Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Gudalur Spectral Target Detection (GST-D): A New Benchmark Dataset and Engineered Material Target Detection in Multi-Platform Remote Sensing Data

Target detection in remote sensing imagery, mapping of sparsely distributed materials, has vital applications in defense security and surveillance, mineral exploration, agriculture, environmental monitoring, etc. The detection probability and the quality of retrievals are functions of various parameters of the sensor, platform, target–background dynamics, targets’ spectral contrast, and atmospheric influence. Generally, target detection in remote sensing imagery has been approached using various statistical detection algorithms with an assumption of linearity in the image formation process. Knowledge on the image acquisition geometry, and spectral features and their stability across different imaging platforms is vital for designing a spectral target detection system. We carried out an integrated target detection experiment for the detection of various artificial target materials. As part of this work, we acquired a benchmark multi-platform hyperspectral and multispectral remote sensing dataset named as ‘Gudalur Spectral Target Detection (GST-D)’ dataset. Positioning artificial targets on different surface backgrounds, we acquired remote sensing data by terrestrial, airborne, and space-borne sensors on 20th March 2018. Various statistical and subspace detection algorithms were applied on the benchmark dataset for the detection of targets, considering the different sources of reference target spectra, background, and the spectral continuity across the platforms. We validated the detection results using the receiver operation curve (ROC) for different cases of detection algorithms and imaging platforms. Results indicate, for some combinations of algorithms and imaging platforms, consistent detection of specific material targets with a detection rate of about 80% at a false alarm rate between 10−2 to 10−3. Target detection in satellite imagery using reference target spectra from airborne hyperspectral imagery match closely with the satellite imagery derived reference spectra. The ground-based in-situ reference spectra offer a quantifiable detection in airborne or satellite imagery. However, ground-based hyperspectral imagery has also provided an equivalent target detection in the airborne and satellite imagery paving the way for rapid acquisition of reference target spectra. The benchmark dataset generated in this work is a valuable resourcefor addressing intriguing questions in target detection using hyperspectral imagery from a realistic landscape perspective

Theory of potentiostatic current transients for coupled catalytic reaction at random corrugated fractal electrode

We developed a mathematical model for the first order homogeneous catalytic chemical reaction coupled with an electron transfer (EC′) on a rough working electrode. Results are obtained for the various roughness models of electrode corrugations, viz., (i) roughness as an exact periodic function, (ii) roughness as a random function with known statistical properties, and (iii) roughness as a random function with statistical self-affine fractality over a finite range of length scales. Method of Green's function is used in the formulation to obtain second-order perturbation (in roughness profile) expressions for the concentration, the local current density and the current transients. A general operator structure between these quantities and arbitrary roughness profile is emphasized. The statistically averaged (randomly rough) electrode response is obtained by an ensemble averaging over all possible surface configurations. An elegant mathematical formula between the average electrochemical current transient and surface structure factor or power-spectrum of roughness is obtained. This formula is used to obtain an explicit equation for the current on an approximately self-affine (or realistic) fractal electrode with a limited range of length scales of irregularities. This description of realistic fractal is obtained by cutoff power law power-spectrum of roughness. The realistic fractal power-spectrum consists of four physical characteristics, viz., the fractal dimension (D_H), lower (ℓ) and upper (L) cutoff length scales of fractality and a proportionality factor (μ), which is related to the topothesy or strength of fractality. Numerical calculations are performed on final results to understand the effect of catalytic reaction and fractal morphological characteristics on potentiostatic current transients

Theory of partial diffusion-limited interfacial transfer/reaction on realistic fractals

The problems of diffusive transport to and across an irregular interface are of general interest, but are considered a difficult class of problems for theoretical understanding. In this paper we discuss theory of partial diffusion-limited interfacial transfer/reaction on a realistic fractal interface. The surface irregularity is modeled as a random surface fractal, which is characterized by statistically isotropic self-affine fractals on limited length scales. The power spectrum of roughness of such surface fractal is approximated in terms of power law function for the intermediate wave-numbers (or spatial frequency components in roughness). This description of roughness consists of four fractal morphological characteristic features. Results unravel the connection between the flux/current, surface morphology and its kinetics following a step of surface activity (like a potential step experiment). We show the dependence of reaction flux/current on various fractal roughness characteristics related to power spectrum, and discuss the dynamic crossover of charge transfer controlled regime to fractal morphology controlled diffusion regime to classical inverse square root of time regime

Theory of anomalous diffusive reaction rates on realistic self-affine fractals

We developed a theoretical method based on limited scale power law form of the interfacial roughness power spectrum and the solution of diffusion equation under the diffusion-limited boundary conditions on rough interfaces. This theoretical method is useful for the analysis of diffusion-limited flux/current to limited scale self-affine random fractal interfaces and is compared with experimentally measured electrochemical current for nano- and micron scales of roughness. The new result explains experimental findings of the temporal scale invariance as well as deviation from this in transition, short, and long time regions. Our result show flux/current transients in terms of three dominant fractal morphological parameters, that is, fractal dimension, lower cutoff length scale of fractality, and topothesy, for the limited length scales of fractality. More broadly, these results are applicable for all time scales and roughness factors

Synthesis of soluble phthalocyanines and study of their aggregation behavior in solution

1029-1033Aryloxy substituted soluble phthalocyanine (pc) and its metal complexes (MPcX4,X=4-ethylphenoxy, M=2H, Cu, Ni, Zn, Fe, Co) have been synthesized and characterized by elemental analysis, 1H NMR, UV-visible and IR spectroscopy. Degree of association in toluene solution has been measured by molecular weight determination using vapour pressure osmometry. Association and its relative order have also been established in these complexes by UV-visible spectral studies

Diffusion-controlled potentiostatic current transients on realistic fractal electrodes

We analyze the problem of diffusion to irregular electrode whose irregularity is characterized as statistically isotropic self-affine fractals on limited length scales. The power spectrum of a surface fractal is approximated in terms of a white noise for low wave-numbers and a power law function for the intermediate wave-numbers. This power spectrum has four fractal morphological parameters. They are fractal dimension (D_H), lower (ℓ) and upper (L) cutoff length scales of fractality, and the proportionality factor (μ) related to topothesy or strength of roughness. Our explicit results for the potentiostatic current transient and its limiting laws are presented. These limiting laws are: (i) short time expansion, (ii) long time expansion and (iii) intermediate time expansion. The intermediate time limiting law for the current transient captures the classical anomalous power law behavior which is usually observed in experimental data. Our results show that the scaling exponent of anomalous region is dependent on D_H as well as on ℓ and μ. These results also unravel the connection between the crossover times and the roughness characteristics of realistic fractal surfaces. We demonstrate an excellent comparison between the theoretical results and the experimental potentiostatic current transient. Finally, we also show the localization of current density on a rough corrugated electrode where surface corrugation is taken as a band-limited Weierstrass–Mandelbrot random function