Labour Incomes in India: A Comparison of Two National Household Surveys

The COVID-19 pandemic created a need for high-frequency employment and income data. Policy-makers and researchers of developing countries typically have not had access to such data. In India, a new private high-frequency panel dataset has recently emerged as the dataset of choice for analysis of the economic impact of COVID-19. This is the Consumer Pyramids Household Survey (CPHS) conducted by the Centre for Monitoring the Indian Economy (CMIE). But the CPHS has also been criticised for being inadequately representative nationally by missing poor and vulnerable households in its sample. We examine the comparability of monthly labour income estimates for the pre-pandemic year (2018–19) for CPHS and the official Periodic Labour Force Survey (PLFS). Across different methods and assumptions, as well as rural/urban locations, CPHS mean monthly labour earnings are anywhere between 5 percent and 50 percent higher than corresponding PLFS estimates. In addition to the sampling concerns raised in the literature, we point to differences in the way employment and income are captured in the two surveys as possible causes of these differences. While CPHS estimates are always higher, it should also be emphasised that the two surveys agree on some stylised facts regarding the Indian workforce. An individual earning ₹50,000 per month lies in the top 5 percent of the income distribution in India as per both surveys. Second, both PLFS and CPHS show that half the Indian workforce earns below the recommended National Minimum Wage. Supplementary Information The online version contains supplementary material available at 10.1007/s41027-023-00427-8.

A systematic review of the incidence, management and prognosis of new-onset autoimmune connective tissue diseases after COVID-19.

A literature review on new-onset autoimmune connective tissue diseases (ACTDs) following COVID-19 is lacking. We evaluated potential associations between COVID-19 and the development of new-onset ACTDs. The "population" was adults with disease terms for ACTDs, including systemic lupus erythematosus (SLE), Sjogren's syndrome, systemic sclerosis (SSc), idiopathic inflammatory myositis (IIM), anti-synthetase syndrome, mixed CTD and undifferentiated CTD, and "intervention" as COVID-19 and related terms. Databases were searched for English-language articles published until September 2022. We identified 2236 articles with 28 ultimately included. Of the 28 included patients, 64.3% were female, with a mean age was 51.1 years. The USA reported the most cases (9/28). ACTD diagnoses comprised: 11 (39.3%) IIM (including four dermatomyositis); 7 (25%) SLE; four (14.3%) anti-synthetase syndrome; four (14.3%) SSc; two (7.1%) other ACTD (one lupus/MCTD overlap). Of eight, four (14.3%) patients (including that with lupus/MCTD) had lupus nephritis. The average time from COVID-19 to ACTD diagnosis was 23.7 days. A third of patients were admitted to critical care, one for treatment of haemophagocytic lymphohistiocytosis in SLE (14 sessions of plasmapheresis, rituximab and intravenous corticosteroids) and nine due to COVID-19. 80% of patients went into remission of ACTD following treatment, while three (10%) patients died-one due to macrophage activation syndrome with anti-synthetase syndrome and two from unreported causes. Our results suggest a potential association between COVID-19 and new-onset ACTDs, notably in young females, reflecting more comprehensive CTD epidemiology. The most common diagnosis in our cohort was IIM. The aetiology and mechanisms by which ACTDs emerge following COVID-19 remain unknown and require further research.

The infection risks of JAK inhibition.

INTRODUCTION: Janus Kinase inhibitors (JAKi) have shown to be highly effective in the treatment of immune-mediated inflammatory diseases. As with all immunomodulatory therapies, careful assessment of any treatment-associated infection risk is essential to inform clinical decision-making. AREAS COVERED: We summarize current literature on infection rates among the licensed JAKi using published phase II/III trial results, post-licensing and registry data. EXPERT OPINION: licensed JAKi show increased risk of infection across the class compared to placebo, most commonly affecting respiratory and urinary tracts, nasopharynx and skin. This risk is dose-dependent. Risks are similar at licensed JAKi doses to that seen with biologic therapies. The risk is compounded by other risk factors for infection, such as age and steroid co-prescription. Herpes zoster reactivation is more common with JAKi compared to other targeted immune modulation, making screening for varicella exposure and vaccination in appropriate cohorts an advisable strategy. Crucially, these small risk increases must be balanced against the known harms (including infection) of uncontrolled autoimmune disease. JAKi are a safe and potentially transformative treatment when used for appropriately selected patients.

T-cell cellular stress and reticulocyte signatures, but not loss of naïve T lymphocytes, characterize severe COVID-19 in older adults.

In children and younger adults up to 39 years of age, SARS-CoV-2 usually elicits mild symptoms that resemble the common cold. Disease severity increases with age starting at 30 and reaches astounding mortality rates that are ~330 fold higher in persons above 85 years of age compared to those 18-39 years old. To understand age-specific immune pathobiology of COVID-19, we have analyzed soluble mediators, cellular phenotypes, and transcriptome from over 80 COVID-19 patients of varying ages and disease severity, carefully controlling for age as a variable. We found that reticulocyte numbers and peripheral blood transcriptional signatures robustly correlated with disease severity. By contrast, decreased numbers and proportion of naïve T-cells, reported previously as a COVID-19 severity risk factor, were found to be general features of aging and not of COVID-19 severity, as they readily occurred in older participants experiencing only mild or no disease at all. Single-cell transcriptional signatures across age and severity groups showed that severe but not moderate/mild COVID-19 causes cell stress response in different T-cell populations, and some of that stress was unique to old severe participants, suggesting that in severe disease of older adults, these defenders of the organism may be disabled from performing immune protection. These findings shed new light on interactions between age and disease severity in COVID-19.

A sentiment and content analysis of tweets on monkeypox stigma among the LGBTQ+ community: A cue to risk communication plan.

Background: The stigma associated with monkeypox (mpox) may prevent people from following recommended guidelines. Using a "model of stigma communication," this study maps and determines the mpox stigma on Twitter among LGBTQ+ (Lesbian, gay, bisexual, transgender, queer and more) community. Methods: The tweets that contained the terms '#monkeypox', '#MPVS', '#stigma', and '#LGBTQ+' and were published between May 01, 2022 and Sept 07, 2022 were extracted. For sentiment analysis, the VADER, Text Blob, and Flair analysers were implemented. This study evaluated the dynamics of stigma communication based on the "model of stigma communication". A total of 70,832 tweets were extracted, from which 66,387 tweets were passed to the sentiment analyser and 3100 tweets were randomly selected for manual coding. Consolidated Criteria for Reporting Qualitative Research (COREQ) criteria was adopted to report this study. Findings: This research provided insight on the cause, communication, and patterns of mpox stigma in the LGBTQ+ community. In the community, stigmatisation was influenced by the group's labelling as the source of monkeypox. Some users believed that mpox resembled previously observed diseases such as HIV/AIDS, and COVID-19. Despite officials and media outlets disseminating information about preventing mpox and stigmatisation, a number of individuals failed to comply. The LGBTQ+ community faced peril in the form of violence due to escalating stigma. Misinformation and misinterpretation spread further stigmatisation. Interpretation: This study indicates that authorities must address misinformation, stigmatization of the LGBTQ+ community, and the absence of a comprehensive risk-communication plan to improve the system. The effects of stigmatization on the vulnerable population must be handled in conjunction with a well-developed risk communication plan, without jeopardizing their wellbeing.

Consumers' Online Purchasing Intentions Post COVID-19: Evidence from Lebanon and the Kingdom of Bahrain

The future of consumers' online shopping trends post COVID-19 remains among the contemporary topics that necessitate further explorations. The aim of this research is to explore the intention of Lebanese and Bahraini consumers to shop online in the post pandemic era. This study extends the technology acceptance model that has exhibited prominent results when it comes of online purchasing. An online survey was addressed to consumers in Lebanon and the Kingdom of Bahrain to collect the data. More precisely, a total of 778 responses equally divided between the two countries was collected. Following the analysis of the data, it was found that both Lebanese and Bahraini shoppers demonstrate variations in the positive evidence associated with the elements of the technology acceptance model, except the perceived usefulness positive impact on consumers' intention toward online shopping where no significant impact was shown in both countries. Contactless payment modes have no significant impact on attitudes in both countries contrary to their positive impacts on the intention toward online shopping in both countries. The use of social media and price consciousness also have variations in the positive evidence linked to consumers attitudes in both countries. Finally, both the use of social media and price consciousness reveal differences in the level of negative association with consumers' intention toward online shopping in Lebanon and the Kingdom of Bahrain.

Chapter 8 - Recent applications of nanomedicine in lung disease

Lung diseases include a wide spectrum of illnesses, such as asthma, COPD (chronic obstructive pulmonary disease), pneumonia, tuberculosis, lung cancers, and the recent COVID-19 pandemic, and have been a huge threat to human health and life. However, the treatment and diagnosis of various lung diseases are challenging. Among the several treatment strategies and diagnostic techniques, the adverse effect to chemotherapy in cancers, multidrug resistance in tuberculosis, side effects, toxicity, poor drug delivery, and metabolism require the development of novel and promising alternative treatments. Nanotechnology provides a promising tool for the development of innovative treatment overcoming many drug challenges. Nanotechnology being widely studied in medicinal field has given rise to the interdisciplinary nanomedicine field allowing fundamental changes in the diagnosis, treatment, and prevention of disease. Lungs provide a good target organ for drug delivery via an aerosol inhalation mode. Lungs provide a large surface area for local drug action and systemic drug absorption and hence nanomedicines have been a boon in treating many of the lung diseases without leading to any side effects or toxicity. The present chapter aims to review nanoparticles-based drug delivery systems studied over the last decade as therapeutic agents in lung diseases.

T-cell cellular stress and reticulocyte signatures, but not loss of naive T lymphocytes, characterize severe COVID-19 in older adults (preprint)

In children and younger adults up to 39 years of age, SARS-CoV-2 usually elicits mild symptoms that resemble the common cold. Disease severity increases with age starting at 30 and reaches astounding mortality rates that are ~330 fold higher in persons above 85 years of age compared to those 18-39 years old. To understand age-specific immune pathobiology of COVID-19 we have analyzed soluble mediators, cellular phenotypes, and transcriptome from over 80 COVID-19 patients of varying ages and disease severity, carefully controlling for age as a variable. We found that reticulocyte numbers and peripheral blood transcriptional signatures robustly correlated with disease severity. By contrast, decreased numbers and proportion of naive T-cells, reported previously as a COVID-19 severity risk factor, were found to be general features of aging and not of COVID-19 severity, as they readily occurred in older participants experiencing only mild or no disease at all. Single-cell transcriptional signatures across age and severity groups showed that severe but not moderate/mild COVID-19 causes cell stress response in different T-cell populations, and some of that stress was unique to old severe participants, suggesting that in severe disease of older adults, these defenders of the organism may be disabled from performing immune protection. These findings shed new light on interactions between age and disease severity in COVID-19.

A Case-Control Study on Severity of Covid Infection in Alcohol-Dependent Individuals in a Tertiary Care Hospital in South India

BACKGROUND. In the Indian population, it is estimated that 34-42% of adults have been the users of alcohol in their lifetime. coronavirus disease (COVID-19), undoubtedly the greatest public health catastrophe of our times, has been making a universal concern throughout the world over the past few months and is throwing up several challenges for us in numerous ways. AIM OF THE STUDY:To assess the impact of Covid 19 infection in alcohol-dependent individuals METHODS: This case-control study was conducted in the year October-2021 to January 2022 in the psychiatrySRM Medical College Hospital and Research Centre, Kaatankulathur, Tamilnadu, India. A total of 200 patients are selected for the study. 100 cases with alcohol dependence syndrome & 100 healthy controls without alcoholic usage. In case as well controls COVID positivity was either confirmed with RT-PCR (or) CT severity score(or) by clinical evaluation. Severity of the COVID infection were assessed by, CT severity score. RESULT(S): The proportion of participants with COVID infection was significantly more in the controls than in the Alcohol-dependent patients (P-value < 0.05).The duration of stay was higher in the control group (80.6 %) than the cases (66.6%) with a P value of less than 0.05.Though the oxygen requirement was more in the control group than in the cases the difference was not statistically significant. CONCLUSION(S): The risk of covid infections was higher in the controls than in Alcohol-dependent cases. Copyright © 2022, Anka Publishers. All rights reserved.

Systematic literature review informing the 2022 EULAR recommendations for screening and prophylaxis of chronic and opportunistic infections in adults with autoimmune inflammatory rheumatic diseases.

OBJECTIVE: To conduct a systematic literature review (SLR) on the screening and prophylaxis of opportunistic and chronic infections in autoimmune inflammatory rheumatic diseases (AIIRD). METHODS: SLR (inception-12/2021) based on the following search domains: (1) infectious agents, (2) AIIRD, (3) immunosuppressives/immunomodulators used in rheumatology, (4) screening terms and (5) prophylaxis terms. Articles were retrieved having the terms from (1) AND (2) AND (3) plus terms from (4) OR(5). Databases searched: PubMed, Embase and Cochrane Library. EXCLUSION CRITERIA: studies on postoperative infections, paediatric AIIRD, COVID-19, vaccinations and non-Εnglish literature. Study quality was assessed with Newcastle-Ottawa scale for non-randomised controlled trials (RCTs), RoB-Cochrane for RCTs, AMSTAR2 for SLRs. RESULTS: From 5641 studies were retrieved, 568 full-text articles were assessed for eligibility, with 194 articles finally included. For tuberculosis, tuberculin skin test (TST) is affected by treatment with glucocorticoids and conventional synthetic disease modifying anti-rheumatic drugs (DMARDs) and its performance is inferior to interferon gamma release assay (IGRA). Agreement between TST and IGRA is moderate to low. For hepatitis B virus (HBV): risk of reactivation is increased in patients positive for hepatitis B surface antigen. Anti-HBcore positive patients are at low risk for reactivation but should be monitored periodically with liver function tests and/or HBV-viral load. Risk for Hepatitis C reactivation is existing but low in patients treated with biological DMARDs. For Pneumocystis jirovecii, prophylaxis treatment should be considered in patients treated with prednisolone ≥15-30 mg/day for >2-4 weeks. CONCLUSIONS: Different screening and prophylaxis approaches are described in the literature, partly determined by individual patient and disease characteristics.

The changing role of innovation for crisis management in times of COVID-19: An integrative literature review

Since the outbreak of the COVID-19 pandemic, countries have concentrated on developing policies that encourage the creation of more innovative products and services in response to the global health emergency. Effective collaboration, communication, and Open Innovation (OI) among government entities, education and research institutions, and the private sector have been critical to each country's overall effectiveness during the economic crisis. The objective of this paper is to examine the relationship between innovation and COVID-19 critically to have a better understanding of future research and practice developments. A systematic evaluation was conducted, analyzing papers on innovation and the COVID-19 pandemic. A total of 218 studies were analyzed to determine the essential research directions in this domain. Our suggested framework is made of aggregate components, which include technology adaption, sustainable development, healthcare, and sustainable economic performance. These components form the basis for the identification of emerging research hotspots in the field of COVID and innovation, as well as frame the COVID-19 issue as an opportunity to raise awareness about the crucial role of innovation in business and society at large.

Factors Affecting Post Pandemic Channel Preference of Young Consumers In India

The impact of the Covid 19 pandemic on the retail sector and its adaptive consumer behavior has been strongly felt. Researchers worldwide have studied consumers' behavioral adaptation in phases of lockdown to understand patterns and identify trends that may continue in the post-pandemic world. In order to categorize research specific to buying behavior as a response to the pandemic, the present paper carries out a bibliometric analysis to identify research trends. Further, an empirical study among young Indian shoppers is carried out to identify the factors that affect their online and offline buying decisions. The present study used exploratory factor analysis to identify factors affecting online and offline buying at the pilot study stage. Researchers proposed the models and framed the hypothesis. Dataset using a structured questionnaire was tested using structural equation modeling and path analysis. The result indicated financial impact has no mediation effect on user experience. The partial mediation effect of delivery experience for online channel preference was established. For offline channel preference, discount and in-store deals have a full mediation effect on hedonic and user experience. Indian youth preferred the online channel for utilitarian products and repeat buying whereas offline was preferred for in-store discounts.

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report.

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate.

Breastfeeding and Contraceptive Methods in Women With Severe Acute Respiratory Syndrome Coronavirus- 2 (SARS-COV-2) Infection in Peripartum Period

Objective: This study aimed to assess the exclusive breastfeeding and contraceptive methods among women delivering within 1-week of a positive test for severe acute respiratory syndrome coronavirus- 2 (SARS-CoV-2) infection. Materials and methods: In this study, 106 women with SARS-CoV-2 infection who were either asymptomatic or had mild disease were included. They were admitted for maternity care at a tertiary center between May to September 2020. The data was collected during their hospital stay and subsequently by telephonic or in-person interviews at 4-6 weeks and 8-10 weeks postpartum for contraceptive use, breastfeeding and use of facemask and hand-hygiene. Results: Sixty-three (59.4%) women had vaginal delivery and 43 (40.6%) required cesarean-section. Only one of the 98 newborns who were tested for SARS-CoV-2 turned out positive. Initiation of breastfeeding was delayed by an average of three days due to preparing the Reverse transcription polymerase chain reaction (RT-PCR) report. Exclusive breastfeeding was practiced by 69% and mixed feeding by 26%.Pre breastfeeding hand hygiene and facemask use declined after discharge (100% to 53.75% at 8-10 weeks postpartum). Out of 106, 86 (81%) women used no contraception at 8-10 weeks postpartum, continued with post-placental-IUD in 8/106 (7.5%) and tubal-sterilization during cesarean in 8/106 (7.5%) cases. Only 4/106 (4%) adopted alternative methods like barrier contraception. Conclusion: The practice of exclusive breastfeeding remains unchanged among women who suffered from SARS-CoV-2 infection in the peripartum period while uptake of postpartum contraception was minimal except for the women who opted for long term contraceptive methods in the immediate postpartum period.

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson's Disease Affected by COVID-19: A Narrative Review.

Background and Motivation: Parkinson's disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID-19 causes the ML systems to become severely non-linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well-explained ML paradigms. Deep neural networks are powerful learning machines that generalize non-linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID-19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID-19 framework. We study the hypothesis that PD in the presence of COVID-19 can cause more harm to the heart and brain than in non-COVID-19 conditions. COVID-19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID-19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID-19 lesions, office and laboratory arterial atherosclerotic image-based biomarkers, and medicine usage for the PD patients for the design of DL point-based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID-19 environment and this was also verified. DL architectures like long short-term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID-19. Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID-19.

Analysing the Legal Rights of the Climate Refugees during COVID-19 Pandemic in India: Challenges to International Law

The COVID-19 pandemic came as a shock for the entire world, and it is still ongoing, consequentially hindering mankind from following their normal lives. The novel coronavirus was first reported from the Wuhan city, Hubei province of China, and WHO was aware of the same on 31 December 2019. The entire world came to still for months to prevent the virus from spreading. In India, there was a massive displacement of over 200 million migrant workers due to the sudden lockdown in the country. During this turmoil, the authors feel that the rights of the climate refugees were overlooked. This article will examine the health rights of the climate refugees during this pandemic with a specific focus on the climate refugees staying in the Sundarban Delta during this pandemic. The authors have undertaken a theoretical and qualitative data analysis to analyse the same. The study?s findings showcase the vulnerability due to the negligible health facilities available for them. In this regard, the article would identify the lacuna in the legal framework for protecting the rights of the climate refugees and will argue for integrating and interpreting International Law and Human Rights Law to at least cover the health rights of the climate refugees during pandemics. The authors suggest that the rights of climate change refugees should not be ignored.

A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review.

Background and Motivation: Cardiovascular disease (CVD) causes the highest mortality globally. With escalating healthcare costs, early non-invasive CVD risk assessment is vital. Conventional methods have shown poor performance compared to more recent and fast-evolving Artificial Intelligence (AI) methods. The proposed study reviews the three most recent paradigms for CVD risk assessment, namely multiclass, multi-label, and ensemble-based methods in (i) office-based and (ii) stress-test laboratories. Methods: A total of 265 CVD-based studies were selected using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model. Due to its popularity and recent development, the study analyzed the above three paradigms using machine learning (ML) frameworks. We review comprehensively these three methods using attributes, such as architecture, applications, pro-and-cons, scientific validation, clinical evaluation, and AI risk-of-bias (RoB) in the CVD framework. These ML techniques were then extended under mobile and cloud-based infrastructure. Findings: Most popular biomarkers used were office-based, laboratory-based, image-based phenotypes, and medication usage. Surrogate carotid scanning for coronary artery risk prediction had shown promising results. Ground truth (GT) selection for AI-based training along with scientific and clinical validation is very important for CVD stratification to avoid RoB. It was observed that the most popular classification paradigm is multiclass followed by the ensemble, and multi-label. The use of deep learning techniques in CVD risk stratification is in a very early stage of development. Mobile and cloud-based AI technologies are more likely to be the future. Conclusions: AI-based methods for CVD risk assessment are most promising and successful. Choice of GT is most vital in AI-based models to prevent the RoB. The amalgamation of image-based strategies with conventional risk factors provides the highest stability when using the three CVD paradigms in non-cloud and cloud-based frameworks.