8 research outputs found
High enteric bacterial contamination of drinking water in Jigjiga city, Eastern Ethiopia
No full textBackground: The high prevalence of diarrheal disease among children and infants can be traced due to the use of unsafe water and unhygienic practices. The overall concept adopted for microbiological quality is that no water intended for human consumption shall contain Escherichia coli per 100 ml sample.Objective: The aim of this study was to assess household water handling and hygienic practices and to determine bacteriological quality of drinking water from different sources in Jigjiga city.Methods: A cross-sectional study was conducted to assess bacteriological quality of drinking water in Jigjiga city from May-August, 2013. Both simple random and convenient sampling techniques were applied to select 238 households to assess water handling and hygienic practices, and 125 water samples to assess bacteriological quality of drinking water respectively. The water samples were collected from household water container, pipeline, water reservoir, ‘Beyollie’, and main sources.Easily isolated bacteria called coliforms were used as indicator organisms of human and other animals’ fecal contamination status of drinking water. Data were summarized using descriptive and analytical statistics. Chi-square (χ2) and logistic regression tests were used and p<0.05 was considered as cut off value for statistical significance.Results: Overall, 71.2%(n=89) of water samples were contaminated by one or more bacterial species of E.coli, Shigella Sp, Salmonella Sp, and Vibrio sp. Particularly, 65(52%), 10(8%), 9(7.2%), and 8(6.4%) were contaminated by E.coli, Shigella sp, Salmonella sp, and Vibrio sp, respectively. On the other hand, 20% of the households and pipeline water samples had a fecal coliform count of 150 and above. Placement of water drinking utensils had a statistically significant association with illiterate education (p=0.01, AOR=5.47, 95% CI: (1.31, 22.78)) and male household head (p=0.02, AOR=2.11, 95% CI: (1.10, 4.05)).Conclusions: The majorities of drinking water sources were highly contaminated by Enterobacteriaceae. Regular bacteriological water quality control mechanisms need to be in place to ensure bacteriological safety of drinking water. [Ethiop. J. Health Dev. 2016;30(3):118-128]Keywords: Contamination, drinking water, households, enteric bacteria, Jigjig
High enteric bacterial contamination of drinking water in Jigjiga city, Eastern Ethiopia
No full textCorrection to: Understanding the key processes of excellence as a prerequisite to establishing academic centres of excellence in Africa
No full textCorrection to: BMC Med Educ 21, 36 (2021) https://doi.org/10.1186/s12909-020-02471-0 Following publication of the original article [1], the authors identified an error in the author name of Conor R. Caffrey and also in his affiliation. The incorrect author name is: Connor Caffery The correct author name is: Conor R. Caffrey The incorrect author affiliation is: Skaggs School of Pharmacy & Pharmaceutical Sciences, University of California San Diego, San Diego, California, USA. The correct author affiliation is: Center for Discovery and Innovation in Parasitic Diseases, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California, USA The original article has been corrected
β-Defensin genomic copy number is associated with HIV viral load and immune reconstitution in sub-Saharan Africans
No full textAIDS, caused by the retrovirus HIV, is the leading cause of death of economically-active people (age 15 59) in sub-Saharan Africa. It is characterised by high HIV viral load and reduced (<200 cells/mm3) CD4 + T-cell count.
b-defensins are broad-spectrum antimicrobial genes that are also chemotactic for dendritic cells and T-cells through the CCR6. b-defensin genes have previously been shown to be copy number variable, that is, different individuals have different numbers of the same gene. In this cohort study we analysed the relationship between b-defensin genomic copy number and HIV viral load immediately prior to initiation of retroviral treatment in 627 Ethiopian and 325 Tanzanian HIV patients, some co-infected with tuberculosis. We also measured the response to Highly Active Antiretroviral Therapy (HAART) by measuring follow-up CD4+ T-cell counts and viral load counts in a subsection of these patients. We found that high b-defensin copy number was associated with increased baseline HIV viral load, independent of co-infection with tuberculosis and population of origin. We also found that high b-defensin copy number was associated with impaired immune reconstitution after initiation of HAART, as measured by CD4 count up to 48 weeks follow-up and virological failure (persistence of viremia with viral load >200 copies/ml). Given the known chemotactic role of b-de-fensins, our data suggest a model where b-defensins recruit HIV- permissive Th17 lymphocytes to mucosal sites via the chemokine receptor CCR6.
E. Hollox and E. Aklillu are joint senior author
Global, regional, and national burden of brain and other CNS cancer, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016
No full textBackground Brain and CNS cancers (collectively referred to as CNS cancers) are a source of mortality and morbidity for which diagnosis and treatment require extensive resource allocation and sophisticated diagnostic and therapeutic technology. Previous epidemiological studies are limited to specific geographical regions or time periods, making them difficult to compare on a global scale. In this analysis, we aimed to provide a comparable and comprehensive estimation of the global burden of brain cancer between 1990 and 2016. Methods We report means and 95% uncertainty intervals (UIs) for incidence, mortality, and disability-adjusted life-years (DALYs) estimates for CNS cancers (according to the International Classification of Diseases tenth revision: malignant neoplasm of meninges, malignant neoplasm of brain, and malignant neoplasm of spinal cord, cranial nerves, and other parts of CNS) from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. Data sources include vital registration and cancer registry data. Mortality was modelled using an ensemble model approach. Incidence was estimated by dividing the final mortality estimates by mortality to incidence ratios. DALYs were estimated by summing years of life lost and years lived with disability. Locations were grouped into quintiles based on the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. Findings In 2016, there were 330 000 (95% UI 299 000 to 349 000) incident cases of CNS cancer and 227 000 (205 000 to 241 000) deaths globally, and age-standardised incidence rates of CNS cancer increased globally by 17 3% (95% UI 11.4 to 26.9) between 1990 and 2016 (2016 age-standardised incidence rate 4.63 per 100 000 person-years [4.17 to 4.90]). The highest age-standardised incidence rate was in the highest quintile of SDI (6.91 [5.71 to 7.53]). Age-standardised incidence rates increased with each SDI quintile. East Asia was the region with the most incident cases of CNS cancer for both sexes in 2016 (108 000 [95% UI 98 000 to 122 000]), followed by western Europe (49 000 [3 7 000 to 54 000]), and south Asia (31000 [29000 to 37 000]). The top three countries with the highest number of incident cases were China, the USA, and India. CNS cancer was responsible for 7.7 million (95% UI 6.9 to 8.3) DALYs globally, a non-significant change in age-standardised DALY rate of -10 .0% (-16.4 to 2.6) between 1990 and 2016. The age-standardised DALY rate decreased in the high SDI quintile (-10.0% [-27.1 to -0.1]) and high-middle SDI quintile (-10.5% [-18.4 to -1.4]) over time but increased in the low SDI quintile (22.5% [11.2 to 50.5]). Interpretation CNS cancer is responsible for substantial morbidity and mortality worldwide, and incidence increased between 1990 and 2016. Significant geographical and regional variation in the incidence of CNS cancer might be reflective of differences in diagnoses and reporting practices or unknown environmental and genetic risk factors. Future efforts are needed to analyse CNS cancer burden by subtype. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd.Y
Global, regional, and national burden of brain and other CNS cancer, 1990-2016 : a systematic analysis for the Global Burden of Disease Study 2016
No full textAbstract: Background Brain and CNS cancers (collectively referred to as CNS cancers) are a source of mortality and morbidity for which diagnosis and treatment require extensive resource allocation and sophisticated diagnostic and therapeutic technology. Previous epidemiological studies are limited to specific geographical regions or time periods, making them difficult to compare on a global scale. In this analysis, we aimed to provide a comparable and comprehensive estimation of the global burden of brain cancer between 1990 and 2016. Methods We report means and 95% uncertainty intervals (UIs) for incidence, mortality, and disability-adjusted life-years (DALYs) estimates for CNS cancers (according to the International Classification of Diseases tenth revision: malignant neoplasm of meninges, malignant neoplasm of brain, and malignant neoplasm of spinal cord, cranial nerves, and other parts of CNS) from the Global Burden of Diseases, Injuries, and Risk Factors Study 2016. Data sources include vital registration and cancer registry data. Mortality was modelled using an ensemble model approach. Incidence was estimated by dividing the final mortality estimates by mortality to incidence ratios. DALYs were estimated by summing years of life lost and years lived with disability. Locations were grouped into quintiles based on the Socio-demographic Index (SDI), a summary indicator of income per capita, years of schooling, and total fertility rate. Findings In 2016, there were 330 000 (95% UI 299 000 to 349 000) incident cases of CNS cancer and 227 000 (205 000 to 241 000) deaths globally, and age-standardised incidence rates of CNS cancer increased globally by 17 3% (95% UI 11.4 to 26.9) between 1990 and 2016 (2016 age-standardised incidence rate 4.63 per 100 000 person-years [4.17 to 4.90]). The highest age-standardised incidence rate was in the highest quintile of SDI (6.91 [5.71 to 7.53]). Age-standardised incidence rates increased with each SDI quintile. East Asia was the region with the most incident cases of CNS cancer for both sexes in 2016 (108 000 [95% UI 98 000 to 122 000]), followed by western Europe (49 000 [3 7 000 to 54 000]), and south Asia (31000 [29000 to 37 000]). The top three countries with the highest number of incident cases were China, the USA, and India. CNS cancer was responsible for 7.7 million (95% UI 6.9 to 8.3) DALYs globally, a non-significant change in age-standardised DALY rate of -10 .0% (-16.4 to 2.6) between 1990 and 2016. The age-standardised DALY rate decreased in the high SDI quintile (-10.0% [-27.1 to -0.1]) and high-middle SDI quintile (-10.5% [-18.4 to -1.4]) over time but increased in the low SDI quintile (22.5% [11.2 to 50.5]). Interpretation CNS cancer is responsible for substantial morbidity and mortality worldwide, and incidence increased between 1990 and 2016. Significant geographical and regional variation in the incidence of CNS cancer might be reflective of differences in diagnoses and reporting practices or unknown environmental and genetic risk factors. Future efforts are needed to analyse CNS cancer burden by subtype. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd
Global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017
No full textBackground Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980-2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package-a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1.95 million deaths (95 uncertainty interval 1.87-2.04) and has since decreased to 0.95 million deaths (0.91-1.01) in 2017. New cases of HIV globally peaked in 1999 (3.16 million, 2.79-3.67) and since then have gradually decreased to 1.94 million (1.63-2.29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36.8 million (34.8-39.2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65.7 in Lesotho to 85.7 in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81 ART coverage by 2020 and 12 countries are on track to meet 90 ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd
Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017
No full text© 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license 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. Interpretation: Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Funding: Bill & Melinda Gates Foundation
