Indirect child mortality estimation technique to identify trends of under-five mortality in Ethiopia

Background: In sub-Saharan African countries, the chance of a child dying before the age of five years is high. The problem is similar in Ethiopia, but it shows a decrease over years.Methods: The 2000; 2005 and 2011 Ethiopian Demographic and Health Survey results were used for this work. The purpose of the study is to detect the pattern of under-five child mortality overtime. Indirect child mortality estimation technique is adapted to examine the under-five child mortality trend in Ethiopia.Results: From the result, it was possible to see the trend of under-five child mortality in Ethiopia. The under-five child mortality shows a decline in Ethiopia.Conclusion: From the study, it can be seen that there is a positive correlation between mother and child survival which is almost certain in any population. Therefore, this study shows the trend of under-five mortality in Ethiopia and decline over time.Keywords: EDHS, under-five mortality, parity, indirect technique, CEB, children survivin

Factors affecting child malnutrition in Ethiopia

Background: One of the public health problems in developing countries is child malnutrition. An important factor for children’s well-being is good nutrition. Therefore, the malnutrition status of children under the age of five is an important outcome measure for children’s health. This study uses the proportional odds model to identify risk factors associated with child malnutrition in Ethiopia using the 2016 Ethiopian Demographic and Health Survey data.Methods: This study uses the 2016 Ethiopian Demographic and Health Survey results. Based on weight-for-height anthropometric index (Z-score) child nutrition status is categorized into four levels namely- underweight, normal, overweight and obese. Since this leads to an ordinal variable for nutrition status, an ordinal logistic regression (OLR)proportional odds model (POM) is an obvious choice for analysis.Results: The findings and comparison of results using the cumulative logit model with and without complex survey design are presented. The study results revealed that to produce the appropriate estimates and standard errors for data that were obtained from complex survey design, model fitting based on taking the survey sampling design into account is better. It has also been found that for children under the age of five, weight of a child at birth, mother’s age, mother’s Body Mass Index (BMI), marital status of mother and region (Affar, Dire Dawa, Gambela, Harari and Somali) were influential variables significantly associated with underfive children’s nutritional status in Ethiopia.Conclusion: This child’s age of a child, sex, weight of child at birth, mother’s BMI and region of residence were significant determinants of malnutrition of children under five years in Ethiopia. The effect of these determinants can be used to develop strategies for reducing child malnutrition in Ethiopia. Moreover, these findings show that OLR proportional odds model is appropriate assessing thedeterminants of malnutrition for ordinal nutritional status of underfive children in Ethiopia.Keywords: BMI, Ethiopian Demographic and Health Survey (EDHS), malnutrition, proportional odds model

Using joint models to study the association between CD4 count and the risk of death in TB/HIV data

BACKGROUND: The association structure linking the longitudinal and survival sub-models is of fundamental importance in the joint modeling framework and the choice of this structure should be made based on the clinical background of the study. However, this information may not always be accessible and rationale for selecting this association structure has received relatively little attention in the literature. To this end, we aim to explore four alternative functional forms of the association structure between the CD4 count and the risk of death and provide rationale for selecting the optimal association structure for our data. We also aim to compare the results obtained from the joint model to those obtained from the time-varying Cox model. METHODS: We used data from the Centre for the AIDS Programme of Research in South Africa (CAPRISA) AIDS Treatment programme, the Starting Antiretroviral Therapy at Three Points in Tuberculosis (SAPiT) study, an open-label, three armed randomised, controlled trial between June 2005 and July 2010 (N=642). In our analysis, we combined the early and late integrated arms and compared results to the sequential arm. We utilized the Deviance Information Criterion (DIC) to select the final model with the best structure, with smaller values indicating better model adjustments to the data. RESULTS: Patient characteristics were similar across the study arms. Combined integrated therapy arms had a reduction of 55% in mortality (HR:0.45, 95% CI:0.28-0.72) compared to the sequential therapy arm. The joint model with a cumulative effects functional form was chosen as the best association structure. In particular, our joint model found that the area under the longitudinal profile of CD4 count was strongly associated with a 21% reduction in mortality (HR:0.79, 95% CI:0.72-0.86). Where as results from the time-varying Cox model showed a 19% reduction in mortality (HR:0.81, 95% CI:0.77-0.84). CONCLUSIONS: In this paper we have shown that the “current value” association structure is not always the best structure that expresses the correct relationship between the outcomes in all settings, which is why it is crucial to explore alternative clinically meaningful association structures that links the longitudinal and survival processes

Indirect child mortality estimation technique to identify trends of under-five mortality in Ethiopia.

Background: In sub-Saharan African countries, the chance of a child dying before the age of five years is high. The problem is similar in Ethiopia, but it shows a decrease over years. Methods: The 2000; 2005 and 2011 Ethiopian Demographic and Health Survey results were used for this work. The purpose of the study is to detect the pattern of under-five child mortality overtime. Indirect child mortality estimation technique is adapted to examine the under-five child mortality trend in Ethiopia. Results: From the result, it was possible to see the trend of under-five child mortality in Ethiopia. The under-five child mortality shows a decline in Ethiopia. Conclusion: From the study, it can be seen that there is a positive correlation between mother and child survival which is almost certain in any population. Therefore, this study shows the trend of under-five mortality in Ethiopia and decline over time

Spatiotemporal patterns of successful TB treatment outcomes among HIV co-infected patients in Kenya

Paper presented at the 5th Strathmore International Mathematics Conference (SIMC 2019), 12 - 16 August 2019, Strathmore University, Nairobi, KenyaConvergence of the Tuberculosis (TB) and HIV epidemics threatens the management of TB treatment. These has been evidenced by various studies describing how HIV cc-infection propagates unsuccessful TB treatment outcomes. Information on the spatiotemporal patterns of successful TB treatment outcomes remain less understood despite the multi-organizational TB treatment efforts. This study uses case notification data to evaluate the spatiotemporal patterns of successful TB treatment outcomes for HIV co-infected patients in Kenya. This study used the case notification data from the Kenya National TB control program to investigate successful TB treatment outcomes in forty-seven counties in the period 2012 - 2017. The population of study was HIV co-infected cases with known TB treatment outcome. Achi-squre test was performed to determine the association between treatment outcomes and risk factors; TB- type, age, gender, ART therapy and patient type. The study also assessed the geographic patterns and temporal trends by mapping the TB treatment success rate in each county for the six-year period. Using the Integrated Nested Laplace Approach (INLA), the TB treatment success of HIV co-infected patients was modeled. The spatial parameters assumed the BesagYork-Mollie (BYM) specification. The temporally structured effect was represented through a neighboring structure and the temporally unstructured effects using a Gaussian exchangeable prior. Among the 172233 HIV co-infected cases included in the analysis, 135973 (78.9%) achieved successful TB treatment outcomes. Female cases registered higher treatment success rates (80.1%) compared to the male cases (77.8%). The cases on Anti-Retroviral Therapy (ART) recorded a success rate of 79.9% against 69.1% for their counterpart not on ART. The spatial trend depicted increased treatment success in some parts of the country with a relatively high level of associated certainty, characterized by a spatial relative success above 1 and posterior probabilities above 0.8. The temporal trend of treatment success showed an increase in the treatment success of TB in HIV coinfected cases. Overall, the success rate was still below 85% particularly for Homabay, Siaya, Kisumu, Migori and Busia counties in western Kenya. The successful TB treatment outcomes for HIV coinfected cases in Kenya were slightly below the 85% standard threshold set by the World Health Organization. Our study showed that even though co-infected cases have an increased risk of unsuccessful treatment outcomes, enhanced treatment monitoring improved the treatment outcome in most counties for the six-year period.Department of Mathematical Sciences, Pan African University Institute of Basic Sciences Technology and Innovation, Nairobi, Kenya Epidemiology and Biostatistics Division, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa. School of Mathematics, Statistics Computer Science, University of Kwa-Zulu Natal, Pietermaritzburg, South Africa

Modelling CD4 counts before and after HAART for HIV infected patients in KwaZulu-Natal South Africa

Background: This study aims to make use of a longitudinal data modelling approach to analyze data on the number of CD4+cell counts measured repeatedly in HIV-1 Subtype C infected women enrolled in the Acute Infection Study of the Centre for the AIDS Programme of Research in South Africa. Methodology: This study uses data from the CAPRISA 002 Acute Infection Study, which was conducted in South Africa. This cohort study observed N=235 incident HIV-1 positive women whose disease biomarkers were measured repeatedly at least four times on each participant. Results: From the findings of this study, post-HAART initiation, baseline viral load, and the prevalence of obese nutrition status were found to be major significant factors on the prognosis CD4+ count of HIV-infected patients. Conclusion: Effective HAART initiation immediately after HIV exposure is necessary to suppress the increase of viral loads to induce potential ART benefits that accrue over time. The data showed evidence of strong individual-specific effects on the evolution of CD4+ counts. Effective monitoring and modelling of disease biomarkers are essential to help inform methods that can be put in place to suppress viral loads for maximum ART benefits that can be accrued over time at an individual level

Factors affecting child malnutrition in Ethiopia

Background: One of the public health problems in developing countries is child malnutrition. An important factor for children\u2019s well-being is good nutrition. Therefore, the malnutrition status of children under the age of five is an important outcome measure for children\u2019s health. This study uses the proportional odds model to identify risk factors associated with child malnutrition in Ethiopia using the 2016 Ethiopian Demographic and Health Survey data. Methods: This study uses the 2016 Ethiopian Demographic and Health Survey results. Based on weight-for-height anthropometric index (Z-score) child nutrition status is categorized into four levels namely- underweight, normal, overweight and obese. Since this leads to an ordinal variable for nutrition status, an ordinal logistic regression (OLR)proportional odds model (POM) is an obvious choice for analysis. Results: The findings and comparison of results using the cumulative logit model with and without complex survey design are presented. The study results revealed that to produce the appropriate estimates and standard errors for data that were obtained from complex survey design, model fitting based on taking the survey sampling design into account is better. It has also been found that for children under the age of five, weight of a child at birth, mother\u2019s age, mother\u2019s Body Mass Index (BMI), marital status of mother and region (Affar, Dire Dawa, Gambela, Harari and Somali) were influential variables significantly associated with underfive children\u2019s nutritional status in Ethiopia. Conclusion: This child\u2019s age of a child, sex, weight of child at birth, mother\u2019s BMI and region of residence were significant determinants of malnutrition of children under five years in Ethiopia. The effect of these determinants can be used to develop strategies for reducing child malnutrition in Ethiopia. Moreover, these findings show that OLR proportional odds model is appropriate assessing thedeterminants of malnutrition for ordinal nutritional status of underfive children in Ethiopia. DOI: https://dx.doi.org/10.4314/ahs.v19i2.13 Cite as: Yirga AA, Mwambi HG, Ayele DG, Melesse SF. Factors affecting child malnutrition in Ethiopia. Afri Health Sci.2019;19(2): 1897-1909. https://dx.doi.org/10.4314/ahs.v19i2.1

Meta-analysis of effect sizes reported at multiple time points using general linear mixed model

Meta-analysis of longitudinal studies combines effect sizes measured at pre-determined time points. The most common approach involves performing separate univariate metaanalyses at individual time points. This simplistic approach ignores dependence between longitudinal effect sizes, which might result in less precise parameter estimates. In this paper, we show how to conduct a meta-analysis of longitudinal effect sizes where we contrast different covariance structures for dependence between effect sizes, both within and between studies. We propose new combinations of covariance structures for the dependence between effect size and utilize a practical example involving meta-analysis of 17 trials comparing postoperative treatments for a type of cancer, where survival is measured at 6, 12, 18 and 24 months post randomization. Although the results from this particular data set show the benefit of accounting for within-study serial correlation between effect sizes, simulations are required to confirm these results.S1 Fig. R-code for meta-analysis.http://www.plosone.orgam2016Statistic