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In India, the incidence of mucormycosis reached high levels during 2021–2022, coinciding with the COVID-19 pandemic. In response to this, we established a multicentric ambispective cohort of patients hospitalised with mucormycosis across India. In this paper, we report their baseline profile, clinical characteristics and outcomes at discharge. Patients hospitalized for mucormycosis during March–July 2021 were included. Mucormycosis was diagnosed based on mycological confirmation on direct microscopy (KOH/Calcofluor white stain), culture, histopathology, or supportive evidence from endoscopy or imaging. After consent, trained data collectors used medical records and telephonic interviews to capture data in a pre-tested structured questionnaire. At baseline, we recruited 686 patients from 26 study hospitals, of whom 72.3% were males, 78% had a prior history of diabetes, 53.2% had a history of corticosteroid treatment, and 80% were associated with COVID-19. Pain, numbness or swelling of the face were the commonest symptoms (73.3%). Liposomal Amphotericin B was the commonest drug formulation used (67.1%), and endoscopic sinus surgery was the most common surgical procedure (73.6%). At discharge, the disease was stable in 43.3%, in regression for 29.9% but 9.6% died during hospitalization. Among survivors, commonly reported disabilities included facial disfigurement (18.4%) and difficulties in chewing/swallowing (17.8%). Though the risk of mortality was only 1 in 10, the disability due to the disease was very high. This cohort study could enhance our understanding of the disease's clinical progression and help frame standard treatment guidelines. [ABSTRACT FROM AUTHOR]

The paper examines how Hindu nationalist social service organizations, specifically the Deseeya Seva Bharathi (DSB), reconfigured the religious conception of 'Seva' to advance the project of constructing a Hindu social identity during the COVID-19 pandemic in the state of Kerala. The southern Indian state of Kerala has remained an exception in the story of the rise of the Hindu nationalist movement in contemporary India, which has repeatedly failed to make any considerable political inroads in the state. However, the disastrous economic consequences and livelihood challenges during the COVID-19 pandemic in the state, which was heavily dependent on foreign remittance and service industries, have opened up new spaces of engagement for Hindu nationalists. Drawing on the fieldwork conducted in central Kerala during the pandemic, this paper will elaborate on how the DSB used the crisis moment of the pandemic to reach out to economically and socially disadvantaged communities using the language of 'Seva' to build a Hindu social identity, which imbues the influence of majoritarian Hindu nationalist politics. The paper argues that the DSB's articulation of 'Seva' as a distinct and superior form of social service that is 'self-less', 'non-instrumental' and 'non-reciprocal' is significant in understanding the growing appeal of Hindu nationalist social service in the contested political sphere of Kerala, which is marked by competing social provisions by the state as well as other secular and religious groups. The paper notes that the reconfiguration of 'Seva' as a continuous religious concept enables Hindu nationalists to attain greater acceptance and legitimacy that even the secular state welfare could not achieve, while also concealing the inherent instrumental nature of its social service towards the construction of a Hindu social identity in the region. [ABSTRACT FROM AUTHOR]

Introduction: Many viral and bacterial respiratory tract infections can present with respiratory signs and progress to complicated pneumonia. In the recent Coronavirus Disease-2019 (COVID-19) pandemic, it is crucial to test all Severe Acute Respiratory Infection (SARI) patients for other microbial infections in addition to COVID-19, enabling timely diagnosis and treatment to reduce morbidity and mortality. The automated system, BioFire FilmArray, utilises multiplex Polymerase Chain Reaction (PCR) to rapidly detect and identify multiple respiratory pathogens, including selected Antimicrobial Resistance (AMR) genes, within an hour. Aim: To detect bacterial and/or viral pathogens associated with hospitalised COVID-19-negative SARI patients using the BioFire FilmArray Pneumonia Panel (BFPP). Materials and Methods: This laboratory-based cross-sectional study was conducted at All India Institute of Medical Sciences (AIIMS), Nagpur, Maharashtra, India, from June 2020 to February 2021. Respiratory samples, such as sputum, tracheal aspirate, Endotracheal (ET) secretions, and Bronchoalveolar Lavage (BAL), were collected from COVID-19-negative hospitalised SARI cases. A total of 81 patients were included in the study. The samples were tested using the BFPP (multiplex PCR) system and processed using conventional culture techniques. Patient characteristics, clinical and laboratory investigation data, and findings of respiratory viral and bacterial agents, as well as antibiotic resistance genes detected by BioFire FilmArray, were recorded using paper case reports. The data were collected and analysed using Statistical Package for Social Sciences (SPSS) software. Results: Out of the 81 clinical samples processed, the BFPP detected 168 bacterial and 18 viral pathogens. Bacterial-viral codetection was observed in 13 (16%) samples. Atypical bacteria were detected in 3% of cases. Among the bacterial pathogens, the AMR gene for New Delhi Metallo-beta-lactamases (NDM) was detected in 42 (25.9%) cases, followed by CTX-M betalactamases, VIM, and the oxacillinase group of β-lactamases. Conclusion: The BFPP test is a valuable tool for the rapid detection of a wide range of pathogens, including associated AMR genes, with high sensitivity and specificity. This can greatly aid in treatment decisions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has highlighted the importance of global health diplomacy (GHD), with India emerging as a key player. India's commitment to GHD is demonstrated by its active participation in regional and multilateral projects, pharmaceutical expertise, and large-scale manufacturing capabilities, which include the production and distribution of COVID-19 vaccines and essential medicines. India has supported nations in need through bilateral and multilateral platforms, providing vaccines to countries experiencing shortages and offering technical assistance and capacity-building programs to improve healthcare infrastructure and response capabilities. India's unique approach to GHD, rooted in humanitarian diplomacy, emphasized collaboration and empathy and stressed the well-being of humanity by embracing the philosophy of "Vasudhaiva Kutumbakam," which translates to "the world is one family." Against this background, this paper's main focus is to analyze the rise of India's GHD amidst the COVID-19 pandemic and its leadership in addressing various global challenges. India has demonstrated its commitment to global solidarity by offering medical supplies, equipment, and expertise to more than 100 countries. India's rising global leadership can be attributed to its proactive approach, humanitarian diplomacy, and significant contributions to global health initiatives. [ABSTRACT FROM AUTHOR]

Background: The burden of the COVID-19 pandemic on healthcare systems worldwide has been compromising the progress made in the fight against HIV. This paper aims to determine how the COVID-19 pandemic has impacted HIV comprehensive care service delivery globally as well as to consolidate the evidence and recommendations that may be useful in averting future crisis. Methods: This review adheres to PRISMA guidelines. PubMed, DOAJ, Science Direct and other sources like Google Scholar and citations from included studies were searched methodically to locate studies evaluating the effects of COVID on services for HIV care. The NIH and JBI quality assessment tools were used for the quality assessment of individual studies. Results: In the present review 31 eligible studies were included and the impact on HIV care cascade were summarised under six themes: Lab services, Treatment and allied services, Counselling services, Outreach services, Psycho-social impact and Implementation of sustainable strategies. The studies also presented many innovative alternatives which were lucidly highlighted in the present article. Conclusion: Current evidence depicts multiple factors are responsible for the interruption of HIV care service delivery during the pandemic, especially in low resources settings. The prospective, alternative solutions that have been used to circumvent the threat have also been addressed in this review, in addition to the negative aspects that have been observed. Transition with new innovative, sustainable care paradigms may prove to be the building blocks in removing HIV-AIDS as a public health threat. Registration: Open Science Framework (DOI: 10.17605/OSF.IO/74GHM). [ABSTRACT FROM AUTHOR]

The corona pandemic altered many traditional and historical norms of society and law. COVID-19 created a humanitarian crisis in some parts of globe, while pandemic privacy and civil liberties were under threat all over world. To combat the deadly virus, individual liberty and equality were compromised. This paper focuses on how India's health problem has compromised people's right to privacy. It will highlight how strict executive policies led to the creation of a massive surveillance system in the name of combating the COVID-19 pandemic, as well as how the absence of any policy or legal framework led to the exclusion of individuals and their families who were suspected of having the virus or caring for those who were infected with the deadly virus. The paper uses case studies and data collected from primary as well as secondary sources. The authors will also point out how the absence of privacy regulation puts millions of citizens' private information at risk of being compromised or exploited against their will. [ABSTRACT FROM AUTHOR]

India's pharmaceutical sector has been one of the largest manufacturers of generic drugs globally. During the pandemic, most countries were dependent on imports of generic drugs from India. However, India has been relying on resources from China for Active Pharmaceutical Ingredients (APIs) which are the raw material for preparing generic drugs. We considered, in our analysis, branded product groups of Paracetamol and Amoxicillin due to their extensive use in the treatment of COVID-19. From a thorough market analysis of both the drugs, we conclude that firms have a monopoly over their brands but compete within the same product group and operate in their respective market under varying prices within certain bandwidths which resembles the feature of monopolistic competitive market. We have introduced compensating function a la Helpman (1981) in the pharmaceutical goods market with the assumption that an 'ideal product' exists among the pharmaceutical goods. Given the framework, this paper explores a general equilibrium model set in a monopolistic competitive product market for branded drugs. We concluded through our propositions that expanding the pharmaceutical sector will increase the employment of unskilled labor under no capacity constraint. We will observe an increase in wages of unskilled labor only under full employment conditions wherein we would observe that the expansion of pharmaceutical good will increase wages in the unskilled labor market. However we obtain an intriguing result wherein we obtain that despite instances of limiting trade dependence on China through implementation of policies like 'Aatmanirbhar Bharat' and 'profit linked incentive schemes', yet to maintain the status quo in the global market for generic drugs, India's dependence on China would increase, owing to API imports due to the pandemic crisis. While India can grab the opportunity in the form of increased demand for pharmaceutical goods to increase the employment level of the economy but this improvement in welfare is also dependent on the degree of dependency of API India has on China. The Indian government has recognized the same through the incorporation of 'Covid-Suraksha' and PLI schemes to minimize import dependency, and accelerate the development of APIs and the production of indigenous drugs. [ABSTRACT FROM AUTHOR]

Topic modelling with innovative deep learning methods has gained interest for a wide range of applications that includes COVID-19. It can provide, psychological, social and cultural insights for understanding human behaviour in extreme events such as the COVID-19 pandemic. In this paper, we use prominent deep learning-based language models for COVID-19 topic modelling taking into account data from the emergence (Alpha) to the Omicron variant in India. Our results show that the topics extracted for the subsequent waves had certain overlapping themes such as governance, vaccination, and pandemic management while novel issues aroused in political, social and economic situations during the COVID-19 pandemic. We also find a strong correlation between the major topics with news media prevalent during the respective time period. Hence, our framework has the potential to capture major issues arising during different phases of the COVID-19 pandemic which can be extended to other countries and regions. [ABSTRACT FROM AUTHOR]

The second wave of COVID-19 is an unprecedented condition in India and began in mid February 2021. Individuals who were already suffering from other comorbidities were found with lung infection, and hence, the number of disease induced deaths were rising faster during the second wave in relation to the first wave. This paper has proposed a mathematical model with fractional order derivatives by correlating the model based number of infectives with the real number of infectives in India. For the system of fractional differential equations, a disease-free state has been computed and proved to be locally asymptotically stable with certain restrictions. The mathematical model has been numerically simulated using the predictor-corrector method to highlight the role played by fractional order in controlling the disease spread. Numerical simulations signify the fact that a vital role has been played by fractional order model over integer order model in determining the transmission of COVID-19. It can be visualized that the increment rate in the infectives is lower by taking into consideration the memory effect due to a previous exposure to COVID-19. [ABSTRACT FROM AUTHOR]

Although both central and state governments in India took the decisions to impose hard paternalistic policies of lockdown/shutdown to manage the spread of COVID-19, new cases were rising even after the first and second waves. Reverse migration, lack of social distancing, and failure to adhere to appropriate covid behavior are attributed as the leading cause of COVID-19 spread. The policy measures like 'Pradhan Mantri Gareeb Kalyan Yojana,' financial assistance, and series of lockdowns and shutdowns by the government of India have not significantly controlledthe spread of disease owing to a lack of understanding of individual's reaction to the pandemic and their reactive behavior. This paper used daily COVID-19 positive cases data to show the overall picture of COVID-19 in India. It used the explorative method to review articles related to behavioral biases involved in the decision-making process of migrant workers and individuals during the pandemic. The paper's findings show that different behavioral biases like base rate neglect, herd behavior, anchoring effect, availability bias are responsible for creating chaos, trauma, and anxiety among the migrant workers and leading to reverse migration in India. Despite knowing that COVID-19 is a fatal disease, some individuals' reaction to it was casual mainly because of hyperbolic discounting bias, optimism bias, overconfidence bias, confirmation bias, status quo bias, and loss aversion. Taking behavioral economics lessons, the paper suggests different nudging techniques for guiding people to maintain social distancing during this pandemic. Nudging has been proved to be an inexpensive tool in bringing desired behavioral changes in health economics. The paper concludes that nudging techniques can influence human behavior to control the spread of the disease. In the end, it gives direction for future work in this area to explore how behavioral economics can help policymakers to tackle the spread of infectious diseases such as COVID-19. [ABSTRACT FROM AUTHOR]

Introduction: Covid Pandemic has posed several challenges to medical leadership and public health management. The whole world is working on the best possible problem-solving health strategies to combat the worst pandemic. Modem and traditional drugs have been used and have been under testing, trial and developments; however, there is no full-proof curative or Prophylaxis treatment to Covid-19. The paper aims to develop an integrative approach to treat Covid-19. It exemplifies the integrative approach that emerged in a blending protective mechanism to reduce the infection and save people. One of the objectives of the paper is to understand how the integrative approach to treat covid-19, in tum, provided medical ethics suitable for the management ofCovid pandemic like health emergencies. Method:The research work is based on contemporary theoretical and empirical studies published in Elsevier, Pubmed and Scopus Journals. Some Studies based on modem drugs researched to show their efficacy in managing severe and critical cases. Traditional ayurvedic medicine based studies have been examined to understand their prophylaxis preventive immunity booster role in fighting against the covid19 early stages ofinfections. The integrative stratigy ofusing modem and traditional medicines, based on severity and criticality of the covid patients, has been examined. The role of A YUSH protocol in guiding the treatment and therapies with drugs and procedures have been discussed to understand integrative health management. The medical ethics has been tested through various researches on the application of social distancing, integrative medical leadership of the government and social health practices followed by the people to protect from Covid pandemic. Results:Modem medicine based curative treatments to Covid-19 has been explorative and empirical. Remdesivier, Hydroxychloroquine, Azithromycin, Evermactine, Ritonavir, Ruxolitinib and Camostat as they have entered the trials in treating corona infection. These modem drugs have if not specific but controlling and positive results to manage and protect the people. Hydroxychloroquine based treatment has saved people in India. On the other hand, traditional medicines; Ayurvedic Tinospora Corifolia (Giloya), Ashwagandha (Withania somnifera), Ayush-64, Homeopathy drugs for mild cases Arsenicum album, Bryonia alba, Gelsemium sempervirens, Rhus tox. Eupatorium perfoliatum, lpecacaucunha, Belladonna, Camphora, may be used depending upon the similarities of the symptoms. Unani drugs are recommended specifically under prophylaxis approach Zanjabeel (Zingiber officinale ), Gilo (Tinospora cordifolia), Aslassus (Glycyrrhiza glabra), Khameera Marwareed, Safoof Asgand and some are used for symptomatic relief in upper respiratory tract infections: Behi dana (Cydonia oblonga ), Unnab (Zizyphus jujuba), Sapistan (Cordia myxa), Karanjwa (Caesalpinia bonducella). Yoga-asana and therapeutic Kriyas have been proved to be effective and recommended for boosting immunity and improving lung capacities and maintaining respiratory hygiene. Conclusion:Indian medical leadership acquired comprehensive medical wisdom through the pandemic experience. The worth of modem medicines and traditional medicines and practices has been recognised, applied and practised by the Indian people. The comprehensive integrative medical approaches, as well as medical leadership, emerged as a virtue in disguise during the Covid-19. Pandemic is not over yet. Those countries who did not tackle covid-19 with integrative approach had no other defence mechanism. They could not maintain a reasonable recovery rate. Hence, they could not control the deaths due to pandemic. They lack the comprehensive medical leadership to adapt to traditional medicines, practices and prophylaxis approaches to prevent the infection in its early stages so to cure. The traditional medication has proved their worth in fighting against Corona. It is complementary for modem curative approaches. They both formed the integrative medical ethics, which must be directive for medical leadership and public health management for ongoing Covid-19 and future course of policies and strategies to fight against the diseases which create health emergencies across the globe. [ABSTRACT FROM AUTHOR]

Engineering is traditionally considered a male domain with lower female participation despite various affirmative actions taken in recent decades. There is evidence of greater gender equality as a result of the COVID-19 pandemic and precautionary lockdown measures. With this in mind, this paper investigates whether women engineers in India were more adversely affected than their male counterparts by the COVID-19 pandemic. Such an impact may be explained by 'intersectional stigma', expanded upon in the literature on discrimination. The impact of such stigma varies in different countries based on socio-cultural factors. Through the use of ethnographic and statistical research methods on secondary and primary data from a sample of 384 engineers, this paper shows that the impact of COVID-19 is not significantly different between genders in engineering education and employment. This may be due to the high demand for digital engineering skills, and strong family support in Indian society. Engineering branch may play a relatively more important role than gender in terms of impact. This finding has repercussions for continuing engineering education (CEE) programs and regulatory bodies in India in terms of enhancing course content and the results may be used in developing affirmative programs in other regions. [ABSTRACT FROM AUTHOR]

COVID-19 outbreaks are the critical challenge to the administrative units of all worldwide nations. India is also more concerned about monitoring the virus's spread to control its growth rate by stringent behaviour. The present COVID-19 situation has huge impact in India, and the results of various preventive measures are discussed in this paper. This research presents different trends and patterns of data sources of States that suffered from the second wave of COVID-19 in India until 3rd July 2021. The data sources were collected from the Indian Ministry of Health and Family Welfare. This work reacts particularly to many research activities to discover the lockdown effects to control the virus through traditional methods to recover and safeguard the pandemic. The second wave caused more losses in the economy than the first wave and increased the death rate. To avoid this, various methods were developed to find infected cases during the regulated national lockdown, but the infected cases still harmed unregulated incidents. The COVID-19 forecasts were made on 3rd July 2021, using exponential simulation. This paper deals with the methods to control the second wave giving various analyses reports showing the impact of lockdown effects. This highly helps to safeguard from the spread of the future pandemic. [ABSTRACT FROM AUTHOR]

This paper is devoted to answering some questions using a mathematical model by analyzing India's first and second phases of the COVID-19 pandemic. A new mathematical model is introduced with a nonmonotonic incidence rate to incorporate the psychological effect of COVID-19 in society. The paper also discusses the local stability and global stability of an endemic equilibrium and a disease-free equilibrium. The basic reproduction number is evaluated using the proposed COVID-19 model for disease spread in India based on the actual data sets. The study of nonperiodic solutions at a positive equilibrium point is also analyzed. The model is rigorously studied using MATLAB to alert the decision-making bodies to hinder the emergence of any other pandemic outbreaks or the arrival of subsequent pandemic waves. This paper shows the excellent prediction of the first wave and very commanding for the second wave. The exciting results of the paper are as follows: (i) psychological effect on the human population has an impact on propagation; (ii) lockdown is a suitable technique mathematically to control the COVID spread; (iii) different variants produce different waves; (iv) the peak value always crosses its past value. [ABSTRACT FROM AUTHOR]

This paper evaluates India's first officially approved self-administered rapid antigen test kit against COVID-19, a device called CoviSelf. The context is rural India. Rapid antigen tests (RATs) are currently popular in situations where vaccination rates are low, where sections of the community remain unvaccinated, where the COVID-19 pandemic continues to grow and where easy or timely access to RTPCR (reverse transcription-polymerase chain reaction) testing is not an option. Given that rural residents make up 66% of the Indian population, our evaluation focuses on the question of whether this self-administered RAT could help protect villagers and contain the Indian pandemic. CoviSelf has two components: the test and IT (information technology) parts. Using discourse analysis, a qualitative methodology, we evaluate the practicality of the kit on the basis of data in its instructional leaflet, reports about India's 'digital divide' and our published research on the constraints of daily life in Indian villages. This paper does not provide a scientific assessment of the effectiveness of CoviSelf in detecting infection. As social scientists, our contribution sits within the field of qualitative studies of medical and health problems. Self-administered RATs are cheap, quick and reasonably reliable. Hence, point-of-care testing at the doorsteps of villagers has much potential, but realising the benefits of innovative, diagnostic medical technologies requires a realistic understanding of the conditions in Indian villages and designing devices that work in rural situations. This paper forms part of a larger project regarding the COVID-19 pandemic in rural India. A follow-up study based on fieldwork is planned for 2022–2023. [ABSTRACT FROM AUTHOR]

The absence of reliable registration of Covid-19 deaths in India has prevented proper assessment and monitoring of the coronavirus pandemic. In addition, India's relatively young age structure tends to conceal the severity of Covid-19 mortality, which is concentrated in older age groups. In this paper, we present four different demographic samples of Indian populations for which we have information on both their demographic structures and death outcomes. We show that we can model the age distribution of Covid-19 mortality in India and use this modeling to estimate Covid-19 mortality in the country. Our findings point to a death toll of approximately 3.2–3.7 million persons by early November 2021. Once India's age structure is factored in, these figures correspond to one of the most severe cases of Covid-19 mortality in the world. India has recorded after February 2021 the second outbreak of coronavirus that has affected the entire country. The accuracy of official statistics of Covid-19 mortality has been questioned, and the real number of Covid-19 deaths is thought to be several times higher than reported. In this paper, we assembled four independent population samples to model and estimate the level of Covid-19 mortality in India. We first used a population sample with the age and sex of Covid-19 victims to develop a Gompertz model of Covid-19 mortality in India. We applied and adjusted this mortality model on two other national population samples after factoring in the demographic characteristics of these samples. We finally derive from these samples the most reasonable estimate of Covid-19 mortality level in India and confirm this result using a fourth population sample. Our findings point to a death toll of about 3.2–3.7 million persons by late May 2021. This is by far the largest number of Covid-19 deaths in the world. Once standardized for age and sex structure, India's Covid-19 mortality rate is above Brazil and the USA. Our analysis shows that existing population samples allow an alternative estimation of deaths due to Covid-19 in India. The results imply that only one out of 7–8 deaths appear to have been recorded as a Covid-19 death in India. The estimates also point to a very high Covid-19 mortality rate, which is even higher after age and sex standardization. The magnitude of the pandemic in India requires immediate attention. In the absence of effective remedies, this calls for a strong response based on a combination of non-pharmaceutical interventions and the scale-up of vaccination to make them accessible to all, with an improved surveillance system to monitor the progression of the pandemic and its spread across India's regions and social groups. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic restricted movement, closed businesses, and economic activities which disproportionately affected people globally. This pandemic has resurfaced the existing cracks in the societal set-up and has pushed the vulnerable and marginalized communities like migrant workers, people with disabilities, geriatric population, and commercial sex workers (CSWs) to an edge for their existence. Materials and Methods: Due to the paucity of peer-reviewed research publications on CSWs, formative research was conducted to identify the determinants and attributes of the challenges faced by CSWs during COVID-19 situation in India. Media scanning approach was used to collate literature from newspaper and magazine reporting, and peer-reviewed articles were referred from research-based search engines. Results: In total, 31 articles were included for content analysis and four domains of issues i.e., economic, social, psychological and health related challenged faced by them were identified which are supported with the verbatims of the community members as reported in the data sources considered for this study. It was identified that the CSWs adopted several protective measures and coping strategies to deal with the pandemic situation. Conclusion: This research highlighted that there is a need for further exploration of issues among CSWs by conducting studies among the communities. Furthermore, this paper provides a scope for future implementation research by identifying the key priorities and determinants of the challenges among the personal livelihood of CSWs in the country. [ABSTRACT FROM AUTHOR]

Background: The second wave of COVID-19 was disastrous and claimed many lives in India and abroad. The most challenging task was to provide the required treatment as per the patient's condition, within a limited span of time. The lack of prognostic predictors at the time of admission led to failure in prioritizing the patient's need for intensive care. Aim: This study was conducted to find out the clinical and laboratory parameters at the time of admission to ICU as predictors of outcomes in COVID-19 patients, which can help in judicious utilization of the available resources for better patient care. Subjects and Methods: Study comprises of 161 ICU admitted patients. Study of clinical traits, comorbidities, test results, and demographic variables were carried out among survivors and non-survivor. Result: Maximum death were patients of age group 21–30 years and male gender. Mortality in hypertensives, diabetics, and patients with sepsis were found to be statistically significant. Patients who developed ARDS and pneumonia or needed ventilation died invariably. High levels of laboratory parameters like IL-6, LDH, PT, INR, aPTT, ferritin, WBC count, and D-dimer were significantly associated with poor outcomes and at a particular cutoff had optimum sensitivity and specificity to predict mortality in ICU admitted COVID-19 patients. At the same time, low lymphocyte count and PaO2/FiO2 ratio was significantly associated with bad prognosis (P < 0.05). Conclusion: This paper will help in prioritizing patients in ICU who need special attention especially at the time of meager supply of resources. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) infection in India demonstrated three peaks in India, with differences in presentation and outcome in all the three waves. The aim of the paper was to assess differences in the epidemiological, clinical features and outcomes of patients with COVID-19 presenting at a tertiary care hospital in the three waves at Jaipur, India. Methods: This was a retrospective study conducted at a tertiary care hospital at Jaipur, India. Demographic, clinical features and outcomes were compared of confirmed COVID-19 cases admitted during the first wave (16-7-2020 to 31-1-2021), second wave (16-3-2021 to 6-5-2021) and third wave (1-1-22 to 20-2-22) of the outbreak. Results: There were 1006 cases, 639 cases and 125 cases admitted during the three waves, respectively. The cases presenting in the second wave were significantly younger, with significantly higher prevalence of symptoms such as fever, cough, sore throat, nausea, vomiting, headache, muscle ache, loss of appetite and fatigue (P < 0.05). A significantly higher proportion of patients received Remdesivir in the second wave (P < 0.001). However, in the second wave, the use of low molecular weight heparin, plasma therapy, non-invasive and invasive ventilator were higher (P < 0.001). Co-morbid conditions were significantly higher in the admitted patients during the third wave (P < 0.05). Radiological scores were similar in second and third wave, significantly higher than the first wave. Lymphopenia and rise of inflammatory markers including C-reactive protein and interleukin-6 were more evident in the second wave (P < 0.001). The mean mortality, hospital stay and air-leak complications were also significantly higher in the second wave (P < 0.001). Conclusions: The second wave was more vicious in terms of symptoms, inflammatory markers, radiology, complications, requirement of ventilation and mortality. Mutation in the virus, lack of immunity and vaccination at the time point of second wave could have been the possible causes. The ferocity of the second wave has important implications for the government to formulate task forces for effective management of such pandemics. [ABSTRACT FROM AUTHOR]

Background: The National Crime Record Bureau and the Prison Statistics India, 2020 report on the overcrowding and occupancy in jails has ripple effect on the spread of the COVID-19. The protection to health freedoms of detainees and prisoners reflected in the World Health Organization (WHO) Guidance on COVID-19 for Prisons and Detention, 2020. The Indian jails have congestion and inhabitance and prone to contagion disease. The COVID-19 has an expanding transmission among detainees in prisons, jails and detention homes. Objectives: The WHO Guidance on COVID-19 for Prisons and Detention, 2020 standardizes the essential instrument to manage the COVID-19 difficulties in penitentiaries and confinement homes. The direction secures the strength of detainees and convicts living in encased conditions. The ostensible purpose is to contain the COVID-19 disease from spreading to general population and release the under trials for the safe healthy conditions. Methodology: The methodology applied the canons of statutory interpretation of United Nations Principles of the Protection of Prisoners, 1982 and Basic Principles for the Treatment of Prisoners, 1990 alongside the Moscow Declaration on Prisons and Health, 2003 and Nelson Mandela Rules, 2015 in fostering the health equity and criminal justice during COVID-19 pandemic. The mandate of the WHO Interim Guidance on COVID-19 in Prisons and Other Places of Detention, 2020 is straight out in preventive and medicinal measures for the penitentiaries and confinement homes in the virus of COVID-19. Results: The paper tracks the salubrious results of the international legal norms and national precedents of High Courts and Supreme Court in heralding systemic prison reform. The compliance of WHO Interim Guidance on Preparedness, Prevention and Control of COVID-19 In Prisons and Other Places of Detention, 2020 cultivated robust criminal administration during COVID-19 pandemic and the lockdown in India. Conclusion: The judgment of High Courts and Supreme Court on prison reform during the COVID-19 pandemic in India has resulted in Health Rights of Prisoners and Prison Law Reforms during COVID-19 Pandemic in India. It also refurbished the medical services in correctional facilities and confinement homes in criminal justice system. [ABSTRACT FROM AUTHOR]

Background: COVID-19 has proven to be the worst pandemic in the history of mankind. While the pandemic still continues to perplex scientists globally, attempts are being made to quantify the mortality caused by the pandemic. Official COVID-19 figures in India grossly understate the true scale of the pandemic in the country. Fatality rates help us understand the severity of a disease, identify at risk populations, and evaluate quality of healthcare. Official COVID-19 mortality figures in India grossly understate the true scale of the pandemic in the country. A COVID-19 death is defined for surveillance purposes as a death resulting from a clinically compatible illness in a probable or confirmed COVID-19 case, unless there is a clear alternative cause of death that cannot be related to COVID-19 disease (e.g., trauma) and excess mortality is defined as the difference in the total number of deaths in a crisis compared to those expected under normal conditions. Materials and Methods: We did a systematic review of multiple papers on PubMed, Medline, Embase, MedRxiV pre print on excess mortality. Differentiation between model based estimated excess mortality and data based excess mortality was studied. Results: All the studies showed that the excess mortality was to the tune of almost three times the official figures. The model based excess mortality assumptions showed higher deaths as compared to the data based one. However, there were a lot of discrepancies in the data provided by various states along with variations observed between the two waves as well. Health survey data suggested higher mortality rate as compared to data compiled from the civil registration system. Additionally, in the second wave, a small but a significant number of deaths occurred due to non availability of oxygen and beds in the hospitals. Conclusions: Official COVID-19 deaths have entirely failed to capture the scale of pandemic excess mortality in India. If most excess deaths were, indeed, from COVID-19 then under ascertainment of COVID-19 deaths has been high, with around 8-10 excess deaths for every recorded COVID-19 death. [ABSTRACT FROM AUTHOR]

Aim. The study aims to scan through the public institutional policy implementation in tackling the global pandemic and framing universal policies for responsible governance. It also measures the impact of training interventions and non-training implications in containing the spread of COVID-19 at the grassroots level. Methods. The samples were drawn empirically from pathological tests conducted over 23 weeks to precisely examine the success of the State Government's approach in lowering COVID-19 mortality and spread. Through trend analysis, the outcome has been predicted. The study establishes a link between acknowledged ideas and government practices, providing insight into how relevant the implementation of planned state-craft programs is. Results. The findings indicated that government-imposed policies account for timely pandemic containment, and even a tiny developing state lacking advanced medical facilities and technology can set an example in combating the epidemic. Conclusions. The temporal analysis is based on the inputs acquired from government publications and other sources, allowing us to assess policy initiatives that encompass training interventions and non-training implications as prioritised by the State Government. The paper shows that a good emergency preparedness and response system is needed to prevent huge losses in any sector. This includes the already-struggling health sector, which India needs to put first to avoid more tragedies. [ABSTRACT FROM AUTHOR]

CCOVID-19 was first reported in late 2019 in Wuhan, China, and spread throughout the world like a pandemic. The population all over the world used lots of medicinal plants for prevention purposes. India has been blessed with cultural wisdom. Social health practices across the country have been utilizing integrative treatments to fight against mild fever and cold flu-like infections. Herbal and Ayurveda medicines have shown their impact on treating such infections in the early stages. The impact of herbal medicines on Covid infection is quite evident and several drug tests and trials have proved its worth of it in treating mild to severe infections. The majority of these plants are used to treat respiratory diseases having the same signs and symptoms as coronavirus symptoms or other flu infections. Our body can fight infections only when immunity is strong and for that herbal drugs as immunomodulators work well. It has worked in boosting the immunity of the patients and normal people to fight against Corona. The paper analyzes such research studies on Covid-19 treatment by herbal medicines. It makes a point that herbal medicine-based treatments and social health practices will play a complementary role in managing Covid-19 and Post-Covid health emergencies. New-Normal social ethics will evolve through such an integrative social health culture. [ABSTRACT FROM AUTHOR]

This research paper is a qualitative-based work on the ethnographic study of Ema keithel of Manipur. The study put forth the after-effect of the economic lockdown of Ema keithel due to COVID-19 and the present condition of women traders after the upliftment of the lockdown. The economic data was comparatively based on the pre-COVID-19 situation and the post-lockdown period. The women in Ema keithel are predominantly the sole bread earners and providers in their families; through their income, financial expenses are sustained. However, with the sudden lockdown caused by the COVID-19 pandemic, many thousands of women and their families had lost their only hope and financial support system. This study brings out the present situation of the women in the economic activities in the Ema keithel. [ABSTRACT FROM AUTHOR]

India is a hotspot of the COVID-19 crisis. During the first wave, several lockdowns (L) and gradual unlock (UL) phases were implemented by the government of India (GOI) to curb the virus spread. These phases witnessed many challenges and various day-to-day developments such as virus spread and resource management. Twitter, a social media platform, was extensively used by citizens to react to these events and related topics that varied temporally and geographically. Analyzing these variations can be a potent tool for informed decision-making. This paper attempts to capture these spatiotemporal variations of citizen reactions by predicting and analyzing the sentiments of geotagged tweets during L and UL phases. Various sentiment analysis based studies on the related subject have been done; however, its integration with location intelligence for decision making remains a research gap. The sentiments were predicted through a proposed hybrid Deep Learning (DL) model which leverages the strengths of BiLSTM and CNN model classes. The model was trained on a freely available Sentiment140 dataset and was tested over manually annotated COVID-19 related tweets from India. The model classified the tweets with high accuracy of around 90%, and analysis of geotagged tweets during L and UL phases reveal significant geographical variations. The findings as a decision support system can aid in analyzing citizen reactions toward the resources and events during an ongoing pandemic. The system can have various applications such as resource planning, crowd management, policy formulation, vaccination, prompt response, etc. [ABSTRACT FROM AUTHOR]

According to the World Health Organization, over 41 million cases of COVID-19 and 1 million deaths have been reported globally. More than 7 million cases of coronavirus have been reported in India alone. The growing number of cases of coronavirus worldwide poses numerous challenges to the country's current healthcare delivery system, especially in developing nations such as India. In such a situation, the task of maintaining continuity in the provision of comprehensive primary healthcare services in the community becomes a big challenge. This article discusses how family physicians can help to augment the healthcare system at the time of pandemic by providing easily accessible, holistic healthcare and by use of telemedicine. It also talks about the need to mainstream family medicine into the undergraduate and postgraduate medical curriculum and establish a robust network of family physicians trained in outbreak response and disease preparedness. For this study we looked for all papers with the terms 'Family physician', 'COVID-19', 'pandemic', and 'Primary health care'. Databases searched include PubMed, Google Scholar and DOAJ, using key words – family physician, family medicine, primary healthcare, COVID-19, and pandemic in different combinations. [ABSTRACT FROM AUTHOR]

Over the years, healthcare system in India has been largely centralized, expensive and impersonal. In a country where expenditure on healthcare is low, most healthcare expenditure is out‑of‑pocket and where most of the population continue to live in rural areas or in urban fringes, such a care is inaccessible, unresponsive and unaffordable. COVID pandemic exposed these realities further. Based on experiences of directly managing health services during COVID‑19 pandemic in different settings and across different levels, authors of this paper argue for a decentralized, distributed and responsive health systems for India, that is likely to be more effective and sustainable in normal times, and in times of crisis. [ABSTRACT FROM AUTHOR]

Background: The objective of this review was to identify and synthesize the findings of the existing literature that highlighted the psychosocial and mental health issues of the migrants during the COVID-19 pandemic in India. Materials and Methods: An exploration of the PubMed, Google Scholar, Web of Science, ScienceDirect, Google search, and some other manual searches was undertaken so that no relevant study was missed. A search on Indian scientific literature and cross-references retrieved was also conducted to get further information. The period of the search has been one year from March 1, 2020, to March 31, 2021. The database was searched with the terms "migrants," "migrant workers," "COVID-19 pandemic," "lockdown," "migrant population," "mental health issues," "psychosocial issues" to retrieve the published literature. Results: Initially, 48 research articles were retrieved and 10 of them were excluded as they had no sufficient information about mental and psychosocial challenges faced by the migrants. In the remaining 38 articles, 9 articles were original research work (n = 9) published from India related to the impact of COVID-19 on migrants. The second category consisted of editorials or commentary or letters to the editor or policy paper on psychosocial and mental health aspects of migrants during the COVID-19 pandemic (n = 17). The third category was 11 articles on perspectives or opinions or viewpoints (n = 11) related to various psychosocial and mental health issues among migrants in India during the COVID-19 pandemic. Predominantly psychosocial issues found among migrants were living conditions, basic needs, family concerns, and joblessness. The mental health issues found among migrants during the COVID-19 pandemic included psychological distress, depressive disorders, anxiety disorders, substance use disorders. Conclusion: Existing literature from India has shown that the COVID-19 pandemic severely impacted the psychosocial and mental health status of the migrants in India. This review suggests the need for more research work from the affected states of India and the development of psychosocial and mental health intervention strategies to minimize the impact of the COVID-19 pandemic on migrants. [ABSTRACT FROM AUTHOR]

This paper is based on the District library, Lakhimpur, Assam, India, which is an endeavor to highlight the reading habits of users in Pre & Post lockdown period (pre lockdown period refer as April 2019 to 24th March 2020 and post Lockdown as after 30th June 2020 to 20th March 2021) of Lakhimpur District Library (LDL). The aim of the present study is also to find out the time used by the users of the Lakhimpur district library in different age groups. The finding of the study also reveals that there is scope for development of LDL to bring more users. The study highlights the pre & post lockdown period scenario of the library where 150 Nos. of users were surveyed with structured questionnaire as a tool for data collection and collected data has been analyzed and presented in the tables and based on the available data on the Library suggestions have been given to improve the functions of the Library. [ABSTRACT FROM AUTHOR]

Social scientists and psychologists take interest in understanding how people express emotions and sentiments when dealing with catastrophic events such as natural disasters, political unrest, and terrorism. The COVID-19 pandemic is a catastrophic event that has raised a number of psychological issues such as depression given abrupt social changes and lack of employment. Advancements of deep learning-based language models have been promising for sentiment analysis with data from social networks such as Twitter. Given the situation with COVID-19 pandemic, different countries had different peaks where rise and fall of new cases affected lock-downs which directly affected the economy and employment. During the rise of COVID-19 cases with stricter lock-downs, people have been expressing their sentiments in social media. This can provide a deep understanding of human psychology during catastrophic events. In this paper, we present a framework that employs deep learning-based language models via long short-term memory (LSTM) recurrent neural networks for sentiment analysis during the rise of novel COVID-19 cases in India. The framework features LSTM language model with a global vector embedding and state-of-art BERT language model. We review the sentiments expressed for selective months in 2020 which covers the major peak of novel cases in India. Our framework utilises multi-label sentiment classification where more than one sentiment can be expressed at once. Our results indicate that the majority of the tweets have been positive with high levels of optimism during the rise of the novel COVID-19 cases and the number of tweets significantly lowered towards the peak. We find that the optimistic, annoyed and joking tweets mostly dominate the monthly tweets with much lower portion of negative sentiments. The predictions generally indicate that although the majority have been optimistic, a significant group of population has been annoyed towards the way the pandemic was handled by the authorities. [ABSTRACT FROM AUTHOR]

Food addiction (FA) has a long-term impact on the health of individuals. This study analyses the changes in FA and related behaviour in India in the wake of lockdown which started on 25th March 2020 as a response to the COVID-19 outbreak. This paper provides insight into the food consumption behavior of various segments of the population during this lockdown. It offers some new insights in this regard by establishing the relationship between a temporary pause in the consumption of palatable food and FA. This study was conducted between March and May 2020 in two stages. First, a quantitative study used the Yale Food Addiction Scale (YFAS) to identify food addicts from a sample of 150 respondents. In the second stage, in-depth telephone interviews were conducted with the food addicts; the responses were recorded, transcribed, and analysed to ascertain the changes in their overall consumption and addiction behavior towards palatable foods. This was done by conducting a thematic analysis with the help of the NVivo software where various tools like word cloud and cluster analysis were used. This study found that COVID-19 restrictions had significantly brought down the addiction to palatable food in India as the regular consumption chain had got broken during the lockdown. The consumption of palatable food is expected to remain low for a brief period after the lockdown due to hygiene issues like improper or lack of sanitization and cleanliness. However, in the long-run, the consumption of palatable food is expected to rise in India owing to its growing population, modernisation, increasing disposable income and changes in customer preferences. These findings have significant implications for the food, packaging and health industries as the changes in customer behavior will certainly impact them, and they need to duly change their strategy to adapt to the changes promptly. [ABSTRACT FROM AUTHOR]

The release of the Telepsychiatry Operational Guidelines 2020 in India, during the COVID-19 pandemic, is a relief for both clinicians and patients. These guidelines embark on initiating and executing naive and recently started telepsychiatry services in India. The document is aligned with other ethical regulations, policies, laws and the 2020 Telemedicine Practice Guidelines in India. This paper discusses a few points about the broader applicability of the guideline for the benefit of humankind in the prevailing healthcare crisis. The guidelines may be extrapolated in policy-making for telepsychiatry services in other low- and middle-income countries sharing a similar socioeconomic, cultural and political milieu. [ABSTRACT FROM AUTHOR]

In view of school closures due to the COVID-19 pandemic, this paper examines how a Home-Based Learning program affects learning outcomes of children in under-resourced communities. To overcome limited internet connectivity, the program provides remote instructions via phone calls and simple text messages along with automated voice calls to engage children enrolled in grades one to five in activity-based learning content. This intervention was conducted in three districts in the state of Odisha in India. Using a difference-in-differences framework, we find that the intervention led to a statistically significant improvement in basic number recognition and arithmetic operations, and language learning scores of children by 4.69 percentage points and 5.52 percentage points, respectively. Our results are robust to alternative methods of estimation and application of Lee bounds, thus indicating that well-designed low cost interventions could be a useful supplement for continued learning in the face of sudden shocks in low income countries. With a rise in hybrid format of teaching and learning, such interventions have the capability to cushion the decline in learning levels and provide a safety net in the event of school closures. [ABSTRACT FROM AUTHOR]

COVID-19 is a respiratory infection caused by a coronavirus that spreads from person to person. In the present situation, the COVID-19 pandemic is a swiftly rising phase. Now the time is the second wave ending phase of coronavirus and the third wave coming phase of coronavirus in India. The pandemic situation is moving forward all over India. Nowadays, the worldwide COVID-19 pandemic structure is a very hazardous situation. The COVID-19 vaccine can suppress this situation and gain preventive measures against coronavirus. In producing the COVID-19 vaccine, the Indian medical board plays a significant role. The COVID-19 vaccines have exhibited 90%–95% efficacy in preventing symptomatic COVID-19 infections. Against COVID-19, for emergency purposes, the Indian medical board has approved three vaccines: Covishield, Covaxin, and Sputnik V. Generally, the Indian people are embarrassed about the vaccination of COVID-19. All people are thinking about which vaccine is best for them. This labyrinth can be evaluated effectively using the multi-criteria decision-making (MCDM) technique. Therefore, we have proposed a novel MCDM technique for selecting COVID-19 vaccines. The main aim of this paper is to develop an MCDM technique based on a λ -weighted ranking interpreter ( R λ + , R λ − ). The first time, we have defined positive and negative λ -weighted rank interpreter for the ranking of single-valued bipolar neutrosophic (SVbN) number. Additionally, positive and negative λ -weighted values and positive and negative λ -weighted ambiguity of an SVbN-number are formulated here. Some important, valuable theorems and corollary of SVbN-number are formulated. To show the applicability of the proposed MCDM technique, we have considered a real decision-making problem where ratings of the alternatives are with SVbN-numbers. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak has led to a substantial loss of human life throughout the world and has a tremendous impact on healthcare services. Industry 4.0 technologies have established effective supply chain management towards the fulfillment of customized demands in the healthcare field. In addition, the internet of things, artificial intelligence, big data analytics, and 3D printing have been extensively used to combat the COVID-19 pandemic and assist in providing value-added services in the healthcare sector. Henceforth, this paper presents a scientometric analysis on the literature of aforementioned Industry 4.0 technologies in the context of COVID-19. It provides extensive insights into co-citation and co-occurrence analysis of high cited publications, participating countries, influential authors, prolific journals, and keywords using the CiteSpace tool. The analyses reveal that China has produced the highest research outputs, although India is the most collaborative country in this field. The current research hotspots include supply chain, 4D printing, and social distancing technologies. Furthermore, it explores emerging trends, intellectual structure of publications, research frontiers, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [Display omitted] • Industry 4.0 technologies have emerged in the healthcare domain as an area of growing interest in academia and industry discipline. • Artificial intelligence, big data analytics, internet of things and 3D printing have been extensively used to control the COVID-19 spread and assist in providing value-added services in the healthcare sector. • It explores emerging trends, intellectual structure of publications, and potential research directions for further work in the Industry 4.0 assisted healthcare domain. [ABSTRACT FROM AUTHOR]

To combat the recent coronavirus disease 2019 (COVID-19), academician and clinician are in search of new approaches to predict the COVID-19 outbreak dynamic trends that may slow down or stop the pandemic. Epidemiological models like Susceptible–Infected–Recovered (SIR) and its variants are helpful to understand the dynamics trend of pandemic that may be used in decision making to optimize possible controls from the infectious disease. But these epidemiological models based on mathematical assumptions may not predict the real pandemic situation. Recently the new machine learning approaches are being used to understand the dynamic trend of COVID-19 spread. In this paper, we designed the recurrent and convolutional neural network models: vanilla LSTM, stacked LSTM, ED_LSTM, BiLSTM, CNN, and hybrid CNN+LSTM model to capture the complex trend of COVID-19 outbreak and perform the forecasting of COVID-19 daily confirmed cases of 7, 14, 21 days for India and its four most affected states (Maharashtra, Kerala, Karnataka, and Tamil Nadu). The root mean square error (RMSE) and mean absolute percentage error (MAPE) evaluation metric are computed on the testing data to demonstrate the relative performance of these models. The results show that the stacked LSTM and hybrid CNN+LSTM models perform best relative to other models. • Various variants of LSTM and CNN deep learning architectures have been designed. • Predicted COVID-19 confirmed cases for India and its four most affected states. • RMSE and MAPE are computed to compare the performance of the designed models. • Experimental results show that predicted cases are very close to actual cases. [ABSTRACT FROM AUTHOR]

This paper deals with the mathematical modeling of the second wave of COVID-19 and verifies the current Omicron variant pandemic data in India. We also we discussed such as uniformly bounded of the system, Equilibrium analysis and basic reproduction number R 0 . We calculated the analytic solutions by HPM (homotopy perturbation method) and used Mathematica 12 software for numerical analysis up to 8th order approximation. It checked the error values of the approximation while the system has residual error, absolute error and h curve initial derivation of square error at up to 8th order approximation. The basic reproduction number ranges between 0.8454 and 2.0317 to form numerical simulation, it helps to identify the whole system fluctuations. Finally, our proposed model validated (from real life data) the highly affected five states of COVID-19 and the Omicron variant. The algorithm guidelines are used for international arrivals, with Omicron variant cases updated by the Union Health Ministry in January 2022. Right now, the third wave is underway in India, and we conclude that it may peak by the end of May 2022. [ABSTRACT FROM AUTHOR]

The global COVID-19 pandemic has hit the agriculture sector hard around the world. A study was conducted to assess the impact of the pandemic on cropping patterns, crop management, usage of chemical inputs and their organic alternatives, harvesting, and marketing avenues through a survey approach in the two states of Kerala and Tamil Nadu in India. A total of 250 farmers participated in the study, the data was analyzed by Chi-square test and Kruskal–Wallis test. The assessment of the impact of COVID-19 on some aspects was undertaken by dividing the study period into three phases. Though a smaller number of people were infected with COVID-19 in the initial phase of the pandemic compared to the later phases, farm operations and the procurement of inputs were significantly affected at this phase as there was a sudden disruption in transportation due to COVID-19-induced movement restrictions. During the entire study period, commodities such as rice, bananas, vegetables, coconuts, and flowers suffered maximum crop loss compared to pulses, groundnuts, cotton, and rubber. Among fertilizers, the maximum shortage was observed for chemical fertilizers (46%) and biofertilizers (30%) compared to cow dung (18%) and poultry manure (6%), indicating that farmers tended to use more local materials that could be easily procured and accessed compared to shop-based inputs. A rise in the cost of cultivation, scarcity of farm workforce, and difficulty in hiring farm machinery all have contributed to the loss of profit during the pandemic period. As a response to COVID-19, growers initiated post-harvest processing of commodities, and cropping systems remained the same during the period. The paper also discusses some remedial measures to be adopted by households in the future, to minimize the impacts of such pandemics in the agrarian sector. [ABSTRACT FROM AUTHOR]