This is the publisher's version, also available electronically from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822014000100057&lng=en&nrm=iso&tlng=en ; Introduction: In past decades, leishmaniasis burden has been low across Egypt; however, changing environment and land use has placed several parts of the country at risk. As a consequence, leishmaniasis has become a particularly difficult health problem, both for local inhabitants and for multinational military personnel. Methods: To evaluate coarse-resolution aspects of the ecology of leishmaniasis transmission, collection records for sandflies and Leishmania species were obtained from diverse sources. To characterize environmental variation across the country, we used multitemporal Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for 2005-2011. Ecological niche models were generated using MaxEnt, and results were analyzed using background similarity tests to assess whether associations among vectors and parasites (i.e., niche similarity) can be detected across broad geographic regions. Results: We found niche similarity only between one vector species and its corresponding parasite species (i.e., Phlebotomus papatasi with Leishmania major), suggesting that geographic ranges of zoonotic cutaneous leishmaniasis and its potential vector may overlap, but under distinct environmental associations. Other associations (e.g., P. sergenti with L. major) were not supported. Mapping suitable areas for each species suggested that northeastern Egypt is particularly at risk because both parasites have potential to circulate. Conclusions: Ecological niche modeling approaches can be used as a first-pass assessment of vector-parasite interactions, offering useful insights into constraints on the geography of transmission patterns of leishmaniasis
Background The Mediterranean Basin is historically a hotspot for trade, transport, and migration. As a result, countries surrounding the Mediterranean Sea share common public health threats. Among them are vector-borne diseases, and in particular, mosquito-borne viral diseases are prime candidates as (re)emerging diseases and are likely to spread across the area. Improving preparedness and response capacities to these threats at the regional level is therefore a major issue., The implementation of entomological surveillance is, in particular, of utmost importance. Guidance in designing entomological surveillance systems is critical, and these systems may pursue different specific objectives depending on the disease., The purpose of the proposed review is to draw up guidelines for designing effective and sustainable entomological surveillance systems in order to improve preparedness and response. However, we make it clear that there is no universal surveillance system, so the thinking behind harmonisation is to define evidence-based standards in order to promote best practises, identify the most appropriate surveillance activities, and optimise the use of resources., Such guidance is aimed at policymakers and diverse stakeholders and is intended to be used as a framework for the implementation of entomological surveillance programmes. It will also be useful to collaborate and share information with health professionals involved in other areas of disease surveillance. Medical entomologists and vector control professionals will be able to refer to this report to advocate for tailored entomological surveillance strategies., The main threats targeted in this review are the vectors of dengue virus, chikungunya virus, Zika virus, West Nile virus, and Rift Valley fever virus. The vectors of all these arboviruses are mosquitoes. Methods Current knowledge on vector surveillance in the Mediterranean area is reviewed. The analysis was carried out by a collaboration of the medical entomology experts in the region, all of whom belong to the MediLabSecure network, which is currently funded by the European Union and represents an international effort encompassing 19 countries in the Mediterranean and Black Sea region. Findings Robust surveillance systems are required to address the globalisation of emerging arboviruses. The prevention and management of mosquito-borne viral diseases must be addressed in the prism of a One Health strategy that includes entomological surveillance as an integral part of the policy. Entomological surveillance systems should be designed according to the entomological and epidemiological context and must have well-defined objectives in order to effect a tailored and graduated response. We therefore rely on different scenarios according to different entomological and epidemiological contexts and set out detailed objectives of surveillance. The development of multidisciplinary networks involving both academics and public authorities will provide resources to address these health challenges by promoting good practises in surveillance (identification of surveillance aims, design of surveillance systems, data collection, dissemination of surveillance results, evaluation of surveillance activities) and through the sharing of effective knowledge and information. These networks will also contribute to capacity building and stronger collaborations between sectors at both the local and regional levels. Finally, concrete guidance is offered on the vector of the main arbovirus based on the current situation in the area.
Government and nongovernmental organizations need national and global estimates on the descriptive epidemiology of common oral conditions for policy planning and evaluation. The aim of this component of the Global Burden of Disease study was to produce estimates on prevalence, incidence, and years lived with disability for oral conditions from 1990 to 2017 by sex, age, and countries. In addition, this study reports the global socioeconomic pattern in burden of oral conditions by the standard World Bank classification of economies as well as the Global Burden of Disease Socio-demographic Index. The findings show that oral conditions remain a substantial population health challenge. Globally, there were 3.5 billion cases (95% uncertainty interval [95% UI], 3.2 to 3.7 billion) of oral conditions, of which 2.3 billion (95% UI, 2.1 to 2.5 billion) had untreated caries in permanent teeth, 796 million (95% UI, 671 to 930 million) had severe periodontitis, 532 million (95% UI, 443 to 622 million) had untreated caries in deciduous teeth, 267 million (95% UI, 235 to 300 million) had total tooth loss, and 139 million (95% UI, 133 to 146 million) had other oral conditions in 2017. Several patterns emerged when the World Bank's classification of economies and the Socio-demographic Index were used as indicators of economic development. In general, more economically developed countries have the lowest burden of untreated dental caries and severe periodontitis and the highest burden of total tooth loss. The findings offer an opportunity for policy makers to identify successful oral health strategies and strengthen them; introduce and monitor different approaches where oral diseases are increasing; plan integration of oral health in the agenda for prevention of noncommunicable diseases; and estimate the cost of providing universal coverage for dental care.
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 $1 per capita over this period in 22 of 195 countries. The highest annual growth rates in per capita health spending were observed in upper-middle-income countries (5·55% [5·18-5·95]), mainly due to growth in government health spending, and in lower-middle-income countries (3·71% [3·10-4·34]), mainly from DAH. Health spending globally reached $8·0 trillion (7·8-8·1) in 2016 (comprising 8·6% [8·4-8·7] of the global economy and $10·3 trillion [10·1-10·6] in purchasing-power parity-adjusted dollars), with a per capita spending of US$5252 (5184-5319) in high-income countries, $491 (461-524) in upper-middle-income countries, $81 (74-89) in lower-middle-income countries, and $40 (38-43) in low-income countries. In 2016, 0·4% (0·3-0·4) of health spending globally was in low-income countries, despite these countries comprising 10·0% of the global population. In 2018, the largest proportion of DAH targeted HIV/AIDS ($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 ($644·7 million in 2018). Globally, health spending is projected to increase to $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. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; Sí
BACKGROUND: Traumatic brain injury (TBI) and spinal cord injury (SCI) are increasingly recognised as global health priorities in view of the preventability of most injuries and the complex and expensive medical care they necessitate. We aimed to measure the incidence, prevalence, and years of life lived with disability (YLDs) for TBI and SCI from all causes of injury in every country, to describe how these measures have changed between 1990 and 2016, and to estimate the proportion of TBI and SCI cases caused by different types of injury. METHODS: We used results from the Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study 2016 to measure the global, regional, and national burden of TBI and SCI by age and sex. We measured the incidence and prevalence of all causes of injury requiring medical care in inpatient and outpatient records, literature studies, and survey data. By use of clinical record data, we estimated the proportion of each cause of injury that required medical care that would result in TBI or SCI being considered as the nature of injury. We used literature studies to establish standardised mortality ratios and applied differential equations to convert incidence to prevalence of long-term disability. Finally, we applied GBD disability weights to calculate YLDs. We used a Bayesian meta-regression tool for epidemiological modelling, used cause-specific mortality rates for non-fatal estimation, and adjusted our results for disability experienced with comorbid conditions. We also analysed results on the basis of the Socio-demographic Index, a compound measure of income per capita, education, and fertility. FINDINGS: In 2016, there were 27·08 million (95% uncertainty interval [UI] 24·30-30·30 million) new cases of TBI and 0·93 million (0·78-1·16 million) new cases of SCI, with age-standardised incidence rates of 369 (331-412) per 100 000 population for TBI and 13 (11-16) per 100 000 for SCI. In 2016, the number of prevalent cases of TBI was 55·50 million (53·40-57·62 million) and of SCI was 27·04 million (24·98-30·15 million). From 1990 to 2016, the age-standardised prevalence of TBI increased by 8·4% (95% UI 7·7 to 9·2), whereas that of SCI did not change significantly (-0·2% [-2·1 to 2·7]). Age-standardised incidence rates increased by 3·6% (1·8 to 5·5) for TBI, but did not change significantly for SCI (-3·6% [-7·4 to 4·0]). TBI caused 8·1 million (95% UI 6·0-10·4 million) YLDs and SCI caused 9·5 million (6·7-12·4 million) YLDs in 2016, corresponding to age-standardised rates of 111 (82-141) per 100 000 for TBI and 130 (90-170) per 100 000 for SCI. Falls and road injuries were the leading causes of new cases of TBI and SCI in most regions. INTERPRETATION: TBI and SCI constitute a considerable portion of the global injury burden and are caused primarily by falls and road injuries. The increase in incidence of TBI over time might continue in view of increases in population density, population ageing, and increasing use of motor vehicles, motorcycles, and bicycles. The number of individuals living with SCI is expected to increase in view of population growth, which is concerning because of the specialised care that people with SCI can require. Our study was limited by data sparsity in some regions, and it will be important to invest greater resources in collection of data for TBI and SCI to improve the accuracy of future assessments. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation ; We acknowledge the funding and support of the Bill & Melinda Gates Foundation. AK was supported by the Miguel Servet contract, which was financed by the CP13/00150 and PI15/00862 projects integrated into the National Research, Development, and Implementation,and funded by the Instituto de Salud Carlos III General Branch Evaluation and Promotion of Health Research and the European Regional Development Fund (ERDF-FEDER). AMS is supported by the Egyptian Fulbright Mission Program. AF acknowledges the Federal University of Sergipe (Sergipe, Brazil). AA received financial assistance from the Indian Department of Science and Technology (New Delhi, India) through the INSPIRE faculty programme. AS is supported by Health Data Research UK. DJS is supported by the South African Medical Research Council. AB is supported by the Public Health Agency of Canada. SMSI received a senior research fellowship from the Institute for Physical Activity and Nutrition, Deakin University (Waurn Ponds, VIC, Australia), and a career transition grant from the High Blood Pressure Research Council of Australia. FP and CF acknowledge support from the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e a Tecnologia, and Ministério da Educação e Ciência) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020 UID/QUI/50006/2013. TB acknowledges financial support from the Institute of Medical Research and Medicinal Plant Studies, Yaoundé, Cameroon. AM of Imperial College London is grateful for support from the Northwest London National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research andCare and the Imperial NIHR Biomedical Research Centre. KD is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (grant number 201900). PSA is supported by an Australian National Health and Medical Research Council Early Career Fellowship. RT-S was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. The Serbian part of this contribution (by MJ) has been co-financed with grant OI175014 from the Serbian Ministry of Education, Science and Technological Development; publication of results was not contingent upon the Ministry's approval. MMMSM acknowledges support from the Serbian Ministry of Education, Science and Technological Development (contract 175087). MM's research was supported by the NIHR Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust (London, UK) and King's College London. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt professor award, which was funded by the German Federal Ministry of Education and Research ; Sí
High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations
High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. ; his work was primarily supported by the Bill & Melinda Gates Foundation (grant OPP1132415). Additionally, O Adetokunboh acknowledges the support of the Department of Science and Innovation, and National Research Foundation of South Africa. M Ausloos, A Pana, and C Herteliu are partially supported by a grant of the Romanian National Authority for Scientific Research and Innovation, Executive Agency for Higher Education, Research, Development and Innovation Funding (Romania; project number PN-III-P4-ID-PCCF-2016-0084). T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. M J Bockarie is supported by the European and Developing Countries Clinical Trials Partnership. F Carvalho and E Fernandes acknowledge support from Portuguese national funds (Fundação para a Ciência e Tecnologia and Ministério da Ciência, Tecnologia e Ensino Superior; UIDB/50006/2020, UIDB/04378/2020, and UIDP/04378/2020. K Deribe is supported by the Wellcome Trust (grant 201900/Z/16/Z) as part of his International Intermediate Fellowship. B-F Hwang was partially supported by China Medical University (CMU107-Z-04), Taichung, Taiwan. M Jakovljevic acknowledges support of the Serbia Ministry of Education Science and Technological Development (grant OI 175 014). M N Khan acknowledges the support of Jatiya Kabi Kazi Nazrul Islam University, Bangladesh. Y J Kim was supported by the Research Management Centre, Xiamen University Malaysia, Malaysia, (XMUMRF/2020-C6/ITCM/0004). K Krishnan is supported by University Grants Commission Centre of Advanced Study, (CAS II), awarded to the Department of Anthropology, Panjab University, Chandigarh, India. M Kumar would like to acknowledge National Institutes of Health and Fogarty International Cente (K43TW010716). I Landires is a member of the Sistema Nacional de Investigación, which is supported by the Secretaría Nacional de Ciencia, Tecnología e Innovación, Panama. W Mendoza is a program analyst in population and development at the UN Population Fund Country Office in Peru, which does not necessarily endorse this study. M Phetole received institutional support from the Grants, Innovation and Product Development Unit, South African Medical Research Council. O Odukoya acknowledges support from the Fogarty International Center of the US National Institutes of Health (K43TW010704). The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Institutes of Health. O Oladimeji is grateful for the support from Walter Sisulu University, Eastern Cape, South Africa, the University of Botswana, Botswana, and the University of Technology of Durban, Durban, South Africa. J R Padubidri acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, India. G C Patton is supported by an Australian Government National Health and Medical Research Council research fellowship. P Rathi acknowledges Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal India. A I Ribeiro was supported by National Funds through Fundação para a Ciência e Tecnologia, under the programme of Stimulus of Scientific Employment–Individual Support (CEECIND/02386/2018). A M Samy acknowledges the support of the Egyptian Fulbright Mission Program. F Sha was supported by the Shenzhen Social Science Fund (SZ2020C015) and the Shenzhen Science and Technology Program (KQTD20190929172835662). A Sheikh is supported by Health Data Research UK. N Taveira acknowledges partial funding by Fundação para a Ciência e Tecnologia, Portugal, and Aga Khan Development Network—Portugal Collaborative Research Network in Portuguese-speaking countries in Africa (332821690), and by the European and Developing Countries Clinical Trials Partnership (RIA2016MC-1615). C S Wiysonge is supported by the South African Medical Research Council. Y Zhang was supported by the Science and Technology Research Project of Hubei Provincial Department of Education (Q20201104) and Open Fund Project of Hubei Province Key Laboratory of Occupational Hazard Identification and Control (OHIC2020Y01).Editorial note: the Lancet Group takes a neutral position with respect to territorial claims in published maps and institutional affiliations
Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020.
Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247-308]) and second leading cause of deaths (9.0 million [8.8-9.4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34-44] and DALYs by 15% [9-21]) whereas their age-standardised rates decreased (deaths by 28% [26-30] and DALYs by 27% [24-31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42.2% [38.6-46.1]), migraine (16.3% [11.7-20.8]), Alzheimer's and other dementias (10.4% [9.0-124]), and meningitis (7.9% [6.6-10.4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1.12 [1.05-1.20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0.7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88.8% (86.5-90.9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22.3% [11.8-35.1] of DALYs are risk attributable) and idiopathic epilepsy (14.1% [10.8-17.5] of DALYs are risk attributable). Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Copyright (C) The Author(s). Published by Elsevier Ltd.
Publisher´s version (útgefin grein). ; Background Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders.Methods We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach.Findings Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable).Interpretation Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. ; ROA is funded by the National Institutes of Health (U01HG010273). SMA acknowledges the International Centre for Casemix and Clinical Coding, Faculty of Medicine, National University of Malaysia and Department of Health Policy and Management, Faculty of Public Health, Kuwait University for the approval and support to participate in this research project. AAw acknowledges funding support from Department of Science and Technology, Government of India, New Delhi, through INSPIRE Faculty scheme. TBA acknowledges partial funding from the Institute of Medical Research and Medicinal Plant Studies. ABa is supported by the Public Health Agency of Canada. TWB was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor Award, funded by the Federal Ministry of Education and Research. MSBS acknowledges support from the Australian Government Research and Training Program scholarship for a PhD degree at the Australian National University, Australia. JJC is supported by the Swedish Heart and Lung Foundation. FCar is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundacao para a Ciencia e a Tecnologia and Ministerio da Educacao e Ciencia) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. EC is supported by an Australian Research Council Future Fellowship (FT3 140100085). KD is supported by a Wellcome Trust [Grant Number 201900] as part of his International Intermediate Fellowship. EF is supported by the European Union (FEDER funds POCI/01/0145/FEDER/007728 and POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundacao para a Ciencia e a Tecnologia and Ministerio da Educacao e Ciencia) under the Partnership Agreements PT2020 UID/MULTI/04378/2013 and PT2020UID/QUI/50006/2013. SMSI is funded by the Institute for Physical Activity and Nutrition (IPAN), Deakin University and received funding from High Blood Pressure Research Council of Australia. YKa is a DBT/Wellcome Trust India Alliance Fellow in Public Health. YJK is supported by the Office of Research and Innovation at Xiamen University Malaysia. BL acknowledges funding from the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre. WDL is supported in part by U10NS086484 NINDS. SLo is funded by the German Federal Ministry of Education and Research (nutriCARD, grant agreement number 01EA1411A). RML is supported by a National Health and Medical Research Council (NHMRC) of Australia Senior Research Fellowship. AMa and the Imperial College London are grateful for support from the NW London NIHR Collaboration for Leadership in Applied Health Research and Care. JJM is supported by the Danish National Research Foundation (Niels Bohr Professorship), and the John Cade Fellowship (APP1056929) from NHMRC. TMei acknowledges additional institutional support from the Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD), Jena-Halle-Leipzig. IMV is supported by the Sistema Nacional de Investigacion (Panama). MOO is supported by SIREN U54 U54HG007479 and SIBS Genomics R01NS107900 grants. AMS was supported by a fellowship from the Egyptian Fulbright Mission Program. MMSM acknowledges the support from the Ministry of Education, Science and Technological Development, Republic of Serbia (contract no 175087). AShe is supported by Health Data Research UK. MBS' work on traumatic brain injury is supported by grants NIH U01 NS086090 (PI G Manley) from the National Institutes of Health (NIH) and DoD W81XWH-14-2-0176 (PI G Manley) from the United States Department of Defense. RTS is supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIIIFEDER. AGT was supported by a Fellowship from the NHMRC (Australia; 1042600. KBT acknowledges funding supports from the Maurice Wilkins Centre for Biodiscovery, Cancer Society of New Zealand, Health Research Council, Gut Cancer Foundation, and the University of Auckland. CY acknowledges support from the National Natural Science Foundation of China (grant number 81773552) and the Chinese NSFC International Cooperation and Exchange Program (grant number 71661167007). ; "Peer Reviewed"
BACKGROUND: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. METHODS: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. FINDINGS: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247-308]) and second leading cause of deaths (9·0 million [8·8-9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34-44] and DALYs by 15% [9-21]) whereas their age-standardised rates decreased (deaths by 28% [26-30] and DALYs by 27% [24-31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6-46·1]), migraine (16·3% [11·7-20·8]), Alzheimer's and other dementias (10·4% [9·0-12·1]), and meningitis (7·9% [6·6-10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05-1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5-90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8-35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8-17·5] of DALYs are risk attributable). INTERPRETATION: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. FUNDING: Bill & Melinda Gates Foundation. ; Bill & Melinda Gates Foundation. ; Sí
Background: Neurological disorders are increasingly recognised as major causes of death and disability worldwide. The aim of this analysis from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 is to provide the most comprehensive and up-to-date estimates of the global, regional, and national burden from neurological disorders. Methods: We estimated prevalence, incidence, deaths, and disability-adjusted life-years (DALYs; the sum of years of life lost [YLLs] and years lived with disability [YLDs]) by age and sex for 15 neurological disorder categories (tetanus, meningitis, encephalitis, stroke, brain and other CNS cancers, traumatic brain injury, spinal cord injury, Alzheimer's disease and other dementias, Parkinson's disease, multiple sclerosis, motor neuron diseases, idiopathic epilepsy, migraine, tension-type headache, and a residual category for other less common neurological disorders) in 195 countries from 1990 to 2016. DisMod-MR 2.1, a Bayesian meta-regression tool, was the main method of estimation of prevalence and incidence, and the Cause of Death Ensemble model (CODEm) was used for mortality estimation. We quantified the contribution of 84 risks and combinations of risk to the disease estimates for the 15 neurological disorder categories using the GBD comparative risk assessment approach. Findings: Globally, in 2016, neurological disorders were the leading cause of DALYs (276 million [95% UI 247–308]) and second leading cause of deaths (9·0 million [8·8–9·4]). The absolute number of deaths and DALYs from all neurological disorders combined increased (deaths by 39% [34–44] and DALYs by 15% [9–21]) whereas their age-standardised rates decreased (deaths by 28% [26–30] and DALYs by 27% [24–31]) between 1990 and 2016. The only neurological disorders that had a decrease in rates and absolute numbers of deaths and DALYs were tetanus, meningitis, and encephalitis. The four largest contributors of neurological DALYs were stroke (42·2% [38·6–46·1]), migraine (16·3% [11·7–20·8]), Alzheimer's and other dementias (10·4% [9·0–12·1]), and meningitis (7·9% [6·6–10·4]). For the combined neurological disorders, age-standardised DALY rates were significantly higher in males than in females (male-to-female ratio 1·12 [1·05–1·20]), but migraine, multiple sclerosis, and tension-type headache were more common and caused more burden in females, with male-to-female ratios of less than 0·7. The 84 risks quantified in GBD explain less than 10% of neurological disorder DALY burdens, except stroke, for which 88·8% (86·5–90·9) of DALYs are attributable to risk factors, and to a lesser extent Alzheimer's disease and other dementias (22·3% [11·8–35·1] of DALYs are risk attributable) and idiopathic epilepsy (14·1% [10·8–17·5] of DALYs are risk attributable). Interpretation: Globally, the burden of neurological disorders, as measured by the absolute number of DALYs, continues to increase. As populations are growing and ageing, and the prevalence of major disabling neurological disorders steeply increases with age, governments will face increasing demand for treatment, rehabilitation, and support services for neurological disorders. The scarcity of established modifiable risks for most of the neurological burden demonstrates that new knowledge is required to develop effective prevention and treatment strategies. Funding: Bill & Melinda Gates Foundation.
Importance Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572 000 deaths and 15.2 million DALYs), and stomach cancer (542 000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819 000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601 000 deaths and 17.4 million DALYs), TBL cancer (596 000 deaths and 12.6 million DALYs), and colorectal cancer (414 000 deaths and 8.3 million DALYs). Conclusions and Relevance The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer