122 research outputs found
Avian influenza surveillance in domestic waterfowl and environment of live bird markets in Bangladesh, 2007â2012
Avian influenza viruses, including highly pathogenic strains, pose severe economic, animal and public health concerns. We implemented live bird market surveillance in Bangladesh to identify the subtypes of avian influenza A viruses in domestic waterfowl and market environments. We collected waterfowl samples monthly from 4 rural sites from 2007 to 2012 and environmental samples from 4 rural and 16 urban sites from 2009 to 2012. Samples were tested through real-time RT-PCR, virus culture, and sequencing to detect and characterize avian influenza A viruses. Among 4,308 waterfowl tested, 191 (4.4%) were positive for avian influenza A virus, including 74 (1.9%) avian influenza A/H5 subtype. The majority (99%, nâ=â73) of the influenza A/H5-positive samples were from healthy appearing waterfowl. Multiple subtypes, including H1N1, H1N3, H3N2, H3N6, H3N8, H4N1, H4N2, H4N6, H5N1 (clades 2.2.2, 2.3.2.1a, 2.3.4.2), H5N2, H6N1, H7N9, H9N2, H11N2 and H11N3, H11N6 were detected in waterfowl and environmental samples. Environmental samples tested positive for influenza A viruses throughout the year. Avian influenza viruses, including H5N1 and H9N2 subtypes were also identified in backyard and small-scale raised poultry. Live bird markets could be high-risk sites for harboring the viruses and have the potential to infect naive birds and humans exposed to them
Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at âs = 7 TeV with the ATLAS detector
This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of âs = 7 TeV;{\rm Te}{\rm V}4.6\;{\rm f}{{{\rm b}}^{-1}}{{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}|\eta |\lt 1.9{{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques
Past, present, and future of global health financing : a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050
Background Comprehensive and comparable estimates of health spending in each country are a key input for health policy and planning, and are necessary to support the achievement of national and international health goals. Previous studies have tracked past and projected future health spending until 2040 and shown that, with economic development, countries tend to spend more on health per capita, with a decreasing share of spending from development assistance and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending, with an emphasis on equity in spending across countries. Methods We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three categories-government, out-of-pocket, and prepaid private health spending-and estimated development assistance for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050 and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private, and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition methods to assess a set of factors associated with changes in government health spending between 1995 and 2016 and to examine evidence to support the theory of the health financing transition. We projected two alternative future scenarios based on higher government health spending to assess the potential ability of governments to generate more resources for health. Findings Between 1995 and 2016, health spending grew at a rate of 4.00% (95% uncertainty interval 3.89-4.12) annually, although it grew slower in per capita terms (2.72% [2.61-2.84]) and increased by less than 8.0 trillion (7.8-8.1) in 2016 (comprising 8.6% [8.4-8.7] of the global economy and 5252 (5184-5319) in high-income countries, 81 (74-89) in lower-middle-income countries, and 9.5 billion, 24.3% of total DAH), although spending on other infectious diseases (excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6.27% per year). The leading sources of DAH were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation). For the first time, we included estimates of China's contribution to DAH ( 15.0 trillion (14.0-16.0) by 2050 (reaching 9.4% [7.6-11.3] of the global economy and $ 21.3 trillion [19.8-23.1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of 1.84% (1.68-2.02) annually, and with continuing disparities in spending between countries. In 2050, we estimate that 0.6% (0.6-0.7) of health spending will occur in currently low-income countries, despite these countries comprising an estimated 15.7% of the global population by 2050. The ratio between per capita health spending in high-income and low-income countries was 130.2 (122.9-136.9) in 2016 and is projected to remain at similar levels in 2050 (125.9 [113.7-138.1]). The decomposition analysis identified governments' increased prioritisation of the health sector and economic development as the strongest factors associated with increases in government health spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the health sector and increased government spending, health spending per capita could more than double, with greater impacts in countries that currently have the lowest levels of government health spending. Interpretation Financing for global health has increased steadily over the past two decades and is projected to continue increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income countries. Many low-income countries are expected to remain dependent on development assistance, although with greater government spending, larger investments in health are feasible. In the absence of sustained new investments in health, increasing efficiency in health spending is essential to meet global health targets.Peer reviewe
Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995â2050
Background: Comprehensive and comparable estimates of health spending in each country are a key input for health
policy and planning, and are necessary to support the achievement of national and international health goals. Previous
studies have tracked past and projected future health spending until 2040 and shown that, with economic development,
countries tend to spend more on health per capita, with a decreasing share of spending from development assistance
and out-of-pocket sources. We aimed to characterise the past, present, and predicted future of global health spending,
with an emphasis on equity in spending across countries.
Methods: We estimated domestic health spending for 195 countries and territories from 1995 to 2016, split into three
categoriesâgovernment, out-of-pocket, and prepaid private health spendingâand estimated development assistance
for health (DAH) from 1990 to 2018. We estimated future scenarios of health spending using an ensemble of linear
mixed-effects models with time series specifications to project domestic health spending from 2017 through 2050
and DAH from 2019 through 2050. Data were extracted from a broad set of sources tracking health spending and
revenue, and were standardised and converted to inflation-adjusted 2018 US dollars. Incomplete or low-quality data
were modelled and uncertainty was estimated, leading to a complete data series of total, government, prepaid private,
and out-of-pocket health spending, and DAH. Estimates are reported in 2018 US dollars, 2018 purchasing-power
parity-adjusted dollars, and as a percentage of gross domestic product. We used demographic decomposition
methods to assess a set of factors associated with changes in government health spending between 1995 and 2016
and to examine evidence to support the theory of the health financing transition. We projected two alternative future
scenarios based on higher government health spending to assess the potential ability of governments to generate
more resources for health.
Findings: Between 1995 and 2016, health spending grew at a rate of 4·00% (95% uncertainty interval 3·89â4·12)
annually, although it grew slower in per capita terms (2·72% [2·61â2·84]) and increased by less than 8·0 trillion (7·8â8·1) in 2016 (comprising 8·6% [8·4â8·7] of the global economy and 5252 (5184â5319) in high-income
countries, 81 (74â89) in lower-middle-income countries, and
9·5 billion, 24·3% of total DAH), although spending on other infectious diseases
(excluding tuberculosis and malaria) grew fastest from 2010 to 2018 (6·27% per year). The leading sources of DAH
were the USA and private philanthropy (excluding corporate donations and the Bill & Melinda Gates Foundation).
For the first time, we included estimates of Chinaâs contribution to DAH (15·0 trillion (14·0â16·0) by 2050 (reaching 9·4% [7·6â11·3] of the global
economy and $21·3 trillion [19·8â23·1] in purchasing-power parity-adjusted dollars), but at a lower growth rate of
1·84% (1·68â2·02) annually, and with continuing disparities in spending between countries. In 2050, we estimate
that 0·6% (0·6â0·7) of health spending will occur in currently low-income countries, despite these countries
comprising an estimated 15·7% of the global population by 2050. The ratio between per capita health spending in
high-income and low-income countries was 130·2 (122·9â136·9) in 2016 and is projected to remain at similar levels
in 2050 (125·9 [113·7â138·1]). The decomposition analysis identified governmentsâ increased prioritisation of the
health sector and economic development as the strongest factors associated with increases in government health
spending globally. Future government health spending scenarios suggest that, with greater prioritisation of the
health sector and increased government spending, health spending per capita could more than double, with greater
impacts in countries that currently have the lowest levels of government health spending
Interpretation: Financing for global health has increased steadily over the past two decades and is projected to continue
increasing in the future, although at a slower pace of growth and with persistent disparities in per-capita health
spending between countries. Out-of-pocket spending is projected to remain substantial outside of high-income
countries. Many low-income countries are expected to remain dependent on development assistance, although with
greater government spending, larger investments in health are feasible. In the absence of sustained new investments
in health, increasing efficiency in health spending is essential to meet global health targets.
Funding: Bill & Melinda Gates Foundatio
Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3
Background: Sustainable Development Goal (SDG) 3 aims to âensure healthy lives and promote well-being for all at all
agesâ. While a substantial effort has been made to quantify progress towards SDG3, less research has focused on
tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas
of SDG3, examine the association between outcomes and financing, and identify where resource gains are most
needed to achieve the SDG3 indicators for which data are available.
Methods: We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid
private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated
spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in
106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from
1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for
pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until
2030. We report all spending estimates in inflation-adjusted 2019 US7·9 trillion (95% uncertainty interval 7·8â8·0) in 2017 and is expected to increase to 20·2 billion
(17·0â25·0) and on tuberculosis it was 5·1 billion (4·9â5·4). Development assistance for health was 374 million of DAH was provided
for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis,
and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence,
and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to
increase from 81·6% (81·6â81·7) in 2015 to 83·1% (82·8â83·3) in 2030.
Interpretation: Health spending on SDG3 priority areas has increased, but not in all countries, and progress towards
meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of
spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do
not always results in improvements in outcomes. Although countries will probably need more resources to achieve
SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions
and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be
addressed.
Funding: The Bill & Melinda Gates Foundatio
Comparative genomics of two jute species and insight into fibre biogenesis
Jute (Corchorus sp.) is one of the most important sources of natural fibre, covering âŒ80% of global bast fibre production1. Only Corchorus olitorius and Corchorus capsularis are commercially cultivated, though there are more than 100 Corchorus species2 in the Malvaceae family. Here we describe high-quality draft genomes of these two species and their comparisons at the functional genomics level to support tailor-designed breeding. The assemblies cover 91.6% and 82.2% of the estimated genome sizes for C. olitorius and C. capsularis, respectively. In total, 37,031 C. olitorius and 30,096 C. capsularis genes are identified, and most of the genes are validated by cDNA and RNA-seq data. Analyses of clustered gene families and gene collinearity show that jute underwent shared whole-genome duplication âŒ18.66â
million years (Myr) ago prior to speciation. RNA expression analysis from isolated fibre cells reveals the key regulatory and structural genes involved in fibre formation. This work expands our understanding of the molecular basis of fibre formation laying the foundation for the genetic improvement of jute.
Bast (phloem) fibres are obtained from the stem of the plants such as jute, flax, hemp, ramie and kenaf. The annual global production of jute generates a farm value of âŒUS$2.3â
billion1. The cultivated species of jute, C. olitorius and C. capsularis, are morphologically and physiologically distinct (Supplementary Fig. 1), and a combination of useful traits from these species into a single genotype is highly desirable3. However, interspecific hybridization is limited because of their cross-incompatibility4,5. To facilitate comparative functional genomics and to understand the molecular basis of bast fibre biogenesis, genomes of two popular jute cultivars C. olitorius var. O-4 and C. capsularis var. CVL-1 are sequenced and analysed
Estimating global injuries morbidity and mortality: methods and data used in the Global Burden of Disease 2017 study
BACKGROUND: While there is a long history of measuring death and disability from injuries, modern research methods must account for the wide spectrum of disability that can occur in an injury, and must provide estimates with sufficient demographic, geographical and temporal detail to be useful for policy makers. The Global Burden of Disease (GBD) 2017 study used methods to provide highly detailed estimates of global injury burden that meet these criteria. METHODS: In this study, we report and discuss the methods used in GBD 2017 for injury morbidity and mortality burden estimation. In summary, these methods included estimating cause-specific mortality for every cause of injury, and then estimating incidence for every cause of injury. Non-fatal disability for each cause is then calculated based on the probabilities of suffering from different types of bodily injury experienced. RESULTS: GBD 2017 produced morbidity and mortality estimates for 38 causes of injury. Estimates were produced in terms of incidence, prevalence, years lived with disability, cause-specific mortality, years of life lost and disability-adjusted life-years for a 28-year period for 22 age groups, 195 countries and both sexes. CONCLUSIONS: GBD 2017 demonstrated a complex and sophisticated series of analytical steps using the largest known database of morbidity and mortality data on injuries. GBD 2017 results should be used to help inform injury prevention policy making and resource allocation. We also identify important avenues for improving injury burden estimation in the future
Measurement of the transverse polarization of Î and ÎÂŻ hyperons produced in proton-proton collisions at âs=7ââTeV using the ATLAS detector
The transverse polarization of Î and ÎÂŻ hyperons produced in proton-proton collisions at a center-of-mass energy of 7 TeV is measured. The analysis uses 760ââÎŒbâ1 of minimum bias data collected by the ATLAS detector at the LHC in the year 2010. The measured transverse polarization averaged over Feynman xF from 5Ă10â5 to 0.01 and transverse momentum pT from 0.8 to 15 GeV is â0.010±0.005(stat)±0.004(syst) for Î and 0.002±0.006(stat)±0.004(syst) for ÎÂŻ. It is also measured as a function of xF and pT, but no significant dependence on these variables is observed. Prior to this measurement, the polarization was measured at fixed-target experiments with center-of-mass energies up to about 40 GeV. The ATLAS results are compatible with the extrapolation of a fit from previous measurements to the xF range covered by this measurement
Charged-particle distributions at low transverse momentum in âs=13 13 TeV pp interactions measured with the ATLAS detector at the LHC
Measurements of distributions of charged particles produced in protonâproton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 ÎŒb â1 ÎŒbâ1 . The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators
Measurement of the inelastic proton-proton cross section at âs=13 TeV with the ATLAS detector at the LHC
This Letter presents a measurement of the inelastic proton-proton cross section using 60ââÎŒb â1 of pp collisions at a center-of-mass energy âs of 13 TeV with the ATLAS detector at the LHC. Inelastic interactions are selected using rings of plastic scintillators in the forward region (2.0710 â6 , where M X is the larger invariant mass of the two hadronic systems separated by the largest rapidity gap in the event. In this Ο range the scintillators are highly efficient. For diffractive events this corresponds to cases where at least one proton dissociates to a system with M X >13ââGeV . The measured cross section is compared with a range of theoretical predictions. When extrapolated to the full phase space, a cross section of 78.1±2.9ââmb is measured, consistent with the inelastic cross section increasing with center-of-mass energy
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