Mr Habtamu Bizuayehu

Background. The major mode of HIV transmission in many resource-limited settings is via heterosexual intercourse, but the primary risk factor for youth is primarily through perinatal infection. With the maturing of the HIV epidemic, youth who acquired the virus perinatally are now reaching adolescence and becoming young adults. There is a paucity of data on the sexual practices of perinatally infected youth in Ethiopia. Methods. This a cross-sectional study among 343 HIV positive youths receiving HIV care and treatment in the two hospitals in northwest Ethiopia. A self-administered questionnaire was administered among those who were able to read and write, and the questionnaire was administered by a trained study team member for those who were illiterate. Data were entered using Epi data version 3.5 and analyzed using SPSS. Sexual behaviors of the two groups were compared using bivariate logistic regression and the significant ones were further analyzed using multivariate logistic regression. Statistical significance was declared at 95% confidence interval and P-value less than 0.05. Result. About (63.3%) were females, and 177 (51.6%) were between 20 and 24 years of age. The modes of HIV acquisition were 133 (35%) through perinatal HIV infection, 120 (35%) through sexual contact, 27 (7.9%) through exposure to HIV infected sharp materials, and 63 (18.4%) unsure how they acquired HIV. More than half 155 (59.3%) had multiple sexual partners, and 50 (63.3%) of their sexual partners were HIV negative. Among those who were sexually active, only 77 (56.2%) use a condom consistently. Conclusions. More children who acquired HIV from their mothers are joining the youth population. Their sexual behavior is similar to those youth with behaviorally acquired HIV. There is significant risky sexual behavior among both groups. There is great urgency to effectively address the HIV the prevention strategy to break the cycle of ¿transgenerational¿ infection.

Background: An adequate amount of prepaid resources for health is important to ensure access to health services and for the pursuit of universal health coverage. Previous studies on global health financing have described the relationship between economic development and health financing. In this study, we further explore global health financing trends and examine how the sources of funds used, types of services purchased, and development assistance for health disbursed change with economic development. We also identify countries that deviate from the trends. Methods: We estimated national health spending by type of care and by source, including development assistance for health, based on a diverse set of data including programme reports, budget data, national estimates, and 964 National Health Accounts. These data represent health spending for 184 countries from 1995 through 2014. We converted these data into a common inflation-adjusted and purchasing power-adjusted currency, and used non-linear regression methods to model the relationship between health financing, time, and economic development. Findings: Between 1995 and 2014, economic development was positively associated with total health spending and a shift away from a reliance on development assistance and out-of-pocket (OOP) towards government spending. The largest absolute increase in spending was in high-income countries, which increased to purchasing power-adjusted $5221 per capita based on an annual growth rate of 3.0%. The largest health spending growth rates were in upper-middle-income (5.9) and lower-middle-income groups (5.0), which both increased spending at more than 5% per year, and spent $914 and $267 per capita in 2014, respectively. Spending in low-income countries grew nearly as fast, at 4.6%, and health spending increased from $51 to $120 per capita. In 2014, 59.2% of all health spending was financed by the government, although in low-income and lower-middle-income countries, 29.1% and 58.0% of spending was OOP spending and 35.7% and 3.0% of spending was development assistance. Recent growth in development assistance for health has been tepid; between 2010 and 2016, it grew annually at 1.8%, and reached US$37.6 billion in 2016. Nonetheless, there is a great deal of variation revolving around these averages. 29 countries spend at least 50% more than expected per capita, based on their level of economic development alone, whereas 11 countries spend less than 50% their expected amount. Interpretation: Health spending remains disparate, with low-income and lower-middle-income countries increasing spending in absolute terms the least, and relying heavily on OOP spending and development assistance. Moreover, tremendous variation shows that neither time nor economic development guarantee adequate prepaid health resources, which are vital for the pursuit of universal health coverage.

Background: The amount of resources, particularly prepaid resources, available for health can affect access to health care and health outcomes. Although health spending tends to increase with economic development, tremendous variation exists among health financing systems. Estimates of future spending can be beneficial for policy makers and planners, and can identify financing gaps. In this study, we estimate future gross domestic product (GDP), all-sector government spending, and health spending disaggregated by source, and we compare expected future spending to potential future spending. Methods: We extracted GDP, government spending in 184 countries from 1980-2015, and health spend data from 1995-2014. We used a series of ensemble models to estimate future GDP, all-sector government spending, development assistance for health, and government, out-of-pocket, and prepaid private health spending through 2040. We used frontier analyses to identify patterns exhibited by the countries that dedicate the most funding to health, and used these frontiers to estimate potential health spending for each low-income or middle-income country. All estimates are inflation and purchasing power adjusted. Findings: We estimated that global spending on health will increase from US$9.21 trillion in 2014 to $24.24 trillion (uncertainty interval [UI] 20.47-29.72) in 2040. We expect per capita health spending to increase fastest in upper-middle-income countries, at 5.3% (UI 4.1-6.8) per year. This growth is driven by continued growth in GDP, government spending, and government health spending. Lower-middle income countries are expected to grow at 4.2% (3.8-4.9). High-income countries are expected to grow at 2.1% (UI 1.8-2.4) and low-income countries are expected to grow at 1.8% (1.0-2.8). Despite this growth, health spending per capita in low-income countries is expected to remain low, at $154 (UI 133-181) per capita in 2030 and $195 (157-258) per capita in 2040. Increases in national health spending to reach the level of the countries who spend the most on health, relative to their level of economic development, would mean $321 (157-258) per capita was available for health in 2040 in low-income countries. Interpretation: Health spending is associated with economic development but past trends and relationships suggest that spending will remain variable, and low in some low-resource settings. Policy change could lead to increased health spending, although for the poorest countries external support might remain essential.

Introduction. In regional state of the study area, HIV (Human Immunodeficiency Virus) prevalence is 2.2% and opportunistic infections (OIs) occurred in 88.9% of pre-ART (Antiretroviral Therapy) people living with HIV/AIDS (PLWHA). Even though OIs are prevalent in the study area, duration of staying free from acquiring rehappening opportunistic infections and its determinant factors are not studied. Method. The study was conducted in randomly selected 341 adult Pre-ART PLWHA who are included in chronic HIV care. OI free duration was estimated using the actuarial life table and Kaplan Meier survival. Cox proportional-hazard model was used to calculate hazard rate. Result. OIs were rediagnosed in three quarters (75.37%) participants. In each week the probability of getting new recurrence OI was about 15.04 per 1000 person weeks. The median duration of not acquiring OI recurrence was 54 weeks. After adjustment, variables associated with recurrence were employment status, marital status, exposure for prophylaxis and adherence to it, CD4 count, and hemoglobin value. Conclusion. Giving prophylaxis and counseling to adhere it, rise in CD4 and hemoglobin level, and enhancing job opportunities should be given for PLWHA who are on chronic HIV care while continuing the care.