Sebsibe Tadesse

Validating the InterVA Model to Estimate the Burden of Mortality from Verbal Autopsy Data: A Population-Based Cross-Sectional Study

Background In countries with incomplete or no vital registration systems, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. But in addition to being time and energy consuming, the method is liable to produce inconsistent results. The aim of this study is to validate the InterVA model for estimating the burden of mortality from verbal autopsy data by using physician review as a reference standard. Methods and Findings A population-based cross-sectional study was conducted from March to April, 2012. All adults aged ≥14 years and died between 01 January, 2010 and 15 February, 2012 were included in the study. The verbal autopsy interviews were reviewed by the InterVA model and physicians to estimate cause-specific mortality fractions. Cohen’s kappa statistic, sensitivity, specificity, positive predictive value, and negative predictive value were applied to compare the agreement between the InterVA model and the physician review. A total of 408 adult deaths were studied. There was a general similarity and just slight differences between the InterVA model and the physicians in assigning cause-specific mortality. Both approaches showed an overall agreement in 298 (73%) cases [kappa = 0.49, 95% CI: 0.37-0.60]. The observed sensitivities and specificities across causes of death categories varied from 13.3% to 81.9% and 77.7% to 99.5%, respectively. Conclusions In understanding the burden of disease and setting health intervention priorities in areas that lack reliable vital registration systems, an accurate analysis of verbal autopsies is essential. Therefore, users should be aware of the suboptimal performance of the InterVA model. Similar validation studies need to be undertaken considering the limitation of the physician review as gold standard since physicians may misinterpret some of the verbal autopsy data and finally reach a wrong conclusion of the cause of death.

Evaluating the performance of interpreting Verbal Autopsy 3.2 model for establishing pulmonary tuberculosis as a cause of death in Ethiopia: a population-based cross-sectional study.

BackgroundIn resource- poor settings, verbal autopsy data are often reviewed by physicians in order to assign the probable cause of death. But in addition to being time and energy consuming, the method is liable to produce inconsistent results. The aim of this study is to evaluate the performance of the InterVA 3.2 model for establishing pulmonary tuberculosis as a cause of death in comparison with physician review of verbal autopsy data.MethodsA population-based cross-sectional study was conducted from March to April, 2012. All adults aged ≥14 years and died between 01 January 2010 and 15 February 2012 were included in the study. Data were collected by using a pre-tested and modified WHO designed verbal autopsy questionnaire. The verbal autopsy interviews were reviewed by the InterVA model and the physicians. Cohen’s kappa statistic, receiver operating characteristic curves, sensitivity, and specificity values were applied to compare the agreement between the InterVA model and the physician review.ResultsA total of 408 adult deaths were studied. The proportion of tuberculosis-specific mortality was established to be 36.0% and 23.0% by the InterVA model and the physicians, respectively. The InterVA model predicted pulmonary tuberculosis as a cause of death with the probability of 0.80 (95% CI: 0.75-0.85). In classifying all deaths as tuberculosis and non-tuberculosis, the sensitivity and specificity values were 0.82 and 0.78, respectively. A moderate agreement was found between the model and physicians in assigning pulmonary tuberculosis as a cause of deaths [kappa= 0.5; 95% CI: (0.4-0.6)].ConclusionsThis study has revealed that the InterVA model showed a more promising result as a community-level tool for generating pulmonary tuberculosis-specific mortality data from verbal autopsy. The conclusion is believed to provide policymakers with a highly needed piece of information for allocating resources for health intervention.

Stigma against Tuberculosis Patients in Addis Ababa, Ethiopia.

Background Stigma attached to tuberculosis contributes to the limited effectiveness of current TB control approaches. However, there is a dearth of studies that explore the causes of stigma attached to tuberculosis and its effects on patients and tuberculosiscontrol programs in Ethiopia. Methods An institution-based qualitative study was conducted at St. Peter Tuberculosis Specialized Hospital in Addis Ababa, Ethiopia from July to August, 2015. Ten in-depth interviews and 6 key-informant interviews were carried out among tuberculosis patients and healthcare workers, respectively.The Open Code computer software package was used to analyze the data thematically. Results The study revealed that fear of infection and inappropriate health education messages by media were the main causes of tuberculosis stigma. The patients experienced isolation within their family and community, separation, and financial crisis. The stigma attached to tuberculosis may contribute to delayed healthcare seeking, poor treatment adherence, and poor prognosis. Conclusion Interventions thatreduce the stigma attached to tuberculosis should target on areas, such as creating community awareness, patient counseling on problem-solving and emotional skills, preparing culturally sensitive and scientifically sound media messages, providing financial support for the patients, and enhancing the qualities of the healthcare workers, such as empathy, concern, respect for the patient and cultural sensitivity.

Appropriate health-seeking behavior and associated factors among people who had cough for at least two weeks in northwest Ethiopia: a population-based cross-sectional study.

BackgroundTuberculosis remains the major debilitating public health problem in Ethiopia. However, studies to understand the patients’ perspectives on the illness and their health-seeking behavior have been few in the country. In this study, we seek to investigate the magnitude of appropriate health-seeking behavior and factors associated with tuberculosis among people who had cough for at least two weeks.MethodsA population-based cross-sectional study was conducted from July to October 2012 in Dabat, northwest Ethiopia. All people aged ≥15 years and had cough for at least two weeks were included in the study. Data collected by using a pre-tested and structured questionnaire were entered and cleaned using the Epi Info version 2002 statistical software. The statistical Package for the Social Sciences Version 16.0 was also employed for descriptive and logistics regression analysis.ResultsOut of the 25,701 people aged ≥15 years surveyed, the proportion of people who had cough for at least two weeks was reported to be 843(3.3%). Appropriate health-seeking behavior towards tuberculosis was reported by 674(80.0%) of them. Factors significantly associated with health-seeking behavior for tuberculosis were being female [AOR: 0.56, 95%CI: (0.39-0.79)], high monthly real per capita income [AOR: 1.66, 95%CI: (1.15-2.38)], large family size [AOR: 0.50, 95%CI: (0.35-0.72)], and use of traditional-healing practices [AOR: 13.27, 95%CI: (9.10-25.41)].ConclusionThis study showed that the magnitude of appropriate health-seeking behavior during the event of chronic cough was high. However, this doesn’t mean that there will be no need for further strengthening of the intervention activities as significant proportions of the study communities still demonstrate inappropriate health-seeking behavior. So tuberculosis control programs need to emphasize factors, such as sex, family size, socioeconomic inequalities, and traditional-healing practices in resource-poor settings.

Spatial and space-time clustering of tuberculosis in Gurage Zone, Southern Ethiopia

Introduction Spatial targeting is advocated as an effective method that contributes for achieving tuberculosis control in high-burden countries. However, there is a paucity of studies clarifying the spatial nature of the disease in these countries. This study aims to identify the location, size and risk of purely spatial and space-time clusters for high occurrence of tuberculosis in Gurage Zone, Southern Ethiopia during 2007 to 2016. Materials and methods A total of 15,805 patient data that were retrieved from unit TB registers were included in the final analyses. The spatial and space-time cluster analyses were performed using the global Moran’s I, Getis-Ord Gi* and Kulldorff’s scan statistics. Results Eleven purely spatial and three space-time clusters were detected (P <0.001).The clusters were concentrated in border areas of the Gurage Zone. There were considerable spatial variations in the risk of tuberculosis by year during the study period. Conclusions This study showed that tuberculosis clusters were mainly concentrated at border areas of the Gurage Zone during the study period, suggesting that there has been sustained transmission of the disease within these locations. The findings may help intensify the implementation of tuberculosis control activities in these locations. Further study is warranted to explore the roles of various ecological factors on the observed spatial distribution of tuberculosis.

Awareness of occupational hazards and associated factors among welders in Lideta Sub-City, Addis Ababa, Ethiopia

BackgroundWelding is a manufacturing industry where workers could be exposed to several hazards. However, there is a dearth of studies clarifying the situation in Ethiopia. The present study determined the level of awareness of occupational hazards and associated factors among welding employees at Lideta Sub-City, Addis Ababa, Ethiopia.MethodsA work site-based cross-sectional study was conducted among welding employees Lideta Sub-City, Addis Ababa, Ethiopia from April to May 2015. Stratified sampling followed by simple random sampling techniques was used to select the study participants. A pilot tested and structured questionnaire was used to collect data. Multivariable analyses were employed to see the effect of explanatory variables on workers’ awareness of occupational hazards.ResultsAccording to our criteria of awareness 86.5 % of surveyed workers were aware of occupational hazards. A higher work experience, presence of work regulation, job satisfaction, being married, being single, and a higher educational status were factors significantly associated with workers’ awareness of occupational hazards.ConclusionThis study revealed that the level of awareness of occupational hazards among welders was high. However, this does not mean that there will be no need for further strengthening of the safety measures as significant proportions of the workers still had low awareness. Interventions to boost workers awareness of occupational hazards should focus on areas, such as provision of safety trainings, promotion of safety advocacy, and enforcement of appropriate workplace safety regulation.

Estimating the spatial risk of tuberculosis distribution in Gurage zone, southern Ethiopia: a geostatistical kriging approach

BackgroundIn low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets.MethodsA total of 1601 patient data that were retrieved from unit tuberculosis registers were included in the final analyses. The population and geo-location data were obtained from the Central Statistical Agency of Ethiopia. Altitude data were extracted from ASTER Global Digital Elevation Model Version 2. Aggregated datasets from sample of 169(40%), 254(60%) and 338(80%) kebeles were used to estimate the spatial risk of TB distribution in the Gurage Zone by using a geostatistical kriging approach. The best set of input parameters were decided based on the lowest prediction error criteria of the cross-validation technique. ArcGIS 10.2 was used for the spatial data analyses.ResultsThe best semivariogram models were the Pentaspherical, Rational Quadratic, and K-Bessel for the 40, 60 and 80% spatial datasets, respectively. The predictive accuracies of the models have improved with the true anisotropy, altitude and latitude covariates, the change in detrending pattern from local to global, and the increase in size of spatial dataset. The risk of tuberculosis was estimated to be higher at western, northwest, southwest and southeast parts of the study area, and crossed between high and low at west-central parts.ConclusionThis study has underlined that the geostatistical kriging approach can be applied to estimate the spatial risk of tuberculosis distribution in data limited settings. The estimation results may help local public health authorities measure burden of the disease at all locations, identify geographical areas that require more attention, and evaluate the impacts of intervention programs.