Summaryobjective To estimate the female sex worker population size in three cities in Cô te d'Ivoire and in Kisumu, Kenya.methods Capture-recapture was used, calculating size estimates by first 'tagging' a number of individuals and, through an independent recapture, calculating the proportion of overlap. The same procedures were used in all four cities. In the first phase, members of the target population were 'captured' and 'marked' by giving them a capture card. Six days later, in the same places and at the same time, a second sample was 'captured', which comprised a certain number of people who were captured in the first round. During the exercise, questions were asked to estimate the coverage of the sex worker clinics. conclusions Capture-recapture was successfully applied to estimate the population size of female sex workers. These estimations were urgently needed to help mobilize an increased response to HIV, to assess programme coverage and to estimate potential impact of the targeted intervention.
The percentage of university students currently nursing chronic infections/diseases is alarming, and for a long time, these students are ever thought to be healthy. However, research shows otherwise and management of students’ health should be recognized and efforts be directed towards the same. This paper aimed to review the work done by other researchers concerning university students when it comes to chronic diseases and their health, make general comments and emphasize the need to have stakeholders focus on university students in terms of acquiring the right and modern technology meet for dealing with the elephant in the room. About 25 published papers were selected from the internet as they came across and a summary was made from each on what the researchers found concerning the university students’ health and chronic diseases. It was found that no researcher didn’t find unhealthy students and up to 30% of the students can be found infected in a given university. All concluded that the health of the students is deteriorating with time. Therefore, there is a need for stakeholders such as university managements, governments, non-governmental organizations among others to deal with the situation before it’s too late. University students are the next-immediate workforce and their health should not be left to fate. Once this workforce is maimed, there shall be a big problem in the future when things slip out of hand.
There are numerous designs for fitting second order models that can be used in conjunction with the response surface methodology (RSM) technique in optimization processes, be it in agriculture, industries and so on. Some of the designs include the equiradial, Notz, San Cristobal, Koshal, Hoke, Central Composite and Factorial designs. However, RSM can only be applied in conjunction with a single design at a time. This research aimed at choosing a design out of the most widely employed designs for fitting 2nd order models involving 3 factors for optimization of French beans in conjunction with the RSM technique. The most commonly used designs for second order models were first identified as Box-Behnken designs, Hoke D2 and Hoke D6 designs, 3k factorial designs, CCD face centred, CCD rotatable and CCD spherical. Design matrices for these 7 designs were formed and augmented with 5 centre points (chosen through lottery methods), and information and optimal design matrices were formed. Then, for each design, the analysis of D-, A- E-, T- optimality (D-Determinant, A-Average Variance, E-Eigen Value and T-Trace) was carried out according to Pukelsheim’s definitions. The results were ranked for each criterion and the ranks corresponding to each design were averaged. The design chosen was Hoke D2 with the least average- 1.75. The Hoke D2 was found to be optimal in minimizing the variance of prediction and the most economical design among the seven. The findings are in agreement with other researchers and scientist that a design may be optimal in one criterion but fails in another criterion. Further, Hoke designs are in the class of the economical designs. It is recommended that more optimality criteria be applied and a wide range of designs be involved to see whether the results would still agree with these findings.
The percentage of university students currently nursing chronic diseases including but not limited to depression, HIV/AIDs, asthma, stroke and chronic kidney diseases, is alarming, and for a long time, these students are ever thought to be healthy. However, research shows otherwise with up to 30% of the students nursing the diseases. Previous research worldwide shows that up to 30% of university students can be infected at a given time. This research aimed to investigate the issues concerning chronic diseases among university students in Kenya. The specific objectives included estimation of the percentage of students currently suffering from the diseases, determining their effects and factors associated with them. The mixed-study design was applied. Random sampling was done among students in two selected universities in Kenya and a questionnaire was used in data collection. 739 students responded to the research questions. Minitab, SPSS and R software were involved in data management for comparison purpose, especially for statistically significant results. From the analysis, currently, there are approximately 14.6% of the students are suffering from chronic diseases, and this proportion is significant (p-value<0.0001). Among the infected, 60.19% were females and the rest were males. Among the sick, only 43.52% have let the university clinics know about their conditions while more than 50% have concealed the vital information. The factors ‘family history’, ‘involvement in drugs’, ‘adopted life-styles’ and ‘extreme poverty’ were found to be significantly associated with chronic diseases among the students. On the effects, the diseases were found to be negatively affecting the aspects of life of the infected students. Survival of the students was found to be having a mean and median survival time of 29.9472 and 30.27 years respectively. It is concluded that there is need for intervention among university students as 14.6% is not a number to be ignored. It is recommended that the stakeholders to come together and arrest the situation before things slip out of hand.
Globally, infant mortality is used as an important indicator for healthcare status hence an important tool for evaluation and planning of public health strategies. Despite of numerous interventions by governments aimed at reducing infant mortality, high rates are still reported in Kenya. A lot of resources are channeled towards its control leading to low productivity hence impacting the household economic welfare and national GD. The specific objective was to establish risk factors and the spatial variation of infant mortality in Kenya by analyzing the 2014 Kenya Demographic Health Survey data. A fully Bayesian paradigm and logistic regression model were used to determine infant mortality risk factors and spatial variation in Kenya. Demographic, socioeconomic and environmental factors were found to have significant effect on infant mortality. Counties from the northern parts of Kenya, Rift Valley, Central, Eastern, Nyanza, Coastal and Western parts of Kenya showed a high level of infant deaths. Infant mortality is high in arid and semi-arid areas and coastal areas due to high prevalence of infectious diseases and inadequate water supply, health facilities and low education levels. Infant mortality varies significantly across regions in Kenya due to cultural activities, and weather patterns hence exists spatial autocorrelation among neighboring regions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.