Effect of Calcium Soap of Fatty Acids Supplementation on Serum Biochemical Parameters and Ovarian Activity during Out-of-the-Breeding Season in Crossbred Ewes

This experiment aimed to evaluate the effect of calcium soap of fatty acid (CSFA) supplementation on serum biochemical and hormones and ovarian activity during out-of-the-breeding season in ewes. Twelve crossbred ewes, 2-3 years of age and weighting 45–55 kg, were allocated into two equal groups. The first group was control and the other was treated with 50 g/head of CSFA. All ewes were fed basal diet and treated with 60 mg of medroxy progesterone acetate intravaginal sponge for 12 day. At the third day of sponge removal, the CSFA-treated group was given 50 g/head of CSFA daily for two estrous cycles. During the estrus phase, ovarian activity was detected using ultrasonography in both groups. All ewes were then subjected to natural breeding and conception rate. Blood samples were collected from all ewes during treatment period. Results revealed significant (P < 0.05) increases in serum cholesterol, triglycerides, low-density lipoprotein cholesterol, glucose, and progesterone levels with decrease in calcium and phosphorous levels in treated group. In treated group, normal-size ovaries and more than one follicle on the ovaries were detected and pregnancy rate increased. In conclusion, CSFA supplementation was effective to maintain the reproductive performance when ewes were out of the breeding season

Retail Chicken Carcasses as a Reservoir of Multidrug-Resistant .

is a major cause of foodborne disease outbreaks worldwide, mainly through poultry. Recently, there has been an increase in multidrug-resistant (MDR) infections globally. The increased drug resistance results in increased costs and poorer health outcomes due to unavailability or delayed treatment. This study aims to determine the prevalence of in retail raw chicken meat and identify their antimicrobial resistance profiles. A total of 270 retail raw chicken carcasses (local and imported) were collected from three hypermarket chains in Qatar between November 2017 and April 2018. Thirty carcasses were contaminated with (11.11%). The prevalence of in locally produced chicken was higher than in imported chicken (OR = 2.56, 95% CI: 1.18-5.53,  = 0.016). No significant differences were found between the prevalence and storage temperature or hypermarket chain. The highest resistance rates in the isolates were reported to tetracycline (73.7%) followed by nitrofurantoin (53.3%), ampicillin (50%), amoxicillin-clavulanic acid, ceftriaxone (26.7%), and ciprofloxacin (23.3%). Eight isolates were potential extended-spectrum β-lactamase-producers, all in imported frozen chicken ( < 0.0001). Additionally, 43.3% of the isolates were MDR and associated with frozen chicken (OR = 16.88, 95% CI: 2.55-111.47,  = 0.002). The findings indicate that while the prevalence of in retail chicken in Qatar is moderate, a large proportion of them are MDR.This research was funded by, Biomedical Research Centre, Qatar University, grant number “BRC-2018-ID-01 to Nahla O. Eltai.

Surveillance on A/H5N1 virus in domestic poultry and wild birds in Egypt

The endemic H5N1 high pathogenicity avian influenza virus (A/H5N1) in poultry in Egypt continues to cause heavy losses in poultry and poses a significant threat to human health. Here we describe results of A/H5N1 surveillance in domestic poultry in 2009 and wild birds in 2009-2010. Tracheal and cloacal swabs were collected from domestic poultry from 22024 commercial farms, 1435 backyards and 944 live bird markets (LBMs) as well as from 1297 wild birds representing 28 different types of migratory birds. Viral RNA was extracted from a mix of tracheal and cloacal swabs media. Matrix gene of avian influenza type A virus was detected using specific real-time reverse-transcription polymerase chain reaction (RT-qPCR) and positive samples were tested by RT- qPCR for simultaneous detection of the H5 and N1 genes. In this surveillance, A/H5N1 was detected from 0.1% (n = 23/) of examined commercial poultry farms, 10.5% (n = 151) of backyard birds and 11.4% (n = 108) of LBMs but no wild bird tested positive for A/H5N1. The virus was detected from domestic poultry year- round with higher incidence in the warmer months of summer and spring particularly in backyard birds. Outbreaks were recorded mostly in Lower Egypt where 95.7% (n = 22), 68.9% (n = 104) and 52.8% (n = 57) of positive commercial farms, backyards and LBMs were detected, respectively. Higher prevalence (56%, n = 85) was reported in backyards that had mixed chickens and waterfowl together in the same vicinity and LBMs that had waterfowl (76%, n = 82). Our findings indicated broad circulation of the endemic A/H5N1 among poultry in 2009 in Egypt. In addition, the epidemiology of A/H5N1 has changed over time with outbreaks occurring in the warmer months of the year. Backyard waterfowl may play a role as a reservoir and/or source of A/H5N1 particularly in LBMs. The virus has been established in poultry in the Nile Delta where major metropolitan areas, dense human population and poultry stocks are concentrated. Continuous surveillance, tracing the source of live birds in the markets and integration of multifaceted strategies and global collaboration are needed to control the spread of the virus in Egypt

Protective efficacy of recombinant turkey herpes virus (rHVT-H5) and inactivated H5N1 vaccines in commercial Mulard ducks against the highly pathogenic avian influenza (HPAI) H5N1 clade 2.2.1 virus

In Egypt, ducks kept for commercial purposes constitute the second highest poultry population, at 150 million ducks/year. Hence, ducks play an important role in the introduction and transmission of avian influenza (AI) in the Egyptian poultry population. Attempts to control outbreaks include the use of vaccines, which have varying levels of efficacy and failure. To date, the effects of vaccine efficacy has rarely been determined in ducks. In this study, we evaluated the protective efficacy of a live recombinant vector vaccine based on a turkey Herpes Virus (HVT) expressing the H5 gene from a clade 2.2 H5N1 HPAIV strain (A/Swan/ Hungary/499/2006) (rHVT-H5) and a bivalent inactivated H5N1 vaccine prepared from clade 2.2.1 and 2.2.1.1 H5N1 seeds in Mulard ducks. A 0.3ml/dose subcutaneous injection of rHVT-H5 vaccine was administered to one-day-old ducklings (D1) and another 0.5ml/ dose subcutaneous injection of the inactivated MEFLUVAC was administered at 7 days (D7). Four separate challenge experiments were conducted at Days 21, 28, 35 and 42, in which all the vaccinated ducks were challenged with 106EID50/duck of H5N1 HPAI virus (A/ chicken/Egypt/128s/2012(H5N1) (clade 2.2.1) via intranasal inoculation. Maternal-derived antibody regression and post-vaccination antibody immune responses were monitored weekly. Ducks vaccinated at 21, 28, 35 and 42 days with the rHVT-H5 and MEFLUVAC vaccines were protected against mortality (80%, 80%, 90% and 90%) and (50%, 70%, 80% and 90%) respectively, against challenges with the H5N1 HPAI virus. The amount of viral shedding and shedding rates were lower in the rHVT-H5 vaccine groups than in the MEFLUVAC groups only in the first two challenge experiments. However, the non-vaccinated groups shed significantly more of the virus than the vaccinated groups. Both rHVT-H5 and MEFLUVAC provide early protection, and rHVT-H5 vaccine in particular provides protection against HPAI challenge.S1 Table. Weekly mean HI titres (log2 ± SD) using A/Swan/Hungary/4999/2006) rHVT/Ag that indicate the immune response to the rHVT-H5 vaccination. S1 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group I (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).S2 Table. Weekly mean HI titres (log2 ± SD) measured using (A/chicken/Egypt/Q1995D/ 2010) V/H5N1/Ag that indicates the immune response to the KV-H5 vaccination. S2 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group 1 (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).S3 Table. Weekly mean HI titres (log2 ± SD) measured using (A/chicken/Egypt/128S/2012) C/H5N1/Ag that indicates the immune response to the challenge virus. S3 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group 1 (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).This work was supported by the United States Agency for International Development (USAID) under a grant (AID-263-IO-11-00001, Mod. #3) and within the framework of OSRO/EGY/101/ USA, which applies to projects jointly implemented by the FAO, GOVS and NLQP.http://www.plosone.orgam2016Production Animal StudiesVeterinary Tropical Disease

Protective efficacy of recombinant turkey herpes virus (rHVT-H5) and inactivated H5N1 vaccines in commercial Mulard ducks against the highly pathogenic avian influenza (HPAI) H5N1 clade 2.2.1 virus

In Egypt, ducks kept for commercial purposes constitute the second highest poultry population, at 150 million ducks/year. Hence, ducks play an important role in the introduction and transmission of avian influenza (AI) in the Egyptian poultry population. Attempts to control outbreaks include the use of vaccines, which have varying levels of efficacy and failure. To date, the effects of vaccine efficacy has rarely been determined in ducks. In this study, we evaluated the protective efficacy of a live recombinant vector vaccine based on a turkey Herpes Virus (HVT) expressing the H5 gene from a clade 2.2 H5N1 HPAIV strain (A/Swan/ Hungary/499/2006) (rHVT-H5) and a bivalent inactivated H5N1 vaccine prepared from clade 2.2.1 and 2.2.1.1 H5N1 seeds in Mulard ducks. A 0.3ml/dose subcutaneous injection of rHVT-H5 vaccine was administered to one-day-old ducklings (D1) and another 0.5ml/ dose subcutaneous injection of the inactivated MEFLUVAC was administered at 7 days (D7). Four separate challenge experiments were conducted at Days 21, 28, 35 and 42, in which all the vaccinated ducks were challenged with 106EID50/duck of H5N1 HPAI virus (A/ chicken/Egypt/128s/2012(H5N1) (clade 2.2.1) via intranasal inoculation. Maternal-derived antibody regression and post-vaccination antibody immune responses were monitored weekly. Ducks vaccinated at 21, 28, 35 and 42 days with the rHVT-H5 and MEFLUVAC vaccines were protected against mortality (80%, 80%, 90% and 90%) and (50%, 70%, 80% and 90%) respectively, against challenges with the H5N1 HPAI virus. The amount of viral shedding and shedding rates were lower in the rHVT-H5 vaccine groups than in the MEFLUVAC groups only in the first two challenge experiments. However, the non-vaccinated groups shed significantly more of the virus than the vaccinated groups. Both rHVT-H5 and MEFLUVAC provide early protection, and rHVT-H5 vaccine in particular provides protection against HPAI challenge.S1 Table. Weekly mean HI titres (log2 ± SD) using A/Swan/Hungary/4999/2006) rHVT/Ag that indicate the immune response to the rHVT-H5 vaccination. S1 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group I (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).S2 Table. Weekly mean HI titres (log2 ± SD) measured using (A/chicken/Egypt/Q1995D/ 2010) V/H5N1/Ag that indicates the immune response to the KV-H5 vaccination. S2 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group 1 (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).S3 Table. Weekly mean HI titres (log2 ± SD) measured using (A/chicken/Egypt/128S/2012) C/H5N1/Ag that indicates the immune response to the challenge virus. S3 Table legend: Different upper case letters in a row denote the presence of statistically significant (p 0.05) differences. Group 1 (vaccinated with rHVT-H5 vaccine at 1 day old), Group II (vaccinated with inactivated KV-H5 vaccine at 8 days old), Group III (unvaccinated control).This work was supported by the United States Agency for International Development (USAID) under a grant (AID-263-IO-11-00001, Mod. #3) and within the framework of OSRO/EGY/101/ USA, which applies to projects jointly implemented by the FAO, GOVS and NLQP.http://www.plosone.orgam2016Production Animal StudiesVeterinary Tropical Disease

Future and potential spending on health 2015-40: Development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries

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

Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

BACKGROUND: The Millennium Declaration in 2000 brought special global attention to HIV, tuberculosis, and malaria through the formulation of Millennium Development Goal (MDG) 6. The Global Burden of Disease 2013 study provides a consistent and comprehensive approach to disease estimation for between 1990 and 2013, and an opportunity to assess whether accelerated progress has occured since the Millennium Declaration. METHODS: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets. FINDINGS: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 million deaths (1·6 million to 1·9 million). Concentrated epidemics in Latin America and eastern Europe are substantially smaller than previously estimated. Through interventions including PMTCT and ART, 19·1 million life-years (16·6 million to 21·5 million) have been saved, 70·3% (65·4 to 76·1) in developing countries. From 2000 to 2011, the ratio of development assistance for health for HIV to years of life saved through intervention was US$4498 in developing countries. Including in HIV-positive individuals, all-form tuberculosis incidence was 7·5 million (7·4 million to 7·7 million), prevalence was 11·9 million (11·6 million to 12·2 million), and number of deaths was 1·4 million (1·3 million to 1·5 million) in 2013. In the same year and in only individuals who were HIV-negative, all-form tuberculosis incidence was 7·1 million (6·9 million to 7·3 million), prevalence was 11·2 million (10·8 million to 11·6 million), and number of deaths was 1·3 million (1·2 million to 1·4 million). Annualised rates of change (ARC) for incidence, prevalence, and death became negative after 2000. Tuberculosis in HIV-negative individuals disproportionately occurs in men and boys (versus women and girls); 64·0% of cases (63·6 to 64·3) and 64·7% of deaths (60·8 to 70·3). Globally, malaria cases and deaths grew rapidly from 1990 reaching a peak of 232 million cases (143 million to 387 million) in 2003 and 1·2 million deaths (1·1 million to 1·4 million) in 2004. Since 2004, child deaths from malaria in sub-Saharan Africa have decreased by 31·5% (15·7 to 44·1). Outside of Africa, malaria mortality has been steadily decreasing since 1990. INTERPRETATION: Our estimates of the number of people living with HIV are 18·7% smaller than UNAIDS's estimates in 2012. The number of people living with malaria is larger than estimated by WHO. The number of people living with HIV, tuberculosis, or malaria have all decreased since 2000. At the global level, upward trends for malaria and HIV deaths have been reversed and declines in tuberculosis deaths have accelerated. 101 countries (74 of which are developing) still have increasing HIV incidence. Substantial progress since the Millennium Declaration is an encouraging sign of the effect of global action. FUNDING: Bill & Melinda Gates Foundation

Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings: In the reference scenario, global health spending was projected to increase from US$10 trillion (95$20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only $40 (24–65) to$413 (263–668) in 2040 in low-income countries, and from $140 (90–200) to$1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. Funding: The Bill & Melinda Gates Foundation

Trends in HIV/AIDS morbidity and mortality in Eastern 3 Mediterranean countries, 1990–2015: findings from the Global 4 Burden of Disease 2015 study

Objectives We used the results of the Global Burden of Disease 2015 study to estimate trends of HIV/AIDS burden in Eastern Mediterranean Region (EMR) countries between 1990 and 2015. Methods Tailored estimation methods were used to produce final estimates of mortality. Years of life lost (YLLs) were calculated by multiplying the mortality rate by population by age-specific life expectancy. Years lived with disability (YLDs) were computed as the prevalence of a sequela multiplied by its disability weight. Results In 2015, the rate of HIV/AIDS deaths in the EMR was 1.8 (1.4–2.5) per 100,000 population, a 43% increase from 1990 (0.3; 0.2–0.8). Consequently, the rate of YLLs due to HIV/AIDS increased from 15.3 (7.6–36.2) per 100,000 in 1990 to 81.9 (65.3–114.4) in 2015. The rate of YLDs increased from 1.3 (0.6–3.1) in 1990 to 4.4 (2.7–6.6) in 2015. Conclusions HIV/AIDS morbidity and mortality increased in the EMR since 1990. To reverse this trend and achieve epidemic control, EMR countries should strengthen HIV surveillance,and scale up HIV antiretroviral therapy and comprehensive prevention services

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030