This study sought to determine the effect of corruption on productivity of manufacturing firms in Kenya. Specifically, the study sought to investigate the extent to which the productivity of firms in the manufacturing sector is affected by corruption. Additionally, the study compared how corruption affects the productivity of different firm sizes. The study employed panel data from the World Enterprise Survey covering the period 2007-2018. The study found out that corruption had an insignificant positive effect on the productivity of manufacturing firms. Ownership type has also an insignificant effect on productivity. However, large firms engaged in corrupt activities showed a positive effect on their productivity compared to medium sized firms which also showed a positive effect when compared to smaller firms. Thus overall, corruption positively affects the productivity of large firms: large firms have the financial muscles for paying bribe tax and time tax reducing bureaucracies hence improved efficiency.

Realization of ODF communities and progression on the sanitation ladder to 100% utilization of improved sanitation facilities has become an elusive goal for the WaSH sector both globally and in Kenya. The development WaSH sector has engaged governments in the last two decades in developing various strategic frameworks in a bid to achieve the Millennium Development Goals of 2015 and the Sustainable Development goals of 2030 for sanitation. Additionally, research studies have developed theoretical models and descriptive frameworks that endeavor to guide behavior change interventions related to sanitation. Kenya is among countries that have integrated the development goals in its sanitation strategic frameworks however; the country’s OD rate stands at 14% with an annual decline rate of 0.75%, while the rate of uptake of improved sanitation facilities is at 1%. This research study aimed to determine the effects of socioeconomic factors on utilization of improved sanitation facilities by households in Kenya. It followed the Integrated Behavior Model for Water Sanitation and hygiene and, employed probit model in analysis of the 2018 Kenya Integrated Budget Household Survey data to determine the effects of income, education level, gender and age on utilization of improved sanitation facilities by households in Kenya. The study applied probit model. The study findings indicate, the type of sanitation facility utilized by a household is determined by, the sex of the household head, the highest level of education attained by the household head and, the household income. The study concludes that sanitation policy formulation and implementation should target resources towards knowledge empowerment and increasing household income generating streams for investment in improved sanitation.

Commercial poultry production is an important farming enterprise in most parts of Kenya. The treatment of enteric infections in animals has been complicated through development of antimicrobial-resistant microbes. Occurrence of Multiple forms of drug resistance patterns has rendered chemotherapy drugs less effective in management of microbial infection. Multidrugresistant Extended-Spectrum Beta-Lactamase (ESBL) producing Enterobacteriaceae places great threat towards public health by raising morbidity and mortality particularly in developing countries. Accurate statistics on the frequency and mechanism of antibiotic resistance development in enteric micro-organisms isolated from poultry and persons in Kenya is scarce. This current study determined the extent of antimicrobial use, and resistance patterns in selected Enterobacteriaceae isolated from commercial poultry production systems in Kiambu County, Kenya. A descriptive cross-sectional study was conducted on commercial poultry production systems of Kiambu County to ascertain the knowledge level, attitudes, and practices on antibiotics use in addition to their resistant patterns on selected Enterobacteraceae species. One hundred and fifty six commercial poultry farmers were purposively selected from the following subcounties; Ruiru (n=33), Juja (n=20), Gatundu North (n=20), Gatundu South (n=19), Thika (n=27) and Kikuyu (n=37) respectively. One hundred and fifty-six (n=156) semi-structured questionnaires imprinted in a mobile Open data kit were administered to capture the knowledge level, attitudes, and practices on antimicrobial usage in commercial poultry production systems of Kiambu County. A total of 437 fecal samples (cloacal swabs (n=365), and Human stool (n=72)) were collected, followed by bacterial isolation, confirmation, antibiotics susceptibility tests, and molecular detection of ESBLs genes and Quinolones resistance (QNRs) were detected using Polymerase chain reaction (PCR) methods. Out of 156 commercial poultry farmers who participated in this study, females accounted for (64%) with 51% of them keeping layers between 50-500 birds as medium-scale farmers. Sixty-one percent (61%) of the farmers were 45 years and above, and they had obtained a secondary level of education (34%). Sixty seven percent (67%) of the farmers obtain antibiotics through self-prescription/personal experience from the drug shops. Farmers identified lack of enough veterinary officers (77%) and consultation services (72%) as key challenges in poultry production system. Sixty three percent (63%) of the respondents, indicated tetracycline as the most commonly used antibiotic in their farms, with oxytetracyclines subtype (85%) being the most preferred. Also amoxicillin (63%) was equally preferred by farmers with amoxi (88%) sub-types being the most preferred, xxi respectively. Nearness to veterinary services significantly (P<0.05) contributed to the use of antibiotics agents. Additionally, the area of residence, type of production, number of years in farming, and average number of birds kept also significantly (P<0.05) influenced the level of knowledge and practice on antimicrobial usage. Out of 437 fecal and stool samples collected, 591 (Cloacal isolates=544; human isolates= 47) isolates were recovered, with E.coli (48.9%) being the most frequently identified, followed by Shigella spp. (18.8%), Salmonella spp. (18.3%), and Klebsiella spp. (14.0%).There was a great occurrence of multiple resistance among isolates especially towards sulfamethoxazole (79%), trimethoprim (71%), and tetracyclines (59%), respectively. Additionally, the isolates showed the highest rate of susceptibility against cefuroxime (94%), gentamicin (93%), ceftriaxone (91%), cefepime (89%), cefotaxime (85%), ceftazidime (84%), and chloramphenicol (77%), respectively. Out of the isolates (n=78) collected with potential ESBLs production, only 66 (84%) tested positive for the target genes with the utmost detected ESBL genetic factor from the isolates being blaOXA (n=20; 26%), followed by blaTEM (n=16, 21%), with the majority of them detected in Escherichia coli. In all the four enteric's bacteria-type isolates tested, the blaCTXM gene was detected. Three (n=3) Salmonella, and E.coli spp respectively harbored all the five tested antimicrobial resistance (AMR) gene types. The blaTEM, blaOXA, blaSHV, and QnrS genes were not detected from Klebsiella and Shigella spps. Additionally, most of the AMR gene co-carriage was detected in both E.coli and Salmonella spps as follows blaTEM+blaOXA (n=4); blaTEM+QnrS (n=3); blaTEM+blaOXA+Qnrs (n=3), concurrently. It was concluded that both fecal and stool materials from commercial poultry and humans can be a reservoir of multi-drug resistance enterics. This is a potential route of spreading out resistance genes amongst livestock and Humans, which pose a great danger to public health of Kiambu County residence. There is also need to strengthen antimicrobial surveillance and monitoring strategies at County level. It was recommended that the results of the current study be used in formulating strategies and informed decisions in combating antibiotic resistance and irrational usage of antibiotics in commercial poultry production in Kiambu County and other areas with similar poultry production systems in Kenya.

Infrastructure holds a central position in a country’s economic activity, hence the need to do a comprehensive analysis of its specific contributions to an economy. In the last decades, the East African Community (EAC) governments have devoted significant public resources towards building new infrastructure projects in the region. However, growth has not been commensurate with increased public investment in infrastructure; in addition, the volume of trade has stagnated. Therefore, this study employed panel time-series technique and infrastructure augmented production function, to establish the short- and long-run relationship between infrastructure stock and economic growth using data for the period 1990-2019. The study also explored the possible channels through which infrastructure could manifest itself on growth by doing an in-depth analysis on key determinants of growth, like private investment and trade. Infrastructure stock index was constructed from public economic infrastructure including transport, energy, and communications. Data was obtained from various sources including the Socio-Economic database of African Development Bank, World Bank database, International Monetary Fund database and National Bureaus of Statistics of EAC Partner States. Panel data models for growth and private investment were analysed using pooled mean group estimation technique. The study established a cointegrating relationship between infrastructure stock and economic growth in EAC and a uni-directional causality from infrastructure to economic growth. Using an error correction framework to capture the short-and long-run dynamics, the results confirmed that, public infrastructure investment crowds-out private investment in the short-run but crowds-in private investment in the long-run. The study estimated a gravity model augmented for both hard and soft infrastructures from transport and information and communications technology indicators using random effects model and Poisson Pseudo Maximum Likelihood method. Both methods confirmed that infrastructure stock is important in increasing the volume of EAC’s trade. The policy implications are that increased investment is vital in economic infrastructure to increase infrastructure stock, encourage private sector activities and growth in the long-run. Macroeconomic stability is also crucial for private sector investment. Transport infrastructure has a greater impact on exports than Information and Communications Technology infrastructure and thus, it is important to channel additional resources towards increasing transport infrastructure stock. The study also found that, many documents required for exports lowers the volume of trade, hence it is critical to enhance border efficiency for more trade. Key Words: Infrastructure Development; Economic Growth; Private Investment; International Trade; EAC JEL Classification: H54; O47; R42; F10; F15

Soil carbon stocks (SOCs), soil water balance and greenhouse gas fluxes measurements in wooded grassland are often done in a single assessment. This is oblivious of its heterogeneous nature and asymmetric distribution that characterizes wooded grassland and thence inaccurate results are captured. This information is essential, albeit lacking, for designing sustainable strategies important for management of the fragile wooded grassland ecosystems. The present study investigated topographical and vegetation cover types effects on SOCs, soil water balance (SWB) and greenhouse gas fluxes in wooded grasslands of Laikipia County, Kenya. This study was conducted during the short and long rainy seasons of 2016 in Ilmotiok group ranch of Laikipia County. Soil organic carbon stocks (SOCs), soil water balance (SWB) and greenhouse gas fluxes across different topographical positions and vegetation cover were quantified. The experimental design was a RCBD with a split plot layout. The main plots were topographical zones (TZ); mid slopes (MS), foot slope (FS) and toe slope (TS). The subplots were vegetation cover (VC) types: tree (T), grass (G) and bare (B). Sampling of soil was done at intervals of 10 cm to a depth of 50cm in a zigzag manner using a soil auger. The sampling was done along a transect line of 150m after every block of 50m forming three replicates. The sampled soil was analyzed for texture, bulk density (BD) and soil organic carbon. Runoff plots were set up across the TZ and VC types to monitor runoff (RO) and soil loss (SL). To measure Greenhouse Gas (GHGs) fluxes (methane (CH4), carbon dioxide (CO2), and Nitrous Oxide (N2O) static chamber frames were installed across the topographic zones and vegetation cover types. GHGs were measured every 7-10 days in the dry season, intermediate and rainy season between 0800hrs and 1200hr local time. TZ, VC, depth and TZ*VC significantly (p<0.05) influenced BD and SOCs. There was a significantly higher bulk at MS (1.03 g/cm3 and 1.00 g/cm3) but not significantly different from TS (1.02 and 0.92 gcm-3) with FS having the lowest value (0.97 and 0.88 gcm-3) for LRS and SRS respectively. Vegetation cover significantly (P <0.05) influence with highest bulk density recorded under BR (1.04 and 0.96 gcm-3) which was not significantly different from TR (1.01 and 0.92 gcm-3) and significantly higher than GR (0.97 and 0.92 gcm-3) for LRS and SRS respectively. The interaction of topography and vegetation significantly influence bulk density with highest value recorded under FS*BR (1.11 and 1.03 gcm-3) for LRS and SRS respectively. Highest soil organic carbon stocks were recorded at the TS (6.40 and 6.51 MgHa-1) as compared to other zones though not significantly different v v from MS (6.16 and 6.46 MgHa-1) but significantly different from FS (5.29 and 5.93 MgHa-1). SOCs under GR (6.31 and 6.53 MgHa-1) were slightly higher than other vegetation cover, the lowest was recorded under BR (5.76 and 6.02 MgHa-1) for LRS and SRS respectively. The upper soil depth (0-10) had (8.70 and 8.74 MgHa-1) compared to the lower depth (40-50) with (3.52 and 4.07 MgHa-1). There were significant [P<.001] differences in evapotranspiration, runoff and soil loss across the three topographical zones and vegetation cover types. The run off was significantly higher in mid slope*bare [175.90 and 168.75 mm] and mid slope *grass [172.00 and 164.85mm] compared to toe slope *bare [169.79 and 162.64 mm] and Toe Slope* Grass [165.89 and 158.74 mm] during the LRS and SRS. Whereas Soil water balance was highest at the toe slope*grass [279.46 and 119.49 mm] than Foot slope*Grass [273.51 and 113.54 mm] and Mid Slope*Grass [267.23 and 104.76 mm] during the LRS and SRS respectively. The Run off Coefficient was significantly lower in the Toe slope*Grass [0.30 and 0.45] than Foot slope*Grass [0.31 and 0.46] for LRS and SRS). During the wet months, CH4, N2O and CO2 emission were significantly higher than the dry season. Methane fluxes ranged from -0.32 mg.m-2.h-1 to 0.24 mg.m-2.h-1 with the lowest (-0.32 mg.m-2.h-1) recorded under TS*T whereas CO2 was highest under TS*G (47 mg.m-2.h-1) as compared to MS*G (19 mg.m-2.h-1). TZ*VC significantly influence N2O with MS*B recording the lowest (0.008) as compared to TS*B (2.228 mg.m-2.h-1). CO2, N2O and CH4 In the month of January and February emissions were low and it increased in March and April in all the TZ*VC. Topography and vegetation have an effect on soil organic carbon stocks and bulk density. Toe slope and grass significantly increased soil organic carbon stocks and reduced bulk density. Toe slope with grass significantly reduced both runoff and soil loss thus increased Soil water balance and improved runoff coefficient. Therefore, protection of slopes from raindrops can effectively reduce soil loss and runoff and enhance deposition in the mid slope and toe slope. The trends of soil CO2, N2O, and CH4 fluxes were principally controlled by topography and plant cover, with larger soil CH4 uptakes and CO2 emissions on the toe slopes and foot slopes than in MS. Keywords: bulk density, runoff, soil loss, soil water balance, soil organic carbon stocks, topographical zones, vegetation cover.

Community health is the health of a specified group of people, as well as the public and private activities and circumstances adopted to improve, preserve, and conserve their health (McKenzie, Pinger and Kotecki 2005) Health of a community is a product of their environment that is a community where the population have access to safe homes, quality education, adequate employment, physical activities, nutrition, quality healthcare and transportation. According to World health organization (WHO) defines Health as the process of empowering people to take charge and improving their health. In a community different segments of a community contribute to health promotion and therefore share the responsibility for its protection. To improve the health of a community, the population must change the physical, social, organizational, and political environments so as to minimize factors contributing to health hazards and introduce new aspects which promote improved health such as introducing new programs, changing attitudes, beliefs and norms, policies and organization infrastructure. The urban population explosion has been accompanied by overwhelming rate of poverty due to the rising number of people living in informal settlements and has led to poor health outcomes. This study aimed on establishing the disaster management cycle and performance of community health projects a case of Kangemi informal settlement in Nairobi County. This was reviewed through the four stages of disaster management cycle which are identified as: - disaster mitigation, disaster preparedness, disaster response and disaster recovery. All these stages were reviewed in relation to how each one of them influences the performance of community health projects. The study was anchored on the domino theory and theory of reasoned action. Further, the study sought to identify the association amongst independent variables involved and how they influence on performance of health promotion projects. The study used descriptive survey design with a target population of 100,000. A sample size of 390 was drawn from the target population using the Krejcie and Morgan formula and further adopting a proportionate sampling technique. Data was obtained using semi-structured questionnaires and interview guides. The instruments were pilot tested using 39 questionnaires that were administered to Kawangware informal settlement residents who have similar characteristics as the study area. The collected data was analysed with the aid of a Statistical Package for Social Sciences (SPSS) for both descriptive and inferential statistics and then presented in form of description. Cronbach’s alpha coefficient was adopted to ascertain for reliability that was obtained through split-half technique. Simple linear regression was applied in testing for the strength of the association amongst the various variables for instance establishing how the dependent variable was influence by the independent variable. It was established that disaster mitigation with has a strong positive significant influence on performance of community health projects. The study also established a positive relationship between disaster preparedness and performance of community health projects. The study findings showed that disaster response influences performance of community health projects; and also a positive relationship between disaster recovery and performance of community health projects was established. The conclusion according to the study was that catastrophe mitigation, disaster preparedness, disaster response, and disaster recovery all have an impact on the efficacy of community health programs. The research recommended that there is need to adequately enhance sensitization of disaster management strategies during project planning. The research suggested that environmental studies in project management and social analysis should be carried out in informal settlement areas in Kenya.