Jim Crow in New York

More than 108,000 New Yorkers cannot vote because of a conviction in their past. Almost half of these disenfranchised citizens have completed their prison sentence and are living and working in the community

Understanding the Impacts of Mesosphere and Lower Thermosphere on Thermospheric Dynamics and Composition

The Earth’s Ionosphere and Thermosphere (IT) is a highly dynamic system persistently driven by variable forcings both from above (Solar EUV and the magnetosphere) and the lower atmosphere. The forcing from below accounts for the majority of the variability at low- and mid-latitude IT region during geomagnetic quiet times. The IT region is particularly sensitive to the composition, winds, and temperature of the Mesosphere and Lower Thermosphere (MLT) state. The goal of this dissertation is to help understand how the MLT region controls the upper atmosphere. This is achieved by using the IT model, Global Ionosphere Thermosphere Model (GITM) and altering its lower boundary (which is in the MLT) to allow a more accurate representation of the lower atmospheric physics within the model. At the beginning of this thesis, it is identified that recent solstitial observations of MLT atomic oxygen (O) from the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument show larger densities in the summer hemisphere than in the winter hemisphere. This is opposite to what has been previously known and specified in the IT models, and its cause is still under investigation. The first study focuses on understanding the influence of this latitudinal distribution by using a more realistic specification of MLT [O] from the Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM-X), in GITM. This study shows that despite being a minor species throughout the lower thermosphere, reversing the [O] distribution affects the pressure gradients, winds, temperature, and N2 in the lower thermosphere. These changes then map to higher altitudes through diffusive equilibrium, improving the agreement between GITM O/N2 and Global Ultraviolet Imager (GUVI) measurements. Secondly, the importance of MLT variations on the thermospheric and ionospheric semiannual variation (T-I SAO) is investigated. This is done by analyzing the sensitivity of T-I SAO in GITM to different lower boundary assumptions. This study reveals that the primary driver of T-I SAO is the thermospheric spoon mechanism, as a significant T-I SAO is reproduced in GITM without an SAO variation in the MLT. However, using a more realistic MLT [O] from WACCM-X produces an oppositely-phased T-I SAO, maximizing at solstices, disagreeing with the observations. Since the MLT [O] distribution is correct in WACCM-X, the results hint at incomplete specification/physics for lower thermospheric dynamics in GITM that can drive the transition of the SAO to its correct phase. These mechanisms warrant further investigation and may include stronger winter-to-summer winds, and lower thermospheric residual circulation. The goal of the last study is to examine the effects of spatially non-uniform turbulent mixing in the MLT on the IT system. This is achieved by introducing latitudinal variation in the eddy diffusion parameter (Kzz) in GITM. The results reveal larger spatial variability in O/N2 and TEC. However, the net effect is small (within 2-4%) on the globally averaged quantities and depends on the area of the turbulent patch. The results also show a different response between the summer and the winter IT region, with winter exhibiting larger changes. Overall, this thesis has highlighted some of the outstanding questions in the domain of lower atmosphere-IT coupling and have answered them through exhaustive comparisons of GITM simulations with different satellite observations, and extensive term analyses of the GITM equations, while laying out a framework for coupling of GITM with WACCM-X.PHDClimate and Space Sciences and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169766/1/garimam_1.pd

HF radar observations of a quasi‐biennial oscillation in midlatitude mesospheric winds

The equatorial quasi‐biennial oscillation (QBO) is known to be an important source of interannual variability in the middle‐ and high‐latitude stratosphere. The influence of the QBO on the stratospheric polar vortex in particular has been extensively studied. However, the impact of the QBO on the winds of the midlatitude mesosphere is much less clear. We have applied 13 years (2002–2014) of data from the Saskatoon Super Dual Auroral Radar Network HF radar to show that there is a strong QBO signature in the midlatitude mesospheric zonal winds during the late winter months. We find that the Saskatoon mesospheric winds are related to the winds of the equatorial QBO at 50 hPa such that the westerly mesospheric winds strengthen when QBO is easterly, and vice versa. We also consider the situation in the late winter Saskatoon stratosphere using the European Centre for Medium‐Range Weather Forecasts ERA‐Interim reanalysis data set. We find that the Saskatoon stratospheric winds between 7 hPa and 70 hPa weaken when the equatorial QBO at 50 hPa is easterly, and vice versa. We speculate that gravity wave filtering from the QBO‐modulated stratospheric winds and subsequent opposite momentum deposition in the mesosphere plays a major role in the appearance of the QBO signature in the late winter Saskatoon mesospheric winds, thereby coupling the equatorial stratosphere and the midlatitude mesosphere.Key PointsA significant mesospheric QBO signature is observed at Saskatoon using midlatitude SuperDARN HF radar during late winterSaskatoon MQBO signature is significantly correlated with equatorial QBOFiltering of gravity waves through Saskatoon stratospheric winds and opposite momentum deposition in the mesosphere leads to MQBOPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135660/1/jgrd53414.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/135660/2/jgrd53414_am.pd

Assessment of Essential Newborn Care Services in Secondary-level Facilities from Two Districts of India

India faces a formidable burden of neonatal deaths, and quality newborn care is essential for reducing the high neonatal mortality rate. We examined newborn care services, with a focus on essential newborn care (ENC) in two districts, one each from two states in India. Nagaur district in Rajasthan and Chhatarpur district in Madhya Pradesh were included. Six secondary-level facilities from the districts\u2500two district hospitals (DHs) and four community health centres (CHCs) were evaluated, where maximum institutional births within districts were taking place. The assessment included record review, facility observation, and competency assessment of service providers, using structured checklists and sets of questionnaire. The domains assessed for competency were: resuscitation, provision of warmth, breastfeeding, kangaroo mother care, and infection prevention. Our assessments showed that no inpatient care was being rendered at the CHCs while, at DHs, neonates with sepsis, asphyxia, and prematurity/low birthweight were managed. Newborn care corners existed within or adjacent to the labour room in all the facilities and were largely unutilized spaces in most of the facilities. Resuscitation bags and masks were available in four out of six facilities, with a predominant lack of masks of both sizes. Two CHCs in Chhatarpur did not have suction device. The average knowledge score amongst service providers in resuscitation was 76% and, in the remaining ENC domains, was 78%. The corresponding average skill scores were 24% and 34%, highlighting a huge contrast in knowledge and skill scores. This disparity was observed for all levels of providers assessed. While knowledge domain scores were largely satisfactory (>75%) for the majority of providers in domains of kangaroo mother care and breastfeeding, the scores were only moderately satisfactory (50-75%) for all other knowledge domains. The skill scores for all domains were predominantly non-satisfactory (<50%). The findings underpin the need for improving the existing ENC services by making newborn care corners functional and enhancing skills of service providers to reduce neonatal mortality rate in India

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

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