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The twenty-first century has brought in massive changes in the labour processes, employment relations and erosion of labour standards in all sectors—manufacturing, agriculture and service—of the world economy. COVID19 pandemic has brought centre-stage the feminist discourse on paid and unpaid work, visible and invisiblised work, officially recognised and officially bypassed/ignored work as well as women's contribution of care economy for the survival of humankind. At this juncture, this edited volume acquires a great significance as it not only connects the missing dots in the gendered labour markets but also makes a convincing case for an urgent need for fiscal expansion to ensure food and health security, protection of livelihoods and investment in human development in this unequal world. The book is divided into three parts: (1) macroeconomy and women's work, (2) women in the urban economy and regional diversity and (3) women in agriculture and allied occupations. © 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Objectives: A LSR is a systematic review that is continually updated, incorporating new evidence as it becomes available. They are conducted in research areas where new evidence is constantly emerging on diagnostic methods, treatments, and outcomes. The objective of this study was to understand the current application of LSRs across research areas. Method(s): Embase, MEDLINE, and the Cochrane Database of Systematic Reviews were searched to identify LSRs. Only the most recent update of a LSR was included. Data regarding the indication, intervention, methods, frequency of updates, and funding were extracted. Result(s): Of the 1,243 records identified, 126 LSRs were included for analysis. The first LSR was published in 2015, with a significant increase in the number of LSRs published starting in 2020, coinciding with the COVID-19 pandemic. The most common indication represented by LSRs was COVID-19 (72%), followed by oncology (10%). Other indications with LSRs included chronic pain, traumatic brain injury, and skin disorders, among others. While most oncology LSRs identified interventional randomized-controlled trials (RCTs) (85%), only 54% of COVID-19 LSRs were restricted to interventional studies, including a combination of RCTS and real-world observational studies. Oncology LSRs included common cancers such as prostate, renal, or multiple myeloma. Of the reviews that reported update frequency, 28% planned monthly, 12% yearly, and 12% weekly updates. Only 46% of LSRs were registered. The majority of LSRs were funded by government or research organizations. Objectives of LSRs varied, with most stating the need to maintain up-to-date databases;however, several studies used LSRs to facilitate network meta-analysis or mixed treatment comparisons. Conclusion(s): While LSRs were introduced over five years ago, their frequency increased during the COVID-19 pandemic. Apart from COVID-19, LSRs are commonly used in oncology settings. LSRs provide high-level, relevant, and up-to-date evidence, making them a useful tool for clinical and real-world research.Copyright © 2023
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This paper focuses on the pandemic's impact on women's participation in the economy. The author outlines the various barriers to the full and equal participation of women in the Indian economy such as the gender division of labour which requires women to shoulder the burden of unpaid domestic work, the occupational segregation of the labour market, gender-blind development policies, regressive social norms and patriarchal attitudes. The challenge facing women only increased with the pandemic which led to large numbers of women dropping out of the workforce. The author suggests that in the immediate future the State has a crucial role in redressing this injustice. In the longer term, she calls for rethinking the dominant models of development that pursue economic growth and rise in GDP as the panacea for all problems. Such models have given rise to the rampant exploitation of labour, among whom women are the most vulnerable. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.
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The atmospheric aerosols and air pollutants affect the earth's atmosphere, human health and climate system. Human-induced aerosols and air pollutants are the major causes of the deterioration of air quality. The COVID-19 lockdown restricted the movement of people and vehicles, stopped industrial and agricultural activities and may have impacts on the aerosols in the atmosphere. Spatio-temporal map of MODIS Terra AOD_550 nm, OMI Aura UVAI, Ozone, NO2, SO2 and AIRS CO during the lockdown illustrates the significant reduction in their concentration. During the lockdown, the North India shows a record reduction of over 20% in Aerosol Optical Depth and Aerosol Index values. A substantial decrease in AOD and AI was also observed in Eastern and Western parts of India. The average AOD value were reduced from 1.36 (2016–2019) to 1.09 (2020) over India during the lockdown. The satellite-retrieved aerosol variables over India recorded lowest AOD values on 29th March, 2020 (0.2566) and 21st April 2020 (0.2591). Similarly, air pollutants CO, NO2 and SO2 also significantly reduced in India. Despite all variables showing a reduction in concentration, Ozone recorded an increase in value during lockdown primarily over North and North-eastern parts of India. Western India recorded a substantial reduction in SO2 (47%) followed by Central India (31%). As pan India is considered, CO was reduced by 1%, NO2 reduced by 15.29% and SO2 was reduced by 26.82% during the lockdown period. This abrupt reduction in aerosol and air pollutants concentration over India was mainly due to the lockdown of COVID-19. © 2023, The Author(s), under exclusive licence to Korea Spatial Information Society.
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The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them. © 2023 the author(s), published by De Gruyter.
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Objectives: To describe and compare real-world outcomes for patients with mild-to-moderate COVID-19 at high risk for progression to severe COVID-19, treated with sotrovimab versus untreated. Method(s): Electronic health records from the National COVID Cohort Collaborative were used to identify US patients (aged >=12 years) diagnosed with COVID-19 (positive test or ICD-10: U07.1) in an ambulatory setting (26 May 2021-30 April 2022) who met Emergency Use Authorization high-risk criteria. Patients receiving the monoclonal antibody (mAb) sotrovimab within 10 days of diagnosis were assigned to the sotrovimab cohort with an index date on the day of infusion. Untreated patients (no evidence of early mAb treatment or prophylaxis mAb or oral antiviral treatment) were assigned to the untreated cohort with an imputed index date based on the time distribution between diagnosis and sotrovimab infusion for the sotrovimab cohort. The primary endpoint was hospitalization or death (both all-cause) within 29 days of index, reported as descriptive rates and adjusted (via inverse-probability-of-treatment weighting [IPTW]) odds ratios (OR) and 95% confidence intervals (CI). Result(s): Of nearly 2.9 million patients diagnosed with COVID-19 during the analysis time period, 4,992 met the criteria for the sotrovimab cohort and 541,325 were included in the untreated cohort. Patients in the sotrovimab cohort were older (60 versus 54 years), more likely to be male (40% versus 38%) and White (85% versus 75%), and met more EUA criteria (3 versus 2) versus the untreated cohort. The 29-day hospitalization or mortality rates were 3.5% (176/4,992) and 4.5% (24,163/541,325) in the sotrovimab and untreated cohorts respectively (unadjusted OR [95% CI]: 0.77 [0.67,0.90];p=0.001;IPTW-adjusted OR [95% CI]: 0.74 [0.61,0.91];p=0.004). Conclusion(s): Sotrovimab demonstrated clinical effectiveness in preventing severe outcomes (hospitalization, mortality) between 26 May 2021-30 April 2022, which included the Delta variant and early surge of Omicron BA.1/BA.2. Funding(s): GSK (Study 219020)Copyright © 2023
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This article analyses the IT sector in India, the impact of the COVID-19 crisis and transfer pricing issues in the IT sector. © 2022 IBFD.
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The government of India has launched a web portal to register and schedule appointments for COVID-19 vaccination. This paper illustrates an android app model through which people can get notified about available slots according to their filters (age-group, dose type, vaccine name, centers). The proposed app checks for available slots for every given time in the background. Users can schedule their appointment and also enable/disable notifications at any time in the app. The project is developed in android studio. The data source is API Setu, and for client side, Java, XML, and SQLite are used. Software Development Life Cycle model and testing methods are used during the development process. ER diagram, message sequence chart, and flow chart have been shown for database, some important functions, and development process, respectively. The project developed is highly efficient, lightweight, and user-friendly. © 2023 selection and editorial matter, Anshul Verma, Pradeepika Verma, Kiran Kumar Pattanaik and Lalit Garg;individual chapters, the contributors.
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The objective was to evaluate real-world effectiveness of sotrovimab, a monoclonal antibody (mAb) for the treatment of high-risk outpatients with COVID-19, in reducing the risk of mortality or hospitalization during the SARS-CoV-2 Delta and initial Omicron variant waves in the US. A retrospective analysis was conducted of de-identified, high-risk patients diagnosed with COVID-19 (index date) from 1 September 2021 to 28 February 2022 in the FAIR Health FH NPIC claims database. Patients were divided into 2 cohorts based on claimed procedural codes: treated with sotrovimab and not treated with any mAb (no mAb). Facility-reported mortality ("mortality"), all cause hospitalizations and intensive care unit (ICU) admissions <=30 days of index were identified. Multivariable logistic regression was conducted to estimate the risk of 30-day mortality or hospitalization, adjusting for demographic and clinical factors. Of the high-risk COVID-19 patients identified,13,140 were treated with sotrovimab and 1,283,284 received no mAb therapy. In the no mAb cohort, 0.59% died and 5.74% were hospitalized (of whom 30% in ICU). In the sotrovimab cohort, 0.08% died and 2.50% were hospitalized (of whom 15% in ICU). After adjusting for potential confounders, sotrovimab treatment was associated with 85% reduced odds of 30-day mortality (OR: 0.15, 95% CI: 0.08-0.31) and 61% reduced odds of 30-day hospitalization or mortality (OR: 0.39, 95% CI: 0.35-0.44) among high-risk COVID-19 patients. In this US real-world study of high-risk COVID-19 patients during the Delta and initial Omicron waves, treatment with sotrovimab was associated with reduced odds of mortality and hospitalization compared to no mAb treatment.
ABSTRACT
Background. Sotrovimab, a monoclonal antibody (mAb), received Emergency Use Authorization (EUA) for the treatment of high-risk outpatients with symptomatic COVID-19. The study objective was to evaluate real-world effectiveness of sotrovimab (500 mg intravenous) in reducing the risk of mortality or hospitalization during the SARS-CoV-2 Delta and initial Omicron variant waves in the US. Methods. A retrospective analysis was conducted of de-identified patients (pts) diagnosed with COVID-19 (ICD-10: U07.1) from 9/1/2021 to 2/28/2022 in the FAIR Health FH NPIC claims database. Pts were divided into 2 cohorts based on HCPCS codes: treated with sotrovimab and not treated with any mAb (no mAb). Pts meeting EUA high-risk criteria were identified via pre-specified ICD-10-CM diagnoses in records <= 24 months prior to their first COVID-19 diagnosis (index date). Facility-reported mortality (referred to as 'mortality'), all cause hospitalizations and intensive care unit (ICU) admissions within 30 days of index were identified. Chi-square test, ANOVA, or t-tests were performed to statistically compare cohorts at a 0.05 level of significance (2-sided). P-values were not adjusted for multiplicity. Multivariable logistic regression was conducted to estimate the risk of mortality or hospitalization within 30 days, adjusting for demographic and clinical factors. Results. Of the high-risk COVID-19 pts identified, 13,140 were treated with sotrovimab and 1,283,284 received no mAb therapy. Compared to the no mAb cohort, the sotrovimab cohort was older, had more baseline conditions, and were more likely to be female (all p < 0.0001). In the no mAb cohort, 0.59% died and 5.74% were hospitalized (of whom 30% in ICU). In the sotrovimab cohort, 0.08% died and 2.50% were hospitalized (of whom 15% in ICU). After adjusting for potential confounders, treatment with sotrovimab was associated with 83% reduced odds of 30-day mortality (OR: 0.17, 95% CI: 0.09-0.31) and 61% reduced odds of 30-day hospitalization or mortality (OR: 0.39, 95% CI: 0.35-0.43) among high-risk COVID-19 pts. Conclusion. In this US real-world observational study of high-risk COVID-19 pts during the Delta and initial Omicron waves, treatment with sotrovimab was associated with reduced odds of mortality and hospitalization compared to no mAb treatment.
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There is a vast unmet need for mental health care and support in the United States and globally. Although expanding specialty services is needed, this is neither sufficient nor necessary to comprehensively address the current and future demand. Traditional models of care which have focused on mental disorders, while useful for many, remain out of reach, unaffordable, and not timely for helping the vast majority of individuals in need of mental health support. There is a growing movement of community-based networks and organizations which aim to fill this need by harnessing existing community resources to promote mental health and prevent mental and substance use disorders. This paper describes our effort to derive a blue-print for an approach, which we call "Community Initiated Care (CIC)", building on these real-world experiences and the growing science on lay person delivered brief psychosocial interventions in community settings. CIC serves as a back-bone for training lay persons to support the mental health and well-being of others in their communities. CIC is envisioned as an equitable, efficient, safe, and timely form of contextualized support to promote mental health and prevent selfharm, mental health and substance use problems. CIC is not intended to replace clinical interventions;instead, we envisage the supportive encounter to use a person-centered approach to bolster existing positive coping skills, promote positive social engagement, reduce risk of future mental health problems, and encourage other forms of help seeking when appropriate. This article explores how our thinking is aligned with and responsive to the strategies and tactics of the Contextual Behavioral Science Task Force to promote programs that are multidimensional, process-based, prosocial, practical, and multi-level. Development, implementation, and evaluation of CIC will not only advance contextual behavioral science but also move society forward to more equitable mental health and well-being.
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The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, -19.27%) and Particulate Matter (PM 2.5, -23%) during LD (2020)from pre-LD (March-September months for the period 2017-2019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (March-May) and Kharif (June-September). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.
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Federated learning (FL) is a distributed machine learning technique that enables collaborative model training while avoiding explicit data sharing. The inherent privacy-preserving property of FL algorithms makes them especially attractive to the medical field. However, in case of heterogeneous client data distributions, standard FL methods are unstable and require intensive hyperparameter tuning to achieve optimal performance. Conventional hyperparameter optimization algorithms are impractical in real-world FL applications as they involve numerous training trials, which are often not affordable with limited compute budgets. In this work, we propose an efficient reinforcement learning (RL)-based federated hyperparameter optimization algorithm, termed Auto-FedRL, in which an online RL agent can dynamically adjust hyperparameters of each client based on the current training progress. Extensive experiments are conducted to investigate different search strategies and RL agents. The effectiveness of the proposed method is validated on a heterogeneous data split of the CIFAR-10 dataset as well as two real-world medical image segmentation datasets for COVID-19 lesion segmentation in chest CT and pancreas segmentation in abdominal CT. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Over last two decades, private higher education institutions have been making new inroads in the Indian education scenario. This phenomenon is marked by commodification of higher education and culture of capitation fee for admission in professional courses. This has raised major concerns with regard to affordability and equity in the higher education in India. Globally and in India, the discourse on commercialised higher education is polarised on the ground of inclusivity of aspiring students of the socio-culturally and economically marginalised sections on the one hand and opening the door of higher education for those who can pay ‘user fees’. Other philosophical questions are: Is higher education a marketable product or a public good that needs to be supported by the state funding? Does higher education merit state support or ‘user fee model’ is most efficient for crowding out? How to make higher education affordable and accessible to meritorious students, who have been historically neglected, through affirmative action so that higher education markets do not throw them out? How to deal with paradoxical situation where private sectors in professional educational institutions have a large number of vacant seats and aspiring meritorious students do not get admission due to inability to pay highly inflated fees? Relative decline in budgetary allocations for higher education since 1991 and falling government expenditure in higher education and its implications for economic development of the region have been an important area of research in India in the millennium focused on economic growth through expansion of knowledge economy. Augmenting expenditure on education as well as better utilisation of allocated funds is an essential component of the developmental strategy of the state to fulfil its long-term priorities of human development that are essential for economic growth. The COVID pandemic has brought into foreground these perennials and developing issues that reveal the fact that education has been treated as a privilege or a commodity rather than a fundamental right. The pandemic has heightened existing injustices-push out of a large number of students due to circular migration, exposing and deepening of the ‘digital divide’, and profiteering by private managements. Along with the students, the teachers are also bearing the brunt of contractualisation of their services, pressurised to adapt to new technologies in the absence of sufficient support, working without remuneration, and facing job loss. The onslaught of Information and Communication Technology (ICT)-based market forces raise serious concern for the access to the socioeconomically marginalised at the intersections of class, caste, ethnicity, physical and cognitive disabilities, location, and gender. The health emergency has made it mandatory for India to increase seats in medical and nursing education as more doctors, nurses, and health administration personnel are required. Even in arts, commerce, and science degree courses, the platform-based education has forced out a large proportion of students who do not have access to digital education. Digital divide due to gender, class, caste, and location needs to be addressed seriously by the state and private higher education institutions mushrooming in the urban, peri-urban, and rural areas. In this context, a case for enhancing the public funding for higher education to 6 per cent of gross domestic product (GDP) as per the recommendation of National Education Policy 2020 needs immediate implementation. In the last two decades, India has witnessed some praiseworthy examples of support under corporate social responsibility (CSR) in terms of scholarships, fellowships, and freeships for the college and university students/scholars from the marginalised sections. Governments around the world are exploring different ways to involve the private sector in providing higher education. Contracting out educational services is controversial. One criticism that is often made of public-private partnerships (PPPs) is that these initiatives lead to the privatisation of education and thus reduce the government responsibility towards a public service. Another fear expressed is that increasing the educational choices available to students and their families may increase socioeconomic segregation if economically and socio-culturally better placed students end up self-selecting into high-quality universities further improving their outcomes. A third concern is centred on the poorer students that are left behind in the deteriorating state universities and getting ghettoised for general BA/BCom degrees resulting in unemployable degree holders. Currently, centres and departments of women’s studies, dalit studies, tribal studies, and disability studies are facing major crisis in terms of funds and positions. These disciplines are extremely important for creation of a responsible citizenry, still are marginalised in the academic hierarchy and are kept on oxygen. These disciplines need serious attention of not only the state and publicly funded universities but also of the private higher educational institutions. So far as the marginalised sections are concerned, distance education and Open Educational Resources (OERs) have proved to be a blessing with concerns such as recognition of such degrees at par with degrees offered under regular mode, employability of students graduated from distance education, learning of students, etc. Such limitations may end up with further marginalisation of student from poor social and economic background. Learning issues may be addressed through interactive sessions and face-to-face sessions. The supreme concern in the higher education must be equity, accessibility, and affordability for the historically neglected sections which demands affirmative action of the state so that they are not forced out of colleges and universities. For this, expansion, excellence, and equity in higher education are a must. This can be attained only by transcending binaries of profit and not for profit as well as meritocracy-based elitism and money-based elitism. © 2023 selection and editorial matter, National Institute of Educational Planning and Administration.