32 research outputs found

    Methicillin-resistant Staphylococcus aureus with genotyping method among human immunodeficiency virus positive pediatric patients in Northwest Ethiopia: A cross-sectional study design

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    Abstract Background: Increasing evidence suggests that methicillin-resistant Staphylococcus aureus (MRSA) infections are becoming more prevalent throughout the human immunodeficiency virus (HIV) infected community. However, there is scarcity of data about the prevalence of MRSA among HIV positive pediatric patients in the study area. Objectives: To determine the prevalence and types of MRSA among S. aureus isolates of HIV positive pediatric patients in the Amhara National Regional State, Northwest Ethiopia. Methods: Pediatric patients who attended the clinic from December 2013 to April 2014 were included in the study. Genotype MRSA VER 3.0 was used for characterization of S. aureus isolates. This detected methicillin-resistance-mediating mecA and mecC genes and the bicomponent cytotoxic virulence factor Panton–Valentine leukocidin (PVL). Data were analyzed using SPSS version 20. Results: Among 126 S. aureus isolates, 37.3% and 11.9% were mecA and Panton–Valentine leukocidin gene positive, respectively. Patients of FHRH (P = 0.04) and DRH (P = 0.02) have statistical significance for mecA gene. Panton–Valentine leukocidin gene positive strains were about 97% less likelihood to be mecA gene positive (P = 0.001). Conclusion: A high prevalence of pathogenic MRSA strains among HIV positive pediatric patients was observed. Most of the MRSA types were hospital acquired. Hence, strict hygienic approaches by healthcare workers in hospitals should be implemented. In addition, screening and treatment of MRSA for HIV positive pediatric patients is recommended. [Ethiop. J. Health Dev. 2018;32(3):00-000] Key words: MRSA, pediatrics, HIV, Ethiopi

    Evolution of long-term vaccine-induced and hybrid immunity in healthcare workers after different COVID-19 vaccine regimens

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    BACKGROUND: Both infection and vaccination, alone or in combination, generate antibody and T cell responses against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the maintenance of such responses-and hence protection from disease-requires careful characterization. In a large prospective study of UK healthcare workers (HCWs) (Protective Immunity from T Cells in Healthcare Workers [PITCH], within the larger SARS-CoV-2 Immunity and Reinfection Evaluation [SIREN] study), we previously observed that prior infection strongly affected subsequent cellular and humoral immunity induced after long and short dosing intervals of BNT162b2 (Pfizer/BioNTech) vaccination. METHODS: Here, we report longer follow-up of 684 HCWs in this cohort over 6-9 months following two doses of BNT162b2 or AZD1222 (Oxford/AstraZeneca) vaccination and up to 6 months following a subsequent mRNA booster vaccination. FINDINGS: We make three observations: first, the dynamics of humoral and cellular responses differ; binding and neutralizing antibodies declined, whereas T and memory B cell responses were maintained after the second vaccine dose. Second, vaccine boosting restored immunoglobulin (Ig) G levels; broadened neutralizing activity against variants of concern, including Omicron BA.1, BA.2, and BA.5; and boosted T cell responses above the 6-month level after dose 2. Third, prior infection maintained its impact driving larger and broader T cell responses compared with never-infected people, a feature maintained until 6 months after the third dose. CONCLUSIONS: Broadly cross-reactive T cell responses are well maintained over time-especially in those with combined vaccine and infection-induced immunity ("hybrid" immunity)-and may contribute to continued protection against severe disease

    Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

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    Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

    Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

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    Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2\ub75th percentile and 100 as the 97\ub75th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59\ub74 (IQR 35\ub74–67\ub73), ranging from a low of 11\ub76 (95% uncertainty interval 9\ub76–14\ub70) to a high of 84\ub79 (83\ub71–86\ub77). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030

    Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017.

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    BACKGROUND: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of 'leaving no one behind', it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. METHODS: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator

    Methicillin Resistant Staphylococcus aureus among HIV Infected Pediatric Patients in Northwest Ethiopia: Carriage Rates and Antibiotic Co-Resistance Profiles.

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    MRSA infections are becoming more prevalent throughout the HIV community. MRSA infections are a challenge to both physicians and patients due to limited choice of therapeutic options and increased cost of care.This study was aimed to determine the prevalence of colonization and co-resistance patterns of MRSA species among HIV positive pediatric patients in the Amhara National Regional State, Northwest Ethiopia.Culture swabs were collected from the anterior nares, the skin and the perineum of 400 participants. In vitro antimicrobial susceptibility testing was done on Muller Hinton Agar by the Kirby-Bauer disk diffusion method, using 30 ÎŒg cefoxitin (OXOID, ENGLAND) according to the recommendations of the Clinical and Laboratory Standards Institute. Methicillin sensitivity/resistance was tested using cefoxitin. Data was analyzed by descriptive statistics and logistic regression model using Epi Info 7.S. aureus was detected in 206 participants (51.5%). The prevalence of MRSA colonization in this study was 16.8%. Colonization by S. aureus was associated with male gender (OR = 0.5869; 95% CI: 0.3812-0.9036; p-value = 0.0155), history of antibiotic use over the previous 3 months (OR = 2.3126; 95% CI: 1.0707-4.9948; p-value = 0.0329) and having CD4 T-cell counts of more than 350 x 10(6) cells / L (OR = 0.5739; 95% CI = 0.3343-0.9851; p-value = 0.0440). Colonization by MRSA was not associated with any one of the variables. Concomitant resistance of the MRSA to clindamycin, chloramphenicol, co-trimoxazole, ceftriaxone, erythromycin and tetracycline was 7.6%, 6%, 5.25%, 20.9%, 23.9% and 72.1%, respectively.High rates of colonization by pathogenic MRSA strains is observed among HIV positive pediatric patients in the Amhara National Regional state

    Correlation between Variables and Colonization by MRSA among 400 HIV-Infected Pediatric Patients, Amhara National Regional State, 2014.

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    <p>*CD<sub>4</sub>T-cell count of 350 x 10<sup>6</sup> cells / L or more per ml versus CD<sub>4</sub>T-cell counts under 350 x 10<sup>6</sup> cells / L</p><p>Correlation between Variables and Colonization by MRSA among 400 HIV-Infected Pediatric Patients, Amhara National Regional State, 2014.</p

    Numbers of <i>S</i>. <i>aureus</i> clinical isolates by type of specimen among 400 HIV-infected children, Amhara National Regional State, 2014.

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    <p>Numbers of <i>S</i>. <i>aureus</i> clinical isolates by type of specimen among 400 HIV-infected children, Amhara National Regional State, 2014.</p

    Baseline demographic data in HIV-infected children who gave skin, nasal and perineal samples, Amhara National Regional State, 2014.

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    <p>Baseline demographic data in HIV-infected children who gave skin, nasal and perineal samples, Amhara National Regional State, 2014.</p
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