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Estimating the Age at HIV Infection Retroactively in Limited Resource Settings: A Case Study of Tanzania
Theresia Bonifasi Mkenda,
Kaku Sagary Nokoe,
Samuel Githinji Karoki
Issue:
Volume 8, Issue 4, July 2019
Pages:
125-135
Received:
25 June 2019
Accepted:
18 July 2019
Published:
10 August 2019
Abstract: Estimation of HIV infection time is a crucial step in HIV/AIDS management as it can help to make informed decisions on the best intervention strategies for controlling new infections, and for taking care of the infected individuals. This study demonstrates three approaches for estimating the age at HIV infection in limited resource settings. Using HIV testing history data collected from a sample of 88 HIV positive women in Kilimanjaro region-Tanzania, we developed a model for estimating the most likely age at which HIV infection occurs for women under reproductive age. The sampled data were collected from typical poor resource settings where access to data is very challenging and the gap between last HIV negative test and first HIV positive test is wide. Formulation of the proposed model involved three steps. Through Modified Midpoint approach, we first determined the midpoint of the age at last negative HIV test and the age at first positive HIV test for each subject. Then, the average time at risk prior to infection, taken over all individuals was subtracted from each midpoint value to obtain the distribution of their estimated age at HIV infection (T). In the second step, survival analysis techniques were used to obtain the Kaplan Meier plots and Nelson Aalen cumulative hazards estimates in which the median age for HIV infection and the most risky age were estimated. The plots of Kaplan Meir survival curves for women with different marital status and levels of education helped to assess whether their age at infection were significantly different. In the third step, we used bootstrap estimation procedures to generate 200 samples of random data and obtain the bootstrap median age at HIV infection and its confidence intervals. The estimated median age at HIV infection from survival analysis approach was 28 years while from bootstrap estimation procedures was 27 years. Likewise, the Nelson Aalen cumulative hazards plot indicated that the most risky age for HIV infection is between 18-40 years while the most risky age from bootstrap estimation was 25 to 27 years. The confidence intervals obtained through bootstrap estimation approach was narrower than that obtained from the survival analysis approach, implying that the bootstrap approach gives more precise estimates. Generally, the study findings provide useful information towards the attainment of the 90-90-90 global HIV/AIDS target as it shows where to allocate more resources and establish more focused interventions for HIV/AIDS management and control.
Abstract: Estimation of HIV infection time is a crucial step in HIV/AIDS management as it can help to make informed decisions on the best intervention strategies for controlling new infections, and for taking care of the infected individuals. This study demonstrates three approaches for estimating the age at HIV infection in limited resource settings. Using ...
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Use of Alpha-Designs in Oil Palm Breeding Trials
Issue:
Volume 8, Issue 4, July 2019
Pages:
136-146
Received:
26 June 2019
Accepted:
1 August 2019
Published:
14 August 2019
Abstract: In Oil Palm Breeding trials the plots have palms at vertices of equilateral triangles with side length of 9 m. The plots consist of 6x6 = 36 palms, hence a plot is a rectangle of 46.8 x 54m. The number of tested varieties is 20 – 40, the experimental design needed is an incomplete block design, with usually 3 replications; the alpha-designs can give a connected incomplete block design. Current Oil Palm planting materials are DxP hybrid based on crossing selected dura palms (female parents) with pisifera palms (male parents) to produce tenera palms with thin shelled fruits. The crossing scheme of A dura and B pisifera is an incomplete diallel if he number of crossings C is smaller than A*B. To make a connected crossing scheme the alpha-design can be used. In the analysis of an oil palm breeding trial an additive model of the dura and pisifera effects is applied to estimate the general combining ability of the parents after removing the fixed replication effect and the random blocks within the replication effects. The analysis can be done with the package SAS or IBM SPSS Statistics with program Mixed; further with R and the R package lme4.
Abstract: In Oil Palm Breeding trials the plots have palms at vertices of equilateral triangles with side length of 9 m. The plots consist of 6x6 = 36 palms, hence a plot is a rectangle of 46.8 x 54m. The number of tested varieties is 20 – 40, the experimental design needed is an incomplete block design, with usually 3 replications; the alpha-designs can giv...
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Factors That Affect the Growth of Micro and Small Scale Enterprises in DebreBerhan Town
Issue:
Volume 8, Issue 4, July 2019
Pages:
147-156
Received:
2 July 2019
Accepted:
30 July 2019
Published:
23 August 2019
Abstract: Micro and Small Enterprises (MSEs) in DebreBerhan town does not show necessary growth level and some of the enterprises ceased from market in their infant age. Hence, this study conducted with the objective of assessing factors affecting growth of micro and small enterprises in DebreBerhan town. The study has used both descriptive and explanatory research designed. Data for the analyses collected through questionnaire and focus group discussions. The study has used stratified random sampling technique to select 109 MSES from 1511 fond in DebreBerhan town. The study has used correlation and regressions to establish the relationship between variables. Correlation coefficients revealed a significant relationship between the factors and growths of MSEs (current capital). Variables such as initial capital, access of infrastructure, technology use, habit of receiving feedbacks from customer, profitability of business and government motivation are positively influence to growth of MSEs (profit). Hence improving those variables increase growth of MSEs (current capital). Multiple regression analysis has also revealed that 60.6% the variation in response variable (current capital) is explained by predictor variables and improving those variables increase growth of MSEs (capital). The study recommends that MSEs Office could be transparent at the time of allocating the working place to the MSEs, better to design close supervisor of MSEs and linking the MSEs with other private contractors working around DebreBerhan town, support the establishment and strength of business development services. Moreover, in order to reduce the influence of factors on growth of MSEs, policy makers and the service provider institutions need to consider and revise the extent, intensity, and quality of support and their linkages.
Abstract: Micro and Small Enterprises (MSEs) in DebreBerhan town does not show necessary growth level and some of the enterprises ceased from market in their infant age. Hence, this study conducted with the objective of assessing factors affecting growth of micro and small enterprises in DebreBerhan town. The study has used both descriptive and explanatory r...
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