Working Age Group Research Articles

Use, characteristics and influence of lay consultation networks on treatment-seeking decisions in slums of Nigeria: a cross-sectional survey

ObjectivesTo describe the use, characteristics and influence of lay consultants on treatment-seeking decisions of adults in slums of Nigeria.DesignCross-sectional survey using a pre-piloted questionnaire.SettingsTwo slum communities in Ibadan city, Nigeria.Participants480...

Deep learning–based detection of diabetic macular edema using optical coherence tomography and fundus images

Diabetic macular edema (DME) is an important cause of visual impairment in the working-age group. Deep learning methods have been developed to detect DME from two-dimensional retinal images and also from optical coherence tomography (OCT) images. The performances of these algorithms vary and often create doubt regarding their clinical utility. In resource-constrained health-care systems, these algorithms may play an important role in determining referral and treatment. The survey provides a diversified overview of macular edema detection methods, including cutting-edge research, with the objective of providing pertinent information to research groups, health-care professionals, and diabetic patients about the applications of deep learning in retinal image detection and classification process. Electronic databases such as PubMed, IEEE Explore, BioMed, and Google Scholar were searched from inception to March 31, 2022, and the reference lists of published papers were also searched. The study followed the preferred reporting items for systematic review and meta-analysis (PRISMA) reporting guidelines. Examination of various deep learning models and their exhibition regarding precision, epochs, their capacity to detect anomalies for less training data, concepts, and challenges that go deep into the applications were analyzed. A total of 53 studies were included that evaluated the performance of deep learning models in a total of 1,414,169°CT volumes, B-scans, patients, and 472,328 fundus images. The overall area under the receiver operating characteristic curve (AUROC) was 0.9727. The overall sensitivity for detecting DME using OCT images was 96% (95% confidence interval [CI]: 0.94–0.98). The overall sensitivity for detecting DME using fundus images was 94% (95% CI: 0.90–0.96).

Changes in socioeconomic resources and mental health after the second COVID-19 wave (2020–2021): a longitudinal study in Switzerland

BackgroundDuring the 2020/2021 winter, the labour market was under the impact of the COVID-19 pandemic. Changes in socioeconomic resources during this period could have influenced individual mental health. This association may have been mitigated or exacerbated by subjective risk perceptions, such as perceived risk of getting infected with SARS-CoV-2 or perception of the national economic situation. Therefore, we aimed to determine if changes in financial resources and employment situation during and after the second COVID-19 wave were prospectively associated with depression, anxiety and stress, and whether perceptions of the national economic situation and of the risk of getting infected modified this association.MethodsOne thousand seven hundred fifty nine participants from a nation-wide population-based eCohort in Switzerland were followed between November 2020 and September 2021. Financial resources and employment status were assessed twice (Nov2020–Mar2021, May–Jul 2021). Mental health was assessed after the second measurement of financial resources and employment status, using the Depression, Anxiety and Stress Scale (DASS-21). We modelled DASS-21 scores with linear regression, adjusting for demographics, health status, social relationships and changes in workload, and tested interactions with subjective risk perceptions.ResultsWe observed scores above thresholds for normal levels for 16% (95%CI = 15–18) of participants for depression, 8% (95%CI = 7–10) for anxiety, and 10% (95%CI = 9–12) for stress. Compared to continuously comfortable or sufficient financial resources, continuously precarious or insufficient resources were associated with worse scores for all outcomes. Increased financial resources were associated with higher anxiety. In the working-age group, shifting from full to part-time employment was associated with higher stress and anxiety. Perceiving the Swiss economic situation as worrisome was associated with higher anxiety in participants who lost financial resources or had continuously precarious or insufficient resources.ConclusionThis study confirms the association of economic stressors and mental health during the COVID-19 pandemic and highlights the exacerbating role of subjective risk perception on this association.

Association between WHO First-Step Analgesic Use and Risk of Breast Cancer in Women of Working Age.

We assessed the association between breast cancer and analgesic use in women of a specific working-age group. The Korean National Health Insurance Service-National Sample Cohort database (KNHIS-NSC) data were analyzed. We calculated hazard ratios (HRs) with 95% confidence intervals (CIs) for patients' cancer risk based on whether the women participated in economic activity (PEA or not PEA (NPEA) groups) and analgesic use. Additionally, breast cancer incidence variations by age group, and PEA or NPEAs, health behavior, Charlson Comorbidity Index, and analgesic use were evaluated. The PEA group had a higher cancer risk than the NPEA group (HR = 1.542, 95% CI: 1.345-1.768, p < 0.001). Breast cancer risk was high in the PEA, high income, and no history of exercise groups, but significantly reduced in the regular-use-of-analgesics group. Notably, the working age group of 40~49 years, within the PEA group, had the highest HR of breast cancer development (HR = 1.700, 95% CI = 1.361-2.124, p < 0.001); whereas regular analgesic use in those aged 25~39 years decreased breast cancer risk (HR = 0.611, 95% CI = 0.427-0.875, p < 0.05). In conclusion, our results suggest that individuals at a high-risk of comorbidity may benefit from regular use of analgesics, which may prove to be a useful strategy for breast cancer prevention in the Young-aged group.

Creation and Destruction of Jobs in Urban Labour Market: Role of Gender, Caste and Religion in India.

This study analyses labour market transitions from job to jobless or jobless to job by using Periodic Labour Force Survey (PLFS)of India in urban labour market by applying first-order Markov process in constructing transition matrices and panel logit regression model using personal level information from the PLFS in India for 2019-20. While education is assumed to be the most important factor influencing the process of transitions in the labour market, the circumstance variables like gender, caste and religion are expected to have significant effects on it in a country like India. The empirical results show a significant difference in labour market transitions between men and women. The movement of workers between job status was very low and the major part of the transition occurred in the form of job losses for each type of workers both among men and women and also among all working age group and young age group.

What are the individual and joint impacts of key meteorological factors on the risk of unintentional injuries? A case-crossover study of over 147,800 cases from a sentinel-based surveillance system

Meteorological factors are a critical component of a sustainable society, especially in the context of climate change. Although studies have linked key meteorological factors to unintentional injuries, their joint effects on the occurrence of unintentional injuries remain unclear. We conducted a case-crossover study using a sentinel-based injury database in a mega-city in China and identified the vulnerable subgroups by demographic and injury characteristics. We observed significantly increased cumulative risk associated with each interquartile range increase in temperature (excess risk [ER] range=4.78–7.05%) and precipitation (ER range=1.00–2.09%) from lag0–1 day onwards. Conversely, there was a significantly decreased risk with relative humidity (RH) from lag0–2 days onwards (ER range=-2.83 to -2.10%). The link between meteorological factors and unintentional injuries was worthy of particular attention for the working-age groups, males, and those with fall-related injuries, road-related injuries, or fractures. Climate conditions with high wind speed (WS) and temperature combined with low precipitation and RH exhibited the greatest ER. The ER of high WS and RH, combined with low precipitation and temperature, was also significant. These key factors may jointly contribute to unintentional injury, which is important for evidence-based climate mitigation and injury prevention.

Formation of labor resources in rural areas methodological issues

The formation of working-age population groups in terms of modern labor market requirements in the conditions of the market economy lays the groundwork for an easy solution to their employment problems. These problems cover the rural economy. There fore, the article explores the options of using justified methodological approaches and reliable forecast data in the formation of labor resources. Purpose–to systematically and comprehensively study the characteristics of the formation of labor resources in order to solve the employment problem in rural areas Methodology-the study used the method of comparative analysis and synthesis. Research results-the use of opportunities of economic-mathematical modeling is of great importance in solving the methodological problems of the formation of labor resources in rural areas.

THE SOCIAL COST OF MODIFIABLE RISK FACTORS IN SINGAPORE

Abstract Close to half of total disease burdens are attributable to modifiable risk factors, indicating that many illnesses are preventable by modifying behaviours such as increasing physical activity levels or maintaining a healthy diet. This study measures the social costs attributable to modifiable risks in Singapore, one of the most rapidly ageing populations in the world. Measuring the social cost of modifiable risk factors can help public health policymakers prioritise public health programmes and allocate resources. Our study builds on the comparative risk assessment framework from the Global Burden of Disease study. We used a prevalence-based cost-of-illness approach to estimate the social cost attributable to modifiable risk factors. We included healthcare costs from inpatient hospitalisation and productivity losses from absenteeism and premature mortality. Our results found that metabolic risks had the highest social cost of S$2.20 billion in 2019, followed by lifestyle risks of S$1.98 billion and substance risks of S$1.56 billion. Across the risk factors, the social costs were largely driven by productivity losses, heavily skewed towards the older working-age group. For metabolic risks, approximately 80% of the total cost (S$1.82 billion) was from those aged above 45 years old. This study provides evidence of the high social cost of modifiable risks and highlights the importance of developing holistic public health promotion programmes. Our findings suggest that implementing effective population-based programmes targeting multiple modifiable risks would have a strong potential to manage rising disease burdens and healthcare costs, especially with an ageing population.

A Systematic Literature Review on Diabetic Retinopathy Using an Artificial Intelligence Approach

Diabetic retinopathy occurs due to long-term diabetes with changing blood glucose levels and has become the most common cause of vision loss worldwide. It has become a severe problem among the working-age group that needs to be solved early to avoid vision loss in the future. Artificial intelligence-based technologies have been utilized to detect and grade diabetic retinopathy at the initial level. Early detection allows for proper treatment and, as a result, eyesight complications can be avoided. The in-depth analysis now details the various methods for diagnosing diabetic retinopathy using blood vessels, microaneurysms, exudates, macula, optic discs, and hemorrhages. In most trials, fundus images of the retina are used, which are taken using a fundus camera. This survey discusses the basics of diabetes, its prevalence, complications, and artificial intelligence approaches to deal with the early detection and classification of diabetic retinopathy. The research also discusses artificial intelligence-based techniques such as machine learning and deep learning. New research fields such as transfer learning using generative adversarial networks, domain adaptation, multitask learning, and explainable artificial intelligence in diabetic retinopathy are also considered. A list of existing datasets, screening systems, performance measurements, biomarkers in diabetic retinopathy, potential issues, and challenges faced in ophthalmology, followed by the future scope conclusion, is discussed. To the author, no other literature has analyzed recent state-of-the-art techniques considering the PRISMA approach and artificial intelligence as the core.

Deep feature extraction of retinal images for diabetic retinopathy enhanced diagnosis

Most people of working age groups globally around are affected by diabetic retinopathy, which is the most common cause of preventable vision impairment. Recent studies have improved our comprehension of the need for more effective and affordable methods of identifying, managing, diagnosing, and treating retinal disease in clinical eye care practice. The development of computer-aided diagnosis tools must consider the significance of diabetic retinopathy screening programmes and the challenge of obtaining a valid early diagnosis of diabetic retinopathy at an affordable price. Retinal image analysis using computer-aided disease diagnosis may make it easier to screen the population for diabetes mellitus on a mass scale and may also assist physicians to make better use of their time. The creation of image processing models using big data analysis may run into many technical challenges, including the visualization analysis needed by image processing technologies, the semantic expression, and storage of large image samples, the complexity of the algorithms needed for feature extraction, recognition, and prediction analysis using big data, as well as the time and memory requirements.

ESLO: Enhanced sea lion optimization based bi‐directional CNN‐RNN for accurate detection of diabetic retinopathy

SummaryDiabetic retinopathy is considered to be one of the major causes of eye disorder which commonly occurs in working age group of people worldwide. Deficiency of proper screening and early diagnosing leads the diabetic patients completely affected by vision loss. Therefore, an effective detection of diabetic retinopathy before visual symptoms reduces the impact of visual impairment. In recent times, numerous research methods are adopted by researchers in this domain to automatically detect the existence of eye diseases; however, they provide only limited performances like less accuracy with high training error. Therefore, in this article, an attention based bi‐directional convolutional neural network‐recurrent neural network model along with enhanced sea lion optimization (ABCDM‐ESLO) technique is proposed for accurate detection and classification of healthy and unhealthy diabetic retinopathy cases based on the severity levels. In this, seven different datasets are used, analyzed, and classified into five categories (i.e., normal, mild, moderate, severe, and proliferative). Moreover, the performance metrics such as accuracy, sensitivity, specificity, and f‐score are evaluated with respect to severity levels thereby determining the efficiency of the proposed method. The performance of the proposed technique is examined by comparing it with other existing methods. The proposed method achieves 99.2% of detection accuracy, 94% of sensitivity, 96% of specificity, and 92.75% of f‐score. This reveals that the proposed ABCDM‐ESLO technique performs well and classifies than other existing methods in terms of different performance metrics.

Geraniin ameliorates streptozotocin-induced diabetic retinopathy in rats via modulating retinal inflammation and oxidative stress

BackgroundDiabetic retinopathy (DR) is the major complication of diabetes, which causes acquired vision loss in the working-age group population. ObjectiveHere, we planned to address the therapeutic roles of geraniin against the streptozotocin (STZ)-challenged DR in rats MethodologyThe DR was induced in the animals by 60 mg/kg of STZ, and then treated with 25 mg/kg of geraniin for 60 days. Later, bodyweight, food consumption, and blood glucose levels were investigated. The levels of antioxidants, MMP-9, MCP-1, and VEGF, and inflammatory cytokine status were measured using marker-specific kits. The morphometric study was conducted to assess the retinal thickness. The pancreatic tissues were analyzed microscopically. ResultsGeraniin reduced the blood glucose (270.36 ± 81 mg/dL), hemoglobin, and enhanced bodyweight (261.93 ± 72 g)in the DR rats. The antioxidant levels in the STZ-challenged DR rats were substantially improved by geraniin. Geraniin also decreased inflammatory cytokines, MCP-I, MMP-9, and VEGF levels and enhanced the retinal thickness. A histological study demonstrated that geraniin reduced the pancreatic islet cell damage in STZ-induced DR rats. ConclusionOur outcomes witnessed that geraniin reduced retinal inflammation and oxidative stress in the STZ-induced DR rats.

SCRUB TYPHUS DISEASE OUTBREAK AT CHEURAL VILLAGE, LAWNGTLAI DISTRICT, MIZORAM, NORTH-EAST INDIA

Scrub typhus, which is one of the rickettsial diseases, is an acute, febrile illness in men caused by the pathogen, 18 a gram-negative bacterium Orientia tsutsugamushi from the bite of infected mite. Outbreaks of scrub typhus have been reported from various parts of North, South, and Eastern India. There was a report of two unfortunate death cases from Cheural village due to scrub typhus at Lawngtlai district hospital. While, multiple cases, having symptoms like scrub typhus illness were also reported by health officials of the residents of Cheural village, Lawngtlai District, Mizoram. Among the 242 person tested, 80 (33.05%) person were found reactive with Weil felix PROGEN OXK at 1:160 titre value. Maximum numbers of cases were observed among the working age group 20-60 years. Among the different occupational groups, farmers were the most affected as more than 90% of the villagers were involved in forest farming. The five captured rodents’ sera were also tested with Weil felix. All of the captured rodent sera were reactive with one or more antigen. Mites (chigger) were also collected from the rodent samples and the chigger index was found to be 19.2. This study indicated that scrub typhus and other rickettsial diseases were responsible for the outbreak. The extremely high chigger index with reactivity rate reactivity rate of Weil felix with sera of captured rodents strongly indicated the household transmission of scrub typhus and other rickettsial diseases in the outbreak village.

The Demographic Dividend As A Pathway To Development: The Role of Fertility and Education in Sub-Saharan Africa. A Narrative Review

Purpose: Sub-Saharan African countries are experiencing rapid population growth. This is essential in achieving the Demographic Dividend. Age structure, fertility and education play a key role in the achievement of the Demographic Dividend. Although gains from age structure are crucial, its gains are not automatic. However, the inter-relatedness of fertility and education makes a reduction in fertility a cause and effect on investments in education.&#x0D; Methodology: This narrative review looks at studies discussing the Demographic Dividend from a development theory point of view. It is an attempt to explain how different countries within Sub-Saharan Africa are faring due to the inter-play between fertility and education.&#x0D; Findings: The results highlight how the Demographic Dividend is really an Educational Dividend. It also shows a negative correlation between education and fertility across regions and time. The political environment with emphasis on good governance plays a key role in harnessing the Demographic Dividend. Aside this, a fertility decline alone could worsen the existing economic conditions if it is not in tandem with higher education rates among young adults. This is in line with Ester Boserup’s view of seeing population as a resource.&#x0D; Unique contribution to theory, practice and policy (recommendation): A conducive political environment attracts investments and creates room for entrepreneurship and job creation which are necessary to be able to harness the Demographic Dividend. There’s the need to however, look at the definition of working age group and conditions necessary to promote entrepreneurship. &#x0D; &#x0D;

Will Demographic Changes Affect Monetary Policy with Interest Rate Shocks in Indonesia?

Changes in the demographic structure and its impact on the economy are becoming interesting issues in almost all countries in the world, including Indonesia. Until 2030, the working age group dominates almost 60 percent of the total population in Indonesia. This phenomenon is a valuable asset which should be used optimally. Moderate adjustment of interest rate policy is an effort applied by Bank Indonesia to maximize the access to credit and public savings. Therefore, this study aims to determine the effect of demographic aspects and the real sector on the effectiveness of monetary policy in the presence of interest rate shocks. This study employed time series data with a time period of 1987Q1 – 2020Q4 in Indonesia. The analysis was performed by using time varying parameter-vector autoregressive (TVP-VAR) and fully modified-ordinary least square (FM-OLS). The results revealed that the population and the elderly population aspects had significant positive effects on the monetary policy, while the variable of productive age and the number of dependence aspects has significant negative effects. The relationship between the real sector and the monetary policy has a different relationship, such as a positive relationship between the savings and technology variables and the domestic credit variable which has a significant negative relationship with the monetary policy.

The 2009-2014 economic crisis and deaths by suicide in Portugal: time series analysis

Abstract Introduction Population health, including mental health, is influenced by its socioeconomic context. After the 2008 global economic crisis, studies found contradicting results: some showed an increased risk for self-harm and suicidal behavior, while others found the opposite association. To the best of our knowledge, there is no research in Portugal on the subject. Thus, our aim was to estimate the impact of the Portuguese economic crisis of 2009-2014 on the death rate by suicide and self-inflicted injury in Portugal. Methods A retrospective ecological study with an interrupted time series analysis of deaths by suicide and self-inflicted injury (data from the National Statistics Institute) in mainland Portugal, in 2003-2014, was performed. Resident population data was also retrieved from the National Statistics Institute. Binomial negative generalized linear models were used to compare rates and trends before (2003-2008) and during (2009-2014) the economic crisis. All rates were stratified and adjusted for seasonality. Results The economic crisis was associated with 13% a step increase in the death rate due to suicide and self-inflicted injury, with unemployment playing a significant mediating role, being negatively associated to the outcome. Differences between groups exist, with males, working-age groups and the North and Centre regions being the most impacted, globally. Conclusions Economic downturns pose risks for suicidal behavior. Unemployment may play a role in this association. Employment protection schemes can prevent this impact, so urgent action is needed to prevent economic crisis leading to additional suicides, especially in the context of the COVID-19 pandemic and the economic crisis it caused. Key messages • The Portuguese economic crisis of 2009-2014 was associated with an increased death rate due to suicide, especially in males, working-age groups and the North and Centre regions. • Unemployment may play a role in this association, and active labour market programmes can prevent the negative impacts of economic crisis leading to additional suicides.

Spatial disparity and structural inequality in disability patterns across Tianjin municipality: A multiple deprivation perspective

Reducing the spatial disparities and structural inequalities faced by disabled people is a global challenge in both developed and developing countries that requires an understanding of disability-driven deprivation. This study aims to develop and validate a conceptual framework for analysing the structural inequality and spatial disparity of disability-related deprivation. To achieve this goal, an Index of Disability-Related Multiple Deprivation (IDMD) based on six specific domains, including employment, education, marital status, health, services and barrier-free environments, is proposed. The IDMD was calculated at the sub-district level within the Tianjin municipality using aggregated registration information from the Tianjin Disability Database in 2020. Principal component analysis (PCA) was used to assign the weight of each indicator of IDMD. Moran I and LISA analysis were used to quantify the spatial disparity of IDMD across the municipality. Multi-Scale Geographically Weighted Regression (MGWR) was used to model the structural factors shaping the spatial disparity of disability-related deprivation in terms of gender, age, and disability types. Three key findings have been generated as follows. The spatial variability of IDMD revealed significant urban-rural disparity across the municipality, highlighting the difficulties faced by vulnerable and disadvantaged disabled people in rural areas. Men, working age groups and those with intellectual disability contributed most to the structural inequalities of IDMD. Thirdly, the location of greatest deprivation varied for different groups; working age groups faced the highest levels of deprivation in the urban centre, males faced the most deprivation in the urban fringe and those with intellectual, limb, visual, speech or mental disabilities were most deprived in rural areas. These findings reflect the complexity of structural factors affecting disability-related deprivation at the municipality scale. This study points to the need for informed, targeted welfare facilities planning and management strategies to improve spatial equity and social justice for disabled people.

A case-control study of occupational noise exposure induced high-frequency hearing loss and the risk of hypertension

Objective: To investigate the relationship between high frequency hearing loss caused by occupational noise and the risk of hypertension. Methods: In March 2020, a case-control study was conducted. All noise exposed workers who participated in occupational health examination in Wuxi City in 2019 were selected as the study subjects (95432 cases in total) . The hypertension group was defined as the case group, and the normotensive group was defined as the control group. According to the hearing threshold, they were divided into the non high frequency hearing loss group (<40 dB) and the high frequency hearing loss group (≥ 40 dB) . Univariate statistical method and binary logistic regression were used to evaluate the relationship between high-frequency hearing loss and hypertension risk. Stratified analysis was used to compare the risk of hypertension among workers with high-frequency hearing loss of different ages and length of service. Results: There were significant differences in gender, age, length of service, enterprise scale, economic type and high-frequency hearing loss between control group and hypertension group (P<0.05) . Binary logistic regression analysis showed that after adjusting for gender, age, length of service, enterprise scale and economic type, the risk of hypertension in the high-frequency hearing loss group was still increased (OR=1.062, 95%CI: 1.007~1.121, P=0.027) . The risk of hypertension in high-frequency hearing loss patients was higher than that in non high-frequency hearing loss patients in 20-39 years old and 40-59 years old age groups (OR=1.536, 95%CI: 1.353~1.743; OR=1.179, 95%CI: 1.111~1.250; P<0.05) . The risk of hypertension in high-frequency hearing loss patients in <5years, 5-9years, 10-14 years, 15-19 years and ≥20 years working age groups were higher than that in non high-frequency hearing loss groups (OR=1.926, 95%CI=1.007-1.121; OR=1.635, 95%CI=1.478-1.810; OR=1.312, 95%CI=1.167-1.474; OR=1.445, 95%CI=1.238-1.686; OR=1.235, 95%CI=1.043-1.463; P<0.05) . Conclusion: There is a certain relationship between high-frequency hearing loss caused by occupational noise and the risk of hypertension, and the risk of hypertension is different among high-frequency hearing loss patients of different ages and working years.

COVID-19 in India: Epidemiological reflections from initial 170 million consecutive test results.

The Indian Council of Medical Research (ICMR) played a crucial role in streamlining testing and diagnosis, formulating guidelines, and devising management strategies during the COVID-19 pandemic. Additionally, ICMR designed and developed a comprehensive data management tool for collecting testing data in a standardized format from all laboratories across the country. The current report is a retrospective analysis of the testing data generated by the ICMR. The study's main objectives are to understand the probability of a person testing negative based on their age after an initial positive test and to assess the varied impact and duration of the disease in people of different age groups and genders. Anonymized data on the testing for COVID were analyzed. The P-to-P is the longest time interval between two consecutive positive tests for a patient without any negative test in between the positives. P-to-Plast is the time between the first positive and last positive test, as opposed to P-to-P, here we are looking at the first and last positive tests that might or might not be consecutive. P-to-N intervals is the time between the first positive and first negative test of a patient. India conducted 170,914,170 tests during the study-period (until December 29, 2020). After excluding invalid test results and duplicates, there were 11,101,603 (6.5%) positive and 156,542,352 (93.5%) negative test-results performed upon 150,086,257 unique individuals. A negative-report following a positive-test was available in 12.69%. Nearly three-fourths of the cases (78.29%) belonged to the working-age group (18-60 years). The proportion of patients >50 years old has risen from 26.06 to 35.03%, with a steep rise beyond September 2020. Gender-ratio among the positives was 1.73:1 which was neutral in neonates < 7-days (age). The gender ratio was skewed in-favor-of males in the initial months with a reverse trend thereafter and with increasing age of patients. The mean P-to-P, P-to-Plast, and P-to-N durations were 12.7 + 4.3, 13.3 + 4.6, and 14.2 + 4.9 days for individuals with P-to-P duration of 1-4 weeks. The probability of testing negative was 82 & 85% at 14 & 21 days after the first-positive-test respectively with no gender bias. The current study has highlighted some vital aspects of COVID-19 epidemiology in India. This study will add to the current understanding of the virus in the absence of pre- existing information on the novel virus and the disease per se.

Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019

Health-care needs change throughout the life course. It is thus crucial to assess whether health systems provide access to quality health care for all ages. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019), we measured the Healthcare Access and Quality (HAQ) Index overall and for select age groups in 204 locations from 1990 to 2019. We distinguished the overall HAQ Index (ages 0-74 years) from scores for select age groups: the young (ages 0-14 years), working (ages 15-64 years), and post-working (ages 65-74 years) groups. For GBD 2019, HAQ Index construction methods were updated to use the arithmetic mean of scaled mortality-to-incidence ratios (MIRs) and risk-standardised death rates (RSDRs) for 32 causes of death that should not occur in the presence of timely, quality health care. Across locations and years, MIRs and RSDRs were scaled from 0 (worst) to 100 (best) separately, putting the HAQ Index on a different relative scale for each age group. We estimated absolute convergence for each group on the basis of whether the HAQ Index grew faster in absolute terms between 1990 and 2019 in countries with lower 1990 HAQ Index scores than countries with higher 1990 HAQ Index scores and by Socio-demographic Index (SDI) quintile. SDI is a summary metric of overall development. Between 1990 and 2019, the HAQ Index increased overall (by 19·6 points, 95% uncertainty interval 17·9-21·3), as well as among the young (22·5, 19·9-24·7), working (17·2, 15·2-19·1), and post-working (15·1, 13·2-17·0) age groups. Large differences in HAQ Index scores were present across SDI levels in 2019, with the overall index ranging from 30·7 (28·6-33·0) on average in low-SDI countries to 83·4 (82·4-84·3) on average in high-SDI countries. Similarly large ranges between low-SDI and high-SDI countries, respectively, were estimated in the HAQ Index for the young (40·4-89·0), working (33·8-82·8), and post-working (30·4-79·1) groups. Absolute convergence in HAQ Index was estimated in the young group only. In contrast, divergence was estimated among the working and post-working groups, driven by slow progress in low-SDI countries. Although major gaps remain across levels of social and economic development, convergence in the young group is an encouraging sign of reduced disparities in health-care access and quality. However, divergence in the working and post-working groups indicates that health-care access and quality is lagging at lower levels of social and economic development. To meet the needs of ageing populations, health systems need to improve health-care access and quality for working-age adults and older populations while continuing to realise gains among the young. Bill & Melinda Gates Foundation.