 and 2023. Multivariate analysis was used for impact assessment on vegetation health between 2000 and 2023. The study revealed an increase in thermal stress. Areas with very high thermal stress increased from a low of 0.11% in 2008 to 14.49% in 2023, while the areas with very low thermal areas decreased from 16.16% in 2000 to 0.15% in 2023. The regression analysis results for various agro-ecological zones across different years showed consistently negative coefficients for heat stress across all zones and years ranging from - 0.38 to - 0.67. This indicates that increased heat stress is associated with a statistically significant decrease in vegetation health, as supported by the low p-values (below 0.05). All zones, except for the tropical alpine, recorded R-squared values above 0.50 in all the years indicating that more than 50% of the variation in vegetation health index can be explained by thermal heat stress. The research concludes that thermal heat stress is a major contributor to the reduced vegetation health in Tharaka-Nithi County from 2000 to 2023, with an increase in thermal heat stress corresponding to a decline in vegetation health. To maintain vegetation health, this comprehensive analysis is crucial for developing adaptive agricultural practices, improving land management and building resilience to climate change.