Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Reconfiguration and DG placement considering critical system condition

This paper offers a method to reconfiguration and DG placement simultaneously considering critical system condition in distribution systems. The critical system conditions like tripping a 63/20kv distribution transformer and adding an external maneuver loud. Additional finding place and power of DG in this research, optimal power factor is obtained by the given algorithm. Reconfiguration of distribution system is implemented by adaptive genetic algorithm and graph theory to find an optimal structure system with place and power of distributed generators. The offered algorithm is effectively implemented on a 33-bus IEEE test system and a real life distribution system in Iran by Digsilent and Matlab software

Effects of Air Impingement Jet Drying on Drying Kinetics and Some Quality Attributes of Strawberry Slices

Introduction Strawberry plays an important role in human health because of its micronutrients and natural antioxidant content. Increasing storage time and decreasing microbial processes, weight and volume, and eventually facilitating export, has bolded the need for drying this product. The most common drying method is sun drying. This technique requires large areas and lengthens the time to complete the process which is undesirable economically. Furthermore, the final product may be contaminated by dust and insects, and the exposure to solar radiation results in color deterioration. In order to improve the quality, traditional sun drying techniques can be replaced by a more rapid and efficient drying method such as hot-air drying. In recent years air impingement technology has got more attention in the field fruit slices drying due to high heat and mass transfer, decreasing drying time and increasing product quality. The objectives of this study were to investigate the effects of drying conditions on the drying kinetics and quality characteristics including the rehydration ratio of the strawberry slices in an air impingement jet dryer. Materials and Methods An air jet impingement dryer with controllable temperature, air velocity, and the relative nozzle-to-product distance (H/D) was used in this study. The experiments were conducted under different temperatures (45, 55, and 65°C), air velocities (6, 9, and 12 m s-1) and H/D ratios (4, 5, 6, 7, and 8). The initial moisture content, effective moisture diffusivity, activation energy, and rehydration ratio were evaluated. Results and Discussion The effects of drying temperature and air velocity on the moisture ratio and the drying rate are shown in Figs 2 and 3. As it can be seen, the moisture ratio of strawberry slices decreased with the increase of drying time. The analysis of variance for drying time indicated that increasing drying temperature and air velocity could reduce the drying time.  In addition, the effect of drying temperature on drying time was more significant than that of the air velocity.  It is clear that the drying rate decreased with moisture content. There was a rapid decrease in drying rate during the initial period and slow decrease at the later stages of the drying process. It is also found that the drying process generally took place in the falling rate period. It is observed that the moisture ratio decreased as H/D ratio fall. The response of drying time was affected significantly (p < 0.05) by H/D ratio. The effective moisture diffusivity increased with increasing drying temperature and air velocity. Based on the results reported in this study, the Wang and Singh model with the lowest Root Mean Square Error (RMSE=0.02) and the highest Coefficient of determination (R2=0.996) provided the best fit to describe the experimental drying data of strawberry slices. The statistical analysis shows that drying temperature and air velocity have significant (p < 0.01) effect on the rehydration ratio (RR) of slices, while the interaction effect was not significant. The means comparison shows that the RR of dried slices decreased as drying temperature and air velocity rose. H/D ratio significantly (1%) affected rehydration ratio. The means comparisons shows that the rehydration ratio increased when H/D value varied from 4 to 8. Also, the results of color change represented that color change of dried samples decreased with increase of temperature and air velocity and increased with increase of the H/D ratio. Conclusions a) Increasing drying temperature and air velocity dropped the drying time. In addition, the effect of drying temperature on drying time was more significant than that of the air velocity. b) A constant rate period was not observed in drying of strawberry slices and the whole process of strawberry slices was carried out in the falling rate period. c) The moisture ratio decreased as H/D ratio dropped, which in turn resulted in saving drying times. d) The Wang and Singh model was found to be the best model to describe the drying kinetics of strawberry slices. e) The effective moisture diffusivity of strawberry slices ranged from 1.62×10-10 to 3.24×10-10 m2 s-1. f) The values of activation energy of strawberry slices were found to be 12.88, 15.055 and 16.746 kJ mol-1 for air velocities of 6, 9 and 12 m s-1, respectively. g) The rehydration ratio of dried slices dropped as the drying temperature and air velocity rose and increased with increase of the H/D ratio. h) The color change of dried samples decreased with the increase of temperature and air velocity and increased with the increase of the H/D ratio

Discovering Knowledge and Cognitive Based Drivers for SMEs Internationalization

Internationalisation begins with companies’ decision to enter global markets to develop knowledge and experience as key competitive factors in the global economy, which has been the subject of much empirical research. Decision-making, knowledge management, and effective internationalisation have become key strategic tools for all companies, especially for small- and medium-sized enterprises (SMEs). This study wants to provide a framework for SMEs internationalisation based on the real options theory, (ROT) as a knowledge driver method. For this purpose, the effective factors for internationalisation were identified by reviewing the literature on the subject and the internal and external backgrounds of the subject. Then, main and sub-factors were prioritised by the fuzzy analytic hierarchy process (AHP) method. The statistical population consisted of senior managers, business managers of SMEs in Isfahan, Iran, who were eligible to enter this study. Twenty-six experts participated in this study by judgmental non-random sampling method. A fuzzy AHP questionnaire was prepared in the form of 19 sub-factors and 7 main factors. The components of each factor in each group were also ranked by experts, and their weights were obtained. Next, according to the ROT strategies which have 5 options, an alignment matrix was used to align the factors affecting the decision with the strategies. After answering the research question, the option that had a higher mode was considered AS; then, this score was multiplied by the weight obtained in the previous step and the TAS was obtained. Finally, strategies were classified as appropriate, need further investigation, and inappropriate