Mekelle, Tigray | Ethiopia
Main Specialties: Family Medicine, Nursing, Oncology, Preventive Medicine, Public Health, Statistics
Additional Specialties: General MPH
Experienced Training Coordinator with a demonstrated history of working in the Higher Education Institution and Tertiary care hospital. Skilled in Qualitative & Quantitative Research Methodologies, with excellent Interpersonal Communication, Secondary Data Analysis. Strong program and project management professional with a Master's Degree focused in Public Health from University of Gondar. Area of interest for PhD Study: Social and behavior change communication with a focus on sexual and reproductive health challenges of adolescents, access and quality of cervical cancer prevention and treatment and nutrition behavior school children, implementation research to improve quality of cancer care in developing countries.
Publications1. Predictors of loss to follow up among adult clients attending antiretroviral treatment at Karamara general hospital, Jigjiga town, Eastern Ethiopia, 2015: a retrospective cohort study. BMC Infectious Diseases. June 2018, DOI: 10.1186/s12879-018-3188-4, PMID: 299144002. Coverage, social mobilization and challenges of mass Zithromaxadministrationcampaign in South and South East zones of Tigray, Northern Ethiopia: A cross sectional study. PLoS Negl TropDis 12(2): e0006288.https://doi.org/10.1371/journal. pntd.00062883. Factors associated with diarrheal morbidity among under-five children in Jigjiga town, Somali Regional State, eastern Ethiopia: a cross-sectional study. BMC Pediatrics (2017) 17:182 DOI 10.1186/s12887-017-0934-5
1. From Research to Practice: Training Course in Sexual and Reproductive Health Research from May to November, 2017.
2. Adolescent Sexual and Reproductive Health The Geneva Foundation for Medical Education and Research
3. ICH Good Clinical Practice E6 (R2)
4. Introduction to clinical research
5. Obstetric Fistula
6. Assessing newborn size by Anthropometry
7. Maternal Infections from : The Global Health Network
8. Total quality management etc
9. Secondary data analysis
10. Qualitative research
Primary Affiliation: Mekelle University - Mekelle, Tigray , Ethiopia
www.thelancet.com Vol 392 November 10, 2018
Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10–54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10–14 years and 50–54 years was estimated from data on fertility in women aged 15–19 years and 45–49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-component method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49·4% (95% uncertainty interval [UI] 46·4–52·0). The TFR decreased from 4·7 livebirths (4·5–4·9) to 2·4 livebirths (2·2–2·5), and the ASFR of mothers aged 10–19 years decreased from 37 livebirths (34–40) to 22 livebirths (19–24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83·8 million people per year since 1985. The global population increased by 197·2% (193·3–200·8) since 1950, from 2·6 billion (2·5–2·6) to 7·6 billion (7·4–7·9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2·0%; this rate then remained nearly constant until 1970 and then decreased to 1·1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2·5% in 1963 to 0·7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2·7%. The global average age increased from 26·6 years in 1950 to 32·1 years in 2017, and the proportion of the population that is of working age (age 15–64 years) increased from 59·9% to 65·3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1·0 livebirths (95% UI 0·9–1·2) in Cyprus to a high of 7·1 livebirths (6·8–7·4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0·08 livebirths (0·07–0·09) in South Korea to 2·4 livebirths (2·2–2·6) in Niger, and the TFR over age 30 years (TFO30; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0·3 livebirths (0·3–0·4) in Puerto Rico to a high of 3·1 livebirths (3·0–3·2) in Niger. TFO30 was higher than TFU25 in 145 countries and territories in 2017. 33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2·0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger.
www.thelancet.com Vol 392 November 10, 2018
Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing.
Seifu et al. BMC Infectious Diseases (2018) 18:280
BMC Infectious Diseases
Background: Retention in care and adherence to the treatment is very important for the success of the program while access for treatment is being scaled up. Without more precise data about the rate of loss to follow up as well the characteristics of those who disengage from the treatment appropriate interventions to increase ART adherence cannot be designed and implemented. Therefore the aim of this study was to determine incidence and predictors of loss to follow up among adult ART clients attending in Karamara Hospital, Jigjiga town, Eastern Ethiopia, 2015. Methods: An institutional based retrospective cohort study were undertaken among 1439 adult people living with HIV/AIDS and attending ART clinic between September 1, 2007 and September 1, 2014 at Karamara Hospital was undertaken. Loss to follow up was defined as not taking an ART refill for a period of 90 days or longer from the last attendance for refill and not yet classified as ‘dead’ or ‘transferred-out’. A Kaplan-Meier model was used to estimate rate of time to loss to follow up and Cox proportional hazards modeling was used to identify predictors of loss to follow up among ART clients. Result: Of 1439 patients, 830(58.0%) were females in their sex. The mean age of the cohort was 33.5 years with a standard deviation of 9.33. Around 213 (14.8%) patients were defined as LTFU. The incidence rate of loss to follow up in the cohort was 26.6% (95% CI; 18.1–29.6) per 100 person months. Patients with male sex [HR: 2.1CI;(1.3–3.4)], patients whose next appointment weren’t recorded [HR: 1.2, 95% CI; (1.12–1.36)] and patients who did not disclose their status to any one [HR: 2.8, 95% CI; (2.22–5.23)] were significantly associated with LTFU in the cox proportional model. Conclusion: Overall, these data suggested that LTFU in this study was high. The ART patients’ next appointment should be documented very well and as well the clients should be advised to adhere with treatment program as per the schedule. Defaulter tracing mechanism should be operational and strengthen in the health facility. Effective control measures should be designed for at-risk population such as male patients. Keywords: Loss to follow up, ART, Jigjiga town, Predictors, Eastern Ethiopia
PLOS Neglected Tropical Diseases
Background The antibiotic treatment of people with trachoma helps to prevent transmission the disease in a community. Currently, Zithromax is the drug recommended for mass drug administration (MDA). MDA should be carried out annually for three to five years in trachoma endemic areas. Coverage survey is essential to track progress towards program goals and to identify communities with poor coverage in order to permit timely and appropriate actions. We assessed mass Zithromax administration coverage, social mobilization and campaign challenges in south and southeast zones of Tigray, Ethiopia. Method We conducted a survey in community in Southern and South East zones of Tigray region from August 15 to August 31, 2016. The survey included nine Woredas. It was supported by qualitative methods. A total of 3741 individuals were enrolled from 933 households using multistage sampling. We used structured questionnaire. In-depth interview and focus group discussion were also applied. Descriptive statistics was performed using SPSS version 20. We thematically analyzed the qualitative data using Atlas 7. Result The overall coverage of Zithromax MDA was 93.3%. It ranges from 90.0% in Seharti Samre to 97.9% in Endamokoni. The coverage was 93.4% for males and 93.1% for females. A higher proportion (98.3%) of children aged 5 to 15 years and 409 (87.8%) under five children took Zithromax. The coverage was 94% in rural and 91.2% in urban. Women development army (43.3%) and health extension workers (32.5%) were the main source of information. Frequent occurrence of drug side effects, rumors, lack of community and leaders' engagement in the campaign, fasting, shortage of human power and short term unavailability of supplies were barriers during the campaign. Conclusion The Zithromax MDA coverage in the study zones was higher than the minimum WHO set criteria of 80%. There was a wide difference in coverage among Woredas and Kebeles. The MDA coverage was lower in urban than rural. Misconceptions and poor mobilization were common challenges. Thus, proper planning, community mobilization and uniform training will need to be done ahead of the campaign in the future.
BMC Pediatr 2017 Aug 23;17(1):182. Epub 2017 Aug 23.
Epidemiology and Biostatistics Unit, Department of Public Health, College of Medicine and Health Sciences, Jigjiga University, Jigjiga, Somali Regional State, Ethiopia.
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Am J Physiol 1975 Dec;229(6):1510-3
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