IUJ Volume 5 No.1 2016

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    The impact of women members of parliament on policy outcome affecting children in Ugandan, 2001-2009
    (2016) Kakuba, Sultan Juma
    ARTICLE: The impact of women on decision making in Uganda had been constrained for long because of the patriarchal nature of the societies in the country. But since 1986, women have gained recognition and representation in the Parliament. This has given them a unique opportunity to present and influence issues of their concern into legislation. The study is based on content analysis of parliamentary debates, particularly contributions to issues related to children and subsequent policy outcomes. Using systematic stratified sampling a total of 377 hansards were selected out of 752 corresponding to plenary parliamentary sittings which had been held in the period 2001-2009. With the help of content analysis, data were extracted from the sampled hansards, coded and categorised on issues raised and debated in parliament to promote and protect children. The study findings show that though women were new comers in the Parliament, they displayed that they are equal to the task agitate for legislation to improve the status of children and family issues in Uganda. The study uncovered that women Members of Parliament raised many issues to prioritise the welfare and needs of children into legal framework in the country. These included child labour, child sacrifice/child trafficking, street children defilement and girl child education among others. The study found that this resulted into enacting and amendment of laws such as the Child Act, Expansion of defilement and Persons With Disabilities Act among others. The study concludes that women as mothers and Members of Parliament have achieved some legislation, which can positively impact on the status of children. Therefore, there is need to put these legislation into practice because having them on paper is not good enough to improve on the conditions of children in the country.
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    Analysis of non-linear transmission of EBOLA virus disease and the impact of public health control interventions in hospital: the case of Guinea (West Africa) outbreak 2014.
    (2016) Babangida, Bala Garba; Nazziwa, Aisha; Noor, Kasim; Adiukwu, Roseline Nwawure; Ngaloru, Stellamaris Ngozi; Mafuyai, Yaks Mabur; Obi, Edith Nkeiru; Onwunali, Magnus Chibueze; Obanny, Adolphus
    ARTICLE ABSTRACT Epidemiological data on infection outbreaks are challenging to analyze, despite improved control interventions Ebola virus Disease (EVD) remains a serious risk in Guinea (West Africa) with 607 reported cases and 406 deaths recorded (66.8%) as of 20th August, 2014.In this study we use modified epidemiological modeling SEIR to analyze data from an Ebola outbreak in Guinea from 22nd march – 20th August,2014 We use Bayesian inference with non – linear transmission times incorporated into augmented data set as latent variables. Despite the lack of detailed data, most data sets record the time on symptom onset but transmission time is not observable. We inferred from such dataset records using structured Hidden Markov Models HMMS. Infectivity is determined before and after public health interventions for hospitalized cases. We estimate the number of secondary cases generated by an index case in the absence of control interventions (Ro). Our estimate of Ro is 1.57 (CI95 0.82-1.92) and the mean value of estimated detection rate is 0.75 (CI95 0.59 -0.93) with a coefficient of correlation between 𝛽𝛽 and v as – 0.23. We perform sensitivity analysis of the final epidemic size to the time of intervention, which ensures the uniqueness and the global stability of the positive endemic equilibrium state.
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    Application of Markov chain Modelto foreign debt management in Nigerian economy
    (2016) Ngaloru, Stellamaris Ngozi; Abdulazeez, Halimat; Ebuk, Love E.; Adiukwu, Roseline N; Nafiu, Lukman Abiodun
    ARTICLE ABSTRACT Since the last century, there have been marked changes in the approach to scientific enquiries and greater realisation that probability (or non-deterministic) models are more realistic than deterministic models in many situations. Observations taken at different time points rather than those taken at a fixed period of time began to engage the attention of probabilists. Many stochastic processes occurring in social sciences are studied now not only as a random phenomenon but also as one changing with time or space called Markov chain. This study considered an application of Markov chain model to predict future debt pattern as effective management of any nation’s debt is crucial to growth and development of the economy of that nation. We collected data on debts maintained by all the thirty-six states governments and Federal Capital Territory, Abuja in Nigeria for a period of six years and determined future debt trend based on the transition probabilities between various groups of transition states. Three noticeable transition states namely; rising, stable and dropping of debt trend were used. The findings revealed that 55% of states governments will have a rise in their debt profile, 6% will have a stable debt profile while 39% will have a drop in their debt profile. Therefore, it was recommended that the federal government should design appropriate financing strategies that guarantee a debt path matching loan with the ability to repay and put up a policy as a preventive action to reduce, in the medium term, the possibility of debt unsustainability by the various states governments in Nigeria.
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