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- Murray, Christopher J. L., et al.
(author)
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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
- 2018
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In: The Lancet. - 1474-547X .- 0140-6736. ; 392:10159, s. 1995-2051
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Journal article (peer-reviewed)abstract
- 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.
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- Sepanlou, Sadaf G., et al.
(author)
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The global, regional, and national burden of cirrhosis by cause in 195 countries and territories, 1990-2017 : a systematic analysis for the Global Burden of Disease Study 2017
- 2020
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In: The Lancet Gastroenterology & Hepatology. - 2468-1253. ; 5:3, s. 245-266
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Journal article (peer-reviewed)abstract
- Background Cirrhosis and other chronic liver diseases (collectively referred to as cirrhosis in this paper) are a major cause of morbidity and mortality globally, although the burden and underlying causes differ across locations and demographic groups. We report on results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 on the burden of cirrhosis and its trends since 1990, by cause, sex, and age, for 195 countries and territories. Methods We used data from vital registrations, vital registration samples, and verbal autopsies to estimate mortality. We modelled prevalence of total, compensated, and decompensated cirrhosis on the basis of hospital and claims data. Disability-adjusted life-years (DALYs) were calculated as the sum of years of life lost due to premature death and years lived with disability. Estimates are presented as numbers and age-standardised or age-specific rates per 100 000 population, with 95% uncertainty intervals (UIs). All estimates are presented for five causes of cirrhosis: hepatitis B, hepatitis C, alcohol-related liver disease, non-alcoholic steatohepatitis (NASH), and other causes. We compared mortality, prevalence, and DALY estimates with those expected according to the Socio-demographic Index (SDI) as a proxy for the development status of regions and countries. Findings In 2017, cirrhosis caused more than 1.32 million (95% UI 1.27-1.45) deaths (440000 [416 000-518 000; 33.3%] in females and 883 000 [838 000-967 000; 66.7%] in males) globally, compared with less than 899 000 (829 000-948 000) deaths in 1990. Deaths due to cirrhosis constituted 2.4% (2.3-2.6) of total deaths globally in 2017 compared with 1.9% (1.8-2.0) in 1990. Despite an increase in the number of deaths, the age-standardised death rate decreased from 21.0 (19.2-22.3) per 100 000 population in 1990 to 16.5 (15.8-18-1) per 100 000 population in 2017. Sub-Saharan Africa had the highest age-standardised death rate among GBD super-regions for all years of the study period (32.2 [25.8-38.6] deaths per 100 000 population in 2017), and the high-income super-region had the lowest (10.1 [9.8-10-5] deaths per 100 000 population in 2017). The age-standardised death rate decreased or remained constant from 1990 to 2017 in all GBD regions except eastern Europe and central Asia, where the age-standardised death rate increased, primarily due to increases in alcohol-related liver disease prevalence. At the national level, the age-standardised death rate of cirrhosis was lowest in Singapore in 2017 (3.7 [3.3-4.0] per 100 000 in 2017) and highest in Egypt in all years since 1990 (103.3 [64.4-133.4] per 100 000 in 2017). There were 10.6 million (10.3-10.9) prevalent cases of decompensated cirrhosis and 112 million (107-119) prevalent cases of compensated cirrhosis globally in 2017. There was a significant increase in age-standardised prevalence rate of decompensated cirrhosis between 1990 and 2017. Cirrhosis caused by NASH had a steady age-standardised death rate throughout the study period, whereas the other four causes showed declines in age-standardised death rate. The age-standardised prevalence of compensated and decompensated cirrhosis due to NASH increased more than for any other cause of cirrhosis (by 33.2% for compensated cirrhosis and 54.8% for decompensated cirrhosis) over the study period. From 1990 to 2017, the number of prevalent cases snore than doubled for compensated cirrhosis due to NASH and more than tripled for decompensated cirrhosis due to NASH. In 2017, age-standardised death and DALY rates were lower among countries and territories with higher SDI. Interpretation Cirrhosis imposes a substantial health burden on many countries and this burden has increased at the global level since 1990, partly due to population growth and ageing. Although the age-standardised death and DALY rates of cirrhosis decreased from 1990 to 2017, numbers of deaths and DALYs and the proportion of all global deaths due to cirrhosis increased. Despite the availability of effective interventions for the prevention and treatment of hepatitis B and C, they were still the main causes of cirrhosis burden worldwide, particularly in low-income countries. The impact of hepatitis B and C is expected to be attenuated and overtaken by that of NASH in the near future. Cost-effective interventions are required to continue the prevention and treatment of viral hepatitis, and to achieve early diagnosis and prevention of cirrhosis due to alcohol-related liver disease and NASH.
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3. |
- Abbafati, Cristiana, et al.
(author)
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- 2020
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Journal article (peer-reviewed)
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4. |
- Bravo, L, et al.
(author)
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- 2021
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swepub:Mat__t
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5. |
- Tabiri, S, et al.
(author)
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- 2021
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swepub:Mat__t
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6. |
- Mohammadi, Babak, et al.
(author)
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IHACRES, GR4J and MISD-based multi conceptual-machine learning approach for rainfall-runoff modeling
- 2022
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 12
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Journal article (peer-reviewed)abstract
- As a complex hydrological problem, rainfall-runoff (RR) modeling is of importance in runoff studies, water supply, irrigation issues, and environmental management. Among the variety of approaches for RR modeling, conceptual approaches use physical concepts and are appropriate methods for representation of the physics of the problem while may fail in competition with their advanced alternatives. Contrarily, machine learning approaches for RR modeling provide high computation ability however, they are based on the data characteristics and the physics of the problem cannot be completely understood. For the sake of overcoming the aforementioned deficiencies, this study coupled conceptual and machine learning approaches to establish a robust and more reliable RR model. To this end, three hydrological process-based models namely: IHACRES, GR4J, and MISD are applied for runoff simulating in a snow-covered basin in Switzerland and then, conceptual models’ outcomes together with more hydro-meteorological variables were incorporated into the model structure to construct multilayer perceptron (MLP) and support vector machine (SVM) models. At the final stage of the modeling procedure, the data fusion machine learning approach was implemented through using the outcomes of MLP and SVM models to develop two evolutionary models of fusion MLP and hybrid MLP-whale optimization algorithm (MLP-WOA). As a result of conceptual models, the IHACRES-based model better simulated the RR process in comparison to the GR4J, and MISD models. The effect of incorporating meteorological variables into the coupled hydrological process-based and machine learning models was also investigated where precipitation, wind speed, relative humidity, temperature and snow depth were added separately to each hydrological model. It is found that incorporating meteorological variables into the hydrological models increased the accuracy of the models in runoff simulation. Three different learning phases were successfully applied in the current study for improving runoff peak simulation accuracy. This study proved that phase one (only hydrological model) has a big error while phase three (coupling hydrological model by machine learning model) gave a minimum error in runoff estimation in a snow-covered catchment. The IHACRES-based MLP-WOA model with RMSE of 8.49 m3/s improved the performance of the ordinary IHACRES model by a factor of almost 27%. It can be considered as a satisfactory achievement in this study for runoff estimation through applying coupled conceptual-ML hydrological models. Recommended methodology in this study for RR modeling may motivate its application in alternative hydrological problems.
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