Influence of tillage depth, penetration angle and forward speed on the soil/thin-blade interaction force

In this study, an experimental investigation regarding the influence of three independent variables including tillage depth (10, 15, 20 cm), angle of attack (60, 75, 90 degrees) and forward speed (0.5, 1, 1.35, 1.7 m/s) on draft force of a thin blade is presented.  Chisel plow in this research was constructed in two furrows with a blade width of 3 cm and a maximum depth of 25 cm (the distance between two blades was 1 m).  Some changes were made in the chassis of the chisel plow in order to obtain different attack angle of the blade.  The experimental work was then complemented with a new theoretical model for predicting the blade force using dimensional analysis method.  The final expression for estimating the pull resistance is as a function of several soil engineering properties (soil bulk density, soil adhesion and cohesion coefficients), blade parameters (blade width and blade rake angle) and operational conditions (tillage depth and forward speed).  Finally constants of the model were computed based on obtained experimental data.  The proposed model properly estimated the draft force of a thin blade.  Results obtained in this study indicate the stronger influence of tillage depth on the pulling force of a thin soil-working blade compared to the penetration angle and forward velocity.  The average error for the vertical blade with depth of 20, 15 and 10 cm were obtained equal to 4.5%, 4% and 1.5%, respectively.   Keywords: tillage, thin blade, chisel plow, interaction force, dimensional analysi

Numerical Simulation of the Performance and Emission of a Diesel Engine with Diesel-biodiesel Mixture

IntroductionIncreasing industrialization, growing energy demand, limited reserves of fossil fuels, and increasing environmental pollution have jointly necessitated for exploration of a substitute for conventional liquid fuels. Vegetable oils can be used as alternatives to petroleum fuels for engine operation. These oils are mixtures of free-fatty acid molecules to contain carbon, hydrogen, and oxygen atoms. The ability to simulate the process of converting chemical energy to heat, energy users of computational fluid dynamics software in the design, analysis, and optimization of high-tech tools. Also, simulation saves time and reduces costs, workforce, and the space required.Materials and MethodsIn this research, a one-dimensional computational fluid dynamics solution with GT-Power software was used to simulate a four-cylinder, four-stroke, direct injection diesel engine to study the performance and exhaust emissions characteristics with different speeds and blends at full load. The engine speeds were chosen to be 1100 to 1400 rpm at an interval of 100 rpm. Also, fuel blends such as diesel (as a base), B5, and B10 biodiesel were selected for engine testing. To model a engine, we should have the dimensions of the engine, input air collection, output gases collection, the amount of sprinkled fuel, valves properties, combustion, and some of the estimates corresponding to the cylinder’s thermodynamic parameters when opening the output and input gate and to exchange the heat inside the cylinder as the input data. The model mainly consisted of an air cleaner, intake valve, exhaust valve, intake and exhaust port, injection nozzle, engine cylinder, and engine. Engine cylinder’s intake and exhaust ports are modeled geometrically with pipes. Before this investigation was carried out, a validation model for evaluation was done by experimental and simulation data. The validation results showed that the software model error is acceptable.Results and DiscussionThe engine performance and emissions were evaluated in terms of engine torque, specific fuel consumption, NOx, and CO emission at different engine speeds and fuels at full load. The results showed that with increasing the engine speeds, torque increased. On the other hand, the maximum engine torque for the diesel engine is slightly lower than the biodiesel-blended that increased by 4.4% because of the higher density and viscosity of biodiesel than diesel. Specific Fuel Consumption (SFC) is a measure of the fuel efficiency of any prime mover that burns fuel and produces rotation, or shaft, power. The results indicated that by increasing engine speeds, the SFC increased. A fuel with a lower heating value should be injected with more mass into the engine. This will increase the SFC. So, the maximum engine SFC for the diesel engine is more than the biodiesel-blended that decreased by 4.45% because of better fuel combustion and more power generation of biodiesel than diesel. The only nitrogen oxide that can be formed in an engine combustion temperature is nitrogen monoxide (NO). This pollutant factor can be converted to nitrogen dioxide (NO2) over the time of exhaust gas. The results showed that with increasing the engine speeds, the NOX emissions decrease steadily and then increases, which is due to the high temperature in the cylinder. The viscosity and density of fuels have an effect on NOX emission, and because of the larger droplets of the fuel, it released NOX. The highest NOx emissions belong B10 biodiesel in 1400 rpm, due to the high oxygen content of this fuel and the lowest NOx emissions belong B10 biodiesel in 1300 rpm, due to the low density of the fuel compared to diesel. CO is a colorless and odorless gas, whose even very low concentrations are dangerous for humans and animals. The results showed that with increasing the engine speeds, the CO emission decreased and the minimum CO emission for diesel engine is more than the biodiesel-blended that decreased by 37.61% because of excess oxygen availability and complete combustion in biodiesel than diesel.ConclusionThe results of this study showed that the B10 blend in high engine speeds, generally had the best performance and emissions characteristics among the three fuels used in this study. Also, this investigation will assist in the development of WCO biodiesel as a viable sustainable fuel source through the use of a CFD model, optimized engine configuration, and technical report

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Nettle ash as a low cost adsorbent for the removal of nickel and cadmium from wastewater

This study was focused on nettle ash as an alternative adsorbent for the removal of nickel (II) and cadmium (II) from wastewater. Batch experiments were conducted to determine the factors affecting adsorption of nickel (II) and cadmium (II). The adsorption process is affected by various parameters such as contact time, solution pH and adsorbent dose. The optimum pH required for maximum adsorption was found to be 6. The experimental data were tested using Langmuir, Freundlich and Tempkin equations. The data were fitted well to the Langmuir isotherm with monolayer adsorption capacity of 192.3 and 142.8 mg/g for nickel and cadmium, respectively. The adsorption kinetics were best described by the pseudo second order model. The cost of removal is expected to be quite low, as the adsorbent is cheap and easily available in large quantities. The present study showed that nettle ash was capable of removing nickel and cadmium ions from aqueous solution

Construction of a Seed Pod Husker and Evaluating with Soybean in Laboratory Scale

Introduction Nowadays, due to growth and development of the husbandry and its worthiness in providing human basic needs, affecting parameters such as costs, efficiency and fuel consumption is significantly important. So, increasing the efficiency of threshing machine could lead us to huge savings in energy. However using the conventional drums and concaves have some problems such as damaging  seeds due to impact, complicated manufacturing technology and spending a lot of energy in separating process. Therefore in order to overcome above mentioned problems especially energy consumption, a new seed pod husker based on rubbing was designed, fabricated and tested in this research. Materials and Methods Practical tests of this device were carried out on soybean which was harvested in a farm of Babolsar city. The experimental design was simple randomized complete design with three replications. The rotational speed of rollers and distance between rollers varied in three levels of 110, 170, and 210 rpm and 7, 8, and 9 mm for soybean.  The measured parameters consisted of efficiency, separation and loss. For designing the seed pod husker, the required electric motor power and the torque for separating seeds from its pods were calculated. After reviewing the physical and mechanical characteristic of some seed pod crops specially, soybean, a seed pod husker was designed in SOLIDWORKS 2013 software. In order to facilitate seeds separation from the pod, it was preferred to use the right-round and left-round Archimedes screw on the rollers. According to the preliminary evaluations, it was considered to use a speed range of 110 to 210 rpm; it was because of that the speed lower than 110 rpm was not able to open pods and the speed higher than 210 rpm caused hyper movements of pods. Analysis of variance (ANOVA) and mean comparisons and interaction between the parameters were performed using the SPSS 22 software. Results and Discussion The results indicated that the rollers were acceptable and sticking of pods were not seen. Results indicated that the efficiency of this device was increased with increasing the rotational speed and then was decreased. Increasing the rotational speed was led to increase separation. It is because of this fact that the performance of the husker’s component will be more powerful and crops suffer bigger impacts. The chart of device loss had a relatively upward slope. It could be due to a tougher collision between the seeds and the rollers. Increasing the roller distance, first decreased the efficiency of soybean and then increased that. The results indicated that separation efficiency decreased by increasing the distance. The reason for that was due to unavailable necessary force to separate the seed and pod. As the roller distance increased, the total losses of the device also increased. The reason for this was likely increasing in the movement of the seeds. Conclusions The results of practical tests and qualitative observations showed that the device had sufficient resistance against the maximum torque produced by the crop. Influence of rotational speed of rollers and rollers clearance on the efficiency, separation and loss were significant for new fabricated seed pod husker (p < 0.01). The capacity of the machine for soybean was 28.506 (kg hr-1). To achieve maximum efficiency, maximum separation and minimum loss for soybean, authors suggest using (9mm-170rpm), (7mm-210rpm) and (9mm-110rpm) compounds, respectively. Eventually, it is suggested to evaluate this machine for other seed pod crops and for other parameters such as germination percentage, electric conductivity and ergonomic issues such as noise and machine vibration. Of course, it is recommended to survey the impact of length of husking roller, shaft rotation method and thread types on measurement parameters

Design and Development of a Warning System for Seed Blockage in a One Row Grain Drill

Introduction The use of new technology in planters is one of the most important factors in the advancement of agricultural science. In the present study, an electronic warning system has been designed and implemented to prevent large seeds from falling from the fall pipe into the ground groove. In this study, three types of corn, bean and soybean seeds have been used, using two laser and microwave sensors. Viewing and comparison of the two sensors and their performance in two conditions of medium and high sensitivity in both laboratory and field conditions were conducted. In this case, the differences between the two sensors in different sensitivities have been evaluated and compared. The performance of the sensors in seed count has also been studied and compared. According to the results obtained in both cases, the sensors performance was acceptable, and especially in the maximum sensitivity of the sensors, they were able to handle well the clogs created in different situations (clogging down or above the fall pipe or emptying the seed tank). Detect and alert in a timely manner. Also, the count of seeds in all three seed types was recorded with high accuracy compared to the actual number. Materials and Methods Three types of coarse seeds (corn, beans and soybeans) as well as two types of sensors (laser and microwave) with two levels of medium sensitivity and high sensitivity were used for the experiments. Laser sensors are one of the most precise instrumentation and industrial automation tools that use laser light to detect objects or even precise distances. The function of the microwave sensor is that the high frequency waves are transmitted when the power supply is connected. These waves are reflected back to the module receiver if they hit objects. The open waves in the module are multiplied by the frequency of transmission by the mixer and a low-output (IF) signal is generated. The output frequency is equal to the difference between the frequency of the transmitted and reflected waves caused by the Doppler effect. Based on this frequency, the presence of a moving object and its speed are detected. Experiments were carried out at both laboratory and field levels and in both moderate and high sensitivity modes using variable resistance mounted on the controller. The equivalent distance for each seed test is 100 meters, so twice for each seed in the laboratory and field level for each of the laser and microwave sensors in both high and medium sensitivity modes. In this system, in case of falling pipe clogging due to seed accumulation or mud under the falling pipe or other factors, an alert system (warning beep), along with the corresponding LED light, indicates a problem in the seed fall system and the operator alerts paying attention to the LED light (green or red) will detect the problem. Results and Discussion The results indicated that by installing a variable resistance inside the circuit, different sensors can be created in the sensors. Increasing the sensitivity of the sensor as much as possible can cause higher the efficiency of the sensor. In the two cases of medium and high resistance, sensors work with medium and high sensitivity. It works since both modes have been tested and the results have been satisfactory. The accuracy of counting and seed detection accuracy between two laser sensors and microwave sensors in two medium and high sensitivity modes were calculated and evaluated. The experiments in the laboratory showed that the difference in the number of seed count by laser sensor compared to the actual number in maize seed at medium and high sensitivity were 87.4% and 94.3%, respectively, in bean seeds 89.1% and 94.2%, respectively. And in soybean seed were 89.4% and 92.3%, respectively. Conclusions The developed embedded system can successfully check and announce the instantaneous state of three types of grain tested (corn, beans and soybeans) in the seed delivery tube of a hand single-row planter with visual cues (on or off LED lights) and audible signals (on or off the alarm), whenever there is a grain flow or no grain flow. Likewise, the developed system can show the blockage at the end of the seed delivery tube with visual indications of the green and red lights on or off and the alarm sound described in detail. These warnings are indications of a fall pipe failure or lack of grain flow in the grain measuring mechanism toward the opening groove and then into the ground. This type of detection alerts the operator in a timely manner by monitoring the status of the grains in the measuring system and ensuring that the grains are located in the ground

Global, regional, and national incidence and mortality burden of non-COVID-19 lower respiratory infections and aetiologies, 1990–2021 : a systematic analysis from the Global Burden of Disease Study 2021

Background Lower respiratory infections (LRIs) are a major global contributor to morbidity and mortality. In 2020–21, non-pharmaceutical interventions associated with the COVID-19 pandemic reduced not only the transmission of SARS-CoV-2, but also the transmission of other LRI pathogens. Tracking LRI incidence and mortality, as well as the pathogens responsible, can guide health-system responses and funding priorities to reduce future burden. We present estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 of the burden of non-COVID-19 LRIs and corresponding aetiologies from 1990 to 2021, inclusive of pandemic effects on the incidence and mortality of select respiratory viruses, globally, regionally, and for 204 countries and territories. Methods We estimated mortality, incidence, and aetiology attribution for LRI, defined by the GBD as pneumonia or bronchiolitis, not inclusive of COVID-19. We analysed 26 259 site-years of mortality data using the Cause of Death Ensemble model to estimate LRI mortality rates. We analysed all available age-specific and sex-specific data sources, including published literature identified by a systematic review, as well as household surveys, hospital admissions, health insurance claims, and LRI mortality estimates, to generate internally consistent estimates of incidence and prevalence using DisMod-MR 2.1. For aetiology estimation, we analysed multiple causes of death, vital registration, hospital discharge, microbial laboratory, and literature data using a network analysis model to produce the proportion of LRI deaths and episodes attributable to the following pathogens: Acinetobacter baumannii, Chlamydia spp, Enterobacter spp, Escherichia coli, fungi, group B streptococcus, Haemophilus influenzae, influenza viruses, Klebsiella pneumoniae, Legionella spp, Mycoplasma spp, polymicrobial infections, Pseudomonas aeruginosa, respiratory syncytial virus (RSV), Staphylococcus aureus, Streptococcus pneumoniae, and other viruses (ie, the aggregate of all viruses studied except influenza and RSV), as well as a residual category of other bacterial pathogens. Findings Globally, in 2021, we estimated 344 million (95% uncertainty interval [UI] 325–364) incident episodes of LRI, or 4350 episodes (4120–4610) per 100 000 population, and 2·18 million deaths (1·98–2·36), or 27·7 deaths (25·1–29·9) per 100 000. 502 000 deaths (406 000–611 000) were in children younger than 5 years, among which 254 000 deaths (197 000–320 000) occurred in countries with a low Socio-demographic Index. Of the 18 modelled pathogen categories in 2021, S pneumoniae was responsible for the highest proportions of LRI episodes and deaths, with an estimated 97·9 million (92·1–104·0) episodes and 505 000 deaths (454 000–555 000) globally. The pathogens responsible for the second and third highest episode counts globally were other viral aetiologies (46·4 million [43·6–49·3] episodes) and Mycoplasma spp (25·3 million [23·5–27·2]), while those responsible for the second and third highest death counts were S aureus (424 000 [380 000–459 000]) and K pneumoniae (176 000 [158 000–194 000]). From 1990 to 2019, the global all-age non-COVID-19 LRI mortality rate declined by 41·7% (35·9–46·9), from 56·5 deaths (51·3–61·9) to 32·9 deaths (29·9–35·4) per 100 000. From 2019 to 2021, during the COVID-19 pandemic and implementation of associated non-pharmaceutical interventions, we estimated a 16·0% (13·1–18·6) decline in the global all-age non-COVID-19 LRI mortality rate, largely accounted for by a 71·8% (63·8–78·9) decline in the number of influenza deaths and a 66·7% (56·6–75·3) decline in the number of RSV deaths. Interpretation Substantial progress has been made in reducing LRI mortality, but the burden remains high, especially in low-income and middle-income countries. During the COVID-19 pandemic, with its associated non-pharmaceutical interventions, global incident LRI cases and mortality attributable to influenza and RSV declined substantially. Expanding access to health-care services and vaccines, including S pneumoniae, H influenzae type B, and novel RSV vaccines, along with new low-cost interventions against S aureus, could mitigate the LRI burden and prevent transmission of LRI-causing pathogens. Funding Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care (UK)

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

BackgroundAccurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. MethodsTo estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. FindingsDuring the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. InterpretationFertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world. FundingBill & Melinda Gates Foundation