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Mandera County’s 2010- 2030 Population Projections and Their Implications on Human Resources for Health
No full textThe core objective of this study was to project the population of Mandera County from 2010 and 2030 incorporating the county population dynamics and determine their implications on human resources for health. The study employed the cohort component method to project the population of Mandera County and the workforce-to-population ration method to project the required number of heath personnel from the year 2010 to 2030. The study used secondary data from the 2010 Kenya National Bureau of Statistics Analytical Reports on Population projections, fertility and nuptuality, mortality and migration. The study also used secondary data from the 2014 KDHS report. The base year for this study was 2010 and thus it the data derived from the 2010 analytical reports had been subjected to quality assessments to check on its accuracy and address any coverage or content errors.
The study began by projecting Mandera County’s population dynamics whereby the total fertility rates and age-specific fertility rates of the county are projected to decline for the period of the projection. The TFR of Mandera County declined from 7.3 in 2010 to 3.1 in 2030. The projected under-five mortality rates also declined from a high of 155 in 2010 to a low of 26 in 2030. After projecting the population dynamics of the county, the study projected the entire population of the county using these dynamics as is required using the Cohort Component Method. This study found out that Mandera County’s population will increase from 642,733 in 2010 to 747,206 in 2015, to 830,714 in 2020 to 917,324 in 2025 and finally to 1,018,127 by 2030.
Finally, after projecting the population of the county this study projected the required minimum and maximum number of health care personnel per a population of 10,000 people. The county will require a minimum of 1,719 health personnel in 2015, and a maximum 4,531 by 2030. The county also required a minimum of 7,113 nurses and 2,541 doctors in 2015 and a maximum of 9,693 nurses and 3,462 doctors by 2030.
Based on these findings, there is need for more funding that will go towards hiring of health personnel as well as further research on population projections at the county level incorporating the population dynamics, which has not been done previously
A Comparative Analysis of Factors Explaining Fertility Differentials in Nyeri and Mandera Counties in Kenya
No full textThe study’s objective was to determine and explain the effects of the socio-economic, cultural and proximate factors influencing fertility differentials in Nyeri and Mandera counties in Kenya. Two subsets of the 2014 Kenya Demographic and Health Survey data, containing 521 women for Mandera County and 698 women for Nyeri County were used for analysis.
This study analysed the effects of ten explanatory variables, consisting of five background variables and five proximate determinant variables, on rate of childbearing in each county. The explanatory variables analysed were wealth index, education level, place of residence, age at first marriage and religion. The proximate variables: were marital status, ever use of modern contraceptives, experience of child mortality, age at first birth and ideal number of children. Rate of childbearing was measured by a composite variable consisting of children ever born and respondent age.
The study applied descriptive statistics to describe the study variables and Poisson regression analysis to determine the effects of predictor variables on the outcome variable. Bivariate Poisson regression models were used to screen the independent variables considered in this study. Multivariate Poisson regression models fitted involved only the significant explanatory variables at bivariate analysis stage in both or either of the two counties.
The results of the bivariate regression established that except for religion, all the selected background and proximate variables had significant effect on the rate of childbearing in both or either of the two counties. The results of multivariate regression revealed that age at first birth and experience of child death were common across the two although with varied effects, marital status was only unique in Mandera while wealth index, use of modern contraception and ideal number of children were unique in Nyeri.
Experience of child death and low use of modern contraceptives were attributed to high fertility in Mandera while improved wealth status accounted for low fertility in Nyeri. In view of these, key interventions to reduce childhood mortality, reposition family planning and increase wealth creation are recommended. Also, further studies should be undertaken using datasets containing information on proximate factors that were not analysed in this study due to various limitations
Social Economic Factors Influencing Adoption Of Livestock Production Technologies In Kenya: A Case Of “Mifugo Ni Mali”
No full textThe level of livestock improvement technologies disseminated and adopted by the target
audience needs to be investigated. Information dissemination is slowly gaining momentum as
a complimentary factor in promoting agriculture in the rural areas. The study sought to
establish the social economic factors influencing adoption of livestock production
technologies in Makueni County in Kenya. The specific objectives were to: establish
influence of training on adoption of livestock production technologies in Makueni County in
Kenya, establish influence of cost of implementation on adoption of livestock production
technologies in Makueni County in Kenya, establish influence of farmer attributes on
adoption of livestock production technologies in Makueni County in Kenya and establish
influence of dissemination of information on adoption of livestock production technologies in
Makueni County in Kenya. Descriptive research design was utilized in this study. The target
population was 129 including livestock farmers registered in “Mifugo ni Mali” programme
and livestock extension officers in Makueni County. The sample size was 86 respondents.
The data was collected using questionnaires. The collected data was sorted, cleaned and
analyzed to give frequencies and inferential statistics by use of using Statistical Package for
Social Sciences (SPSS Version 25.0). The study found that training greatly influence
adoption of livestock production technologies in Makueni County, Kenya (43%). The study
also established that on farm training of farmers influence adoption of livestock production
technologies in Makueni County, Kenya to a great extent (Mean = 4.114). The study
concluded that dissemination of information (Pearson correlation coefficient = 0.836) had the
greatest influence on adoption of livestock production technologies in Makueni County,
Kenya, followed by training (Pearson correlation coefficient = 0.769), then farmer attributes
(Pearson correlation coefficient = 0.774) while cost of implementation (Pearson correlation
coefficient = 0. 0.672) had the least effect on adoption of livestock production technologies in
Makueni County, Kenya. The study recommends that there is a need for the county
government of Makueni in conjunction with national government of Kenya to come with
strategies of reducing the cost of implementing the livestock production technologies. The
study further recommends that there is need for farmers and extension officers to be trained
on livestock production technologies and other technologies that can positively contribute to
high productivity among farmers. Further studies are recommended on; effect of government
support on adoption of livestock production technologies and another area would be on the
challenges facing the farmers in adoption of livestock production technologie
Towards Decent Work On Online Labour Platforms: Implications Of Working Conditions In Online Freelance Work On The Well being Of Youths In Nairobi County
No full textThis research examined the implication of the working conditions in online freelance work on the wellbeing of youths working on online labour platforms in Nairobi County. In doing so, it examined the characteristics of these youths and their working conditions with a particular attention on how these working conditions compare to the decent digital work standards proposed for the remote platform economy.
It holds that the confluence of information-communication technologies and the worker power - balance of bargaining power between the clients and workers- yields organisational forms which shape the working conditions (job quality outcomes) of online freelance workers (Rubery and Grimshaw, 2001). In this case, working conditions refers to the earnings, working time, availability of work and the work process on the online labour platforms. These working conditions in turn affect the wellbeing (household income, health and skills acquisition and development) of the online freelance workers.
The research used mixed methods research design. The quantitative method involved the use of a semi-structured questionnaire administered to 133 youths doing online freelance work and living continuously in Nairobi County. The qualitative method involved the use of interview guides administered to five key informants, , who are opinion leaders and policy makers on information and communication technology for development, business process outsourcing, online outsourcing, digital work and youth employment in Kenya.
The findings show that online freelance work is characterized with decent work deficits that need an immediate intervention. The earnings, working time, work process on the online labour platforms met the decent digital work standards. However, this obscures various decent work deficits related to these working conditions. Availability of work-also known as stability of work- did not meet the decent digital work standards. The research found that the youths are underemployed with most of them not getting enough freelance work regularly.
These working conditions have tremendous implications on their wellbeing with most of them living in a precarious financial situation-not able to meet their basic needs and cover emergency expenses. On the contrary, these working conditions had no significant effect on the health of the youths apart from a general feeling of anxiety and fatigue emanating from the irregular working
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schedules and insufficient work on the platform. Moreover, the findings showed that online freelance work facilitates skills acquisition and development.
Furthermore, the research provides multi-stakeholder recommendations that can be adopted to bridge the decent work deficits and yield quick gains for the investment that the government has made in online work as an employment strategy for the youth. In general, the research concludes that the government of Kenya needs to pay a particular attention to decent work. It also needs to overhaul Ajira digital programme from a training that introduces high potential but disadvantaged youths to online work to a training that seeks to position the youths in the high-skill macro-task niche. Currently, most youths in Kenya are in the low skill-micro task niche which has meagre earnings and is flooded with workers from other countries in Africa and Asia
Implications of Hate Speech on National Security: a Comparative Analysis of the Kenya and Rwanda Experiences.
No full textThe international community has tried to control hate speech to avoid threats to peace and security. Scholars and researcher have lobbied for the positioning of hate speech in upcoming policies to boost state security. The aim of this study was to examine the impact of hate speech on national security comparative analysis of Kenya and Rwanda; two African countries. The research was driven by the increases in the use of language that is deemed a threat to the security in Kenya, in the pretext of freedom of expression. The setting provided by the Rwanda genocide is used to illustrate the potential danger that countries like Kenya would face in the case of misuse of the Freedom of Expression. The researcher primarily sought to examine how hate speech affects security and stability in the two African countries. The study focused on three objectives, namely: To establish the place of hate speech in the national security discourse, to examine the legal and institutional framework of hate speech management in Kenya and Rwanda, and a critical comparative analysis of impact of hate speech and national security in Kenya and Rwanda. The research adopted descriptive research design because of its precise and authentic representation of the findings. Primary data was obtained both from Kenya and Rwanda using questionnaires and interviews. The study found out that the two countries have sufficient examples to design plans of action, and are treating the subject as a matter of importance giving the reason for continued threat to national security. The adopted strategies are rated to have high effectiveness because they move closer to address the key root cause of hate speech induced conflict. It was also established that, strategies in Kenya still fail due to lack of evidence and manipulation by the political class. The study also observed that hate speech lowers the dignity of individuals resulting to frustrations, anger, emotional suffering and distress. This study recommends that, the policies put in place should be accompanied by efforts to improve the capacity of institutions, which have sought non-legal measures as a strategy to change discourse on different social issues. Consequently, media strategies should regulate the content being aired
Assessment Of The Influence Of Astronomical Parameters On The Skill Of Rainfall Forecasting In East Africa.
No full textSeasonal forecasts generated in East Africa have mainly used the SST-based models in the last
two decades with challenges of poor forecasting skills. In particular, the method of forecasting
rainfall extremes has been too general and that these extremes occur much more frequently
than forecasted. And furthermore, no forecasting model in use in the region provides the
temporal variation or the intra-seasonal-to-interannual variability of rainfall. In addition to the
low skills, the traditional Indigenous Knowledge (IK) forecasting methods are falling out due
to climate change. One component of the IK, the astronomical observations, is viewed with a
lot of scepticism and is considered as a non-science, therefore, inhibiting its application in
science-based forecasting and research.
This study focuses on astronomical observations in its objective which is to determine the
influence of the orbital parameters of planets and the moon on the weather and climate patterns
in East Africa.
Results generated show that Saturn, Jupiter, Venus and Mars have a relationship with rainfall
but at different levels. Both MAM and OND in all zones seem to show a variation from year
to year that indicates strong astronomical influence in most cases. We also note that rainfall
characteristics during two similar celestial phases but which occur at different times of the year
are different, however, rainfall characteristics associated with the same observed phase and in
the same month or period were found to be nearly the same.
To get to the same phase in the same month of the year, would take Saturn 30 years, Jupiter 12
years, Mars 15 years and Venus 8 years giving rise to what is refered to here as Saturn Rainfall
Cycle, Jupiter Rainfall Cycle, Mars Rainfall Cycle and Venus Rainfall Cycle respectively. That
means that the East African rainfall varies in cycles of 8, 12, 15 and 30 years. The rainfall
cycles are easily determined by use of their key phases and can be predicted by use of
astronomical calculations with little error and with sufficient accuracy way ahead of time.
Further, by using historical information, it was found out that severe climate extremes occur
during the conjunctions of both Uranus and Neptune where Uranus takes ~83 years and
Neptune takes ~163 years to orbit to the next conjunction. These periods, now called Uranus
rainfall cycle and Neptune rainfall cycle respectively, coincide with the variation of severe
extreme events in the study area. We can attribute those variations to the two planets’ orbital
motions.
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The probabilistic models developed here use probability of occurrence or exceedance and have
five categories; “Extreme Low”, “Below Normal”, “Normal”, “Above Normal”, “Extreme
High” and “Phenomenal”. Using the probabilities of occurence on 2018 rainfall seasons, a
qualitative verification process indicated relatively high probability values of up to 67% under
“Above Normal” and “Extreme High” for MAM 2018 forecast in areas that mainly fall in the
highlands East of the Riftvalley, while the period OND indicated high probability values of
up to 83% under the category “Below Normal”. The season MAM 2018 was extremely wet
and OND 2018 was extremely dry which means the probabilities had captured the extremes as
projected.
Generally, from the results, it was found out that the planets have a relationship with the East
African rainfall. Each one of them showed a certain level of contribution to the variation of
monthly rainfall with the Planet Saturn indicating the biggest influence. The moon had
relatively little influence to the monthly rainfall variation compared to the planets.
The phases of the planet can be hindcasted back in time to allow a dependable determination
of rainfall variation of the past. In general, the use of these astronomical phases can be used to
generate past and future climate scenarios in the region that can add useful body of knowledge
to climate science that can be integrated in scientific reports like the IPCC Assessment Reports
Influence Of Talent Management Practices On Employee Commitment In The Kenyan Public Service: A Case Of State Department For Infrastructure
No full textThe purpose of the study was to determine the influence of talent management practices on employee commitment at State Department for Infrastructure in Nairobi. The objective of the study was to find out how talent management influences employee commitment. The study was meant to benefit the management of State Department for Infrastructure, Human Resource Practitioners from other institutions, policy makers, future scholars and other stake holders. A descriptive research design was used for the study and data on demographic, talent management practices and employee commitment was collected using questionnaires.102 respondents were targeted to respond to the questionnaires. Data collected was analyzed using descriptive and inferential statistics. The findings of the study revealed that Talent Attraction positively and significantly influences Employee Commitment (β=0.219, p=0.001),Talent Selection positively and significantly influences Employee Commitment (β=0.182, p=0.006),Talent Engagement positively and significantly influences Employee Commitment (β=0.109, p=0.031), Talent Maintenance positively and significantly influences Employee Commitment (β=0.124, p=0.030), Talent Development positively and significantly influences Employee Commitment (β=0.144, p=0.000) and that Talent Retention positively but insignificantly influences Employee Commitment(β=0.089, p=0.293).The study concluded that talent management practices positively influences employee commitment at state department for infrastructure. The study recommended that the managements and stakeholders at state departments should strive to adopt the most appropriate talent management practices to enhance employees’ commitment
Financial Knowledge on Annuity Uptake Among Retirees of Insurance Companies in Kenya
No full textAccess to financial management skills and general education programs is part of many challenges encountered by individuals in their quest to improve their level of knowledge on saving for retirement lifestyle. The study determined the effects of financial knowledge on annuity uptake among retirees of insurance companies in Kenya. The independent variable was financial knowledge while the control variables were gender, age, marital status and income. The study employed descriptive research design. The target population was 8,637 retirees from the 54 insurance companies in Kenya. The results were analyzed using social sciences (SPSS) computer software Version 25.0. Demographic results indicated that majority of retirees were males. Majority of the retirees were married. It was also established that majority of retirees had gross monthly income of KES 150 000 and below. The Cox & Snell R Square was fair at 46.2% implying a fair model fit. Multivariate logit results showed that age was statistically significant in relation to annuity uptake. Age differences irrespective of gender are more likely to influence annuity uptake. Marital status was also statistically significant in relation to annuity uptake. Further, income was statistically significant in relation to annuity uptake. Financial knowledge was statistically significant in relation to annuity uptake. Financial knowledge has the strongest effect on annuity uptake and is strongly associated with an increase in annuity uptake. The study concludes that demographic characteristics of retirees are associated with annuity uptake. Gender, age, marital status and income are likely to influence annuity uptake of retirees. The study revealed that demographic characteristics of retirees are associated with annuity uptake. The demographic features include gender, age, marital status and income. In terms of gender, women are thought to be more likely to make contribution after retirement. However, the findings should not be generalized to all genders as life situations and other factors differ significantly among retirees irrespective of gender. The study therefore recommends for intensive awareness on annuity uptake among men and women retirees to improve annuity uptake after retirement. The study recommends for proper awareness training on the importance of continuing paying annuity premiums after retirement. The awareness should state that paying annuity is important for all retires in different age brackets because life disturbances are unpredictable and do not affect particular age group more than another. The unmarried persons, divorced and widowed persons are often psychologically traumatized and may stop making payments after retirement. The study recommends for proper guiding and counseling sessions to be offered by respective insurance providers to these groups on the need to continue contributing the premium despite the problems that befell them. It is worth noting that being married means you are not psychologically disturbed and recommendations are also applicable to married couples. The study recommends that proper financial awareness on savings is required for employees before they retire from active work to ensure that the retirees have sufficient to meet their needs after retirement
Groundwater quality prediction using logistic regression model for Garissa County
No full textGroundwater quality modeling can reduce the cost of exploration and
siting of boreholes considerably. The present study applies Logistic
Regression Model to predict the probability of siting boreholes of fresh
or saline water based on geospatial data such as altitude (m),
longitudes, latitudes and depths (m), and geophysical data such as
electrical resistivity from 45 exploration sites. The geology of the study
area is represented by permeable water-bearing Tertiary-Quaternary
sediments located within the Anza Rift. The water bearing zones, or
water struck levels, range in depth between 50 and 150 m and the
average yield of about 1 - 5 m3 per hour, in the case of old wells done
using percussion rigs in the period between 1960s to the 1990s.
Recently, the discharge in the wells done using modern mud rotary
equipment yields up to 30 m3 per hour, with depths ranging between
200 to 250m below ground level. The modeling results show strong
correlation between the dependent variables; depth, mean resistivity,
longitudes, and latitudes on one hand, and salinity status of aquifers. It
is, therefore, possible to know the water quality of a location in the
study area before actual drilling is undertaken. Of all the runs made,
93% were predicted accurately while only 7% of the cases deviated
from the predicted quality. These findings prove the usefulness of the
LRM in predicting and identifying sites of high groundwater
accumulation and groundwater salinity in arid region