A mixed method study to assess behavioral and social predictors of parent/caregivers intention to vaccinate their children against COVID-19 disease in an Indian state marked by significant health disparities. (preprint)

Background: Parents/caregivers are the key decision-makers for childs health care including vaccination. Vaccine hesitancy along with lagging full immunization coverage for childhood vaccination in India, affect child health outcome and will affect covid-19 vaccine uptake in children. It is important to understand behavioral and social factors surrounding childhood COVID-19 vaccination to design appropriate interventions to improve uptake. Methods: A mixed-method approach combining quantitative and qualitative method was undertaken. A cross sectional survey of parents/caregivers of children aged less than 18 years residing in the state was carried out to find the prevalence and predictors of parent/ caregivers intention to vaccinate against COVID-19 disease. Semi-structured interviews were carried out to find facilitating and barrier factors for childhood COVID-19 vaccination. Result: Out of 9904 study participants, 73.4% had intention to vaccinate. Parent/caregivers education and occupation, marital status, family type, family income, co-morbidity and previous COVID-19 infection in family, childhood vaccination under NIS, were found to be significantly associated. The likelihood of intention to vaccinate children against COVID-19 disease was greater among parents/caregivers aged 18-29 years (OR=2.631, 95% CI [1.733-3.995], illiterate parents/caregivers (OR=3.037, 95% CI [2.319-3.977], prior COVID-19 infection in family (OR=1.595, 95% CI [1.432-1.821], and childrens prior vaccinations under NIS (OR=1.251, 95% CI [1.218-1.289]. In qualitative part, forty-five semi-structured interviews were conducted. The majority of intending parents gave vaccine effectiveness, increased immunity, high infection risk, herd immunity, and medical recommendations as reasons. Parents who refused mentioned inadequate data, adverse effects, beliefs, safety, and inconvenience as reasons. Effectiveness, and safety, long-term effects, and the short testing period were among the concerns of hesitant parents. Conclusion: In order to promote COVID-19 vaccination among children, we need to address barriers, facilitators and behavioral determinants of parents/caregivers identified in this study and have targeted strategies for them.

The ‘bright' side of innovation management for international new ventures

All businesses are finding it difficult to figure out how to enhance the environment and society. Following the co-generation of social, ethical, and corporate aims, new sustainable inventions have evolved since the COVID-19 pandemic event, similar to new solutions into a workable, viable, and ethical business. The positive and negative aspects of inventions are a topic of discussion among innovation management academics. In particular, how innovation may be more sustainable even when job inequities caused by automation have sparked a feeling of the importance of upholding human rights. Despite that, the innovation management literature is still far from being pedantic in studying automation and human rights towards sustainable innovations in the context of international new ventures (INVs). The article challenges a pessimistic view of innovations by examining automation and human rights for 3000 INVs through the perspective of the micro-foundations. Multiple linear regression analysis is used to evaluate hypotheses, demonstrating how social entrepreneurship can play a constructive mediating role in upholding human rights and promoting automation. This demonstrates the necessity for additional research on a business's individual level to create social breakthroughs. The study encourages policymakers and the government to support sustainable innovations by utilizing technology to boost job quality, uphold human rights, and foster global entrepreneurship.

Effects of COVID-19 pandemic on the host communities of Rohtak, Haryana and Durgapur, West Bengal

Background: The ongoing pandemic has caused severe crisis in the hospitality sector with millions of people forced to stay home and under quarantine to stop the spread of contagion. The following paper aims to highlight the problems and difficulties faced by the hospitality sector and the host communities in particular due to the mandatory nation-wide lockdown owing to COVID-19 pandemic. Background: The purpose of the study was to analyse and highlight the common characteristics of the host community towards the stranded international and domestic travellers while catering and accommodating them owing to local authorities' obligatory lockdown along with the forced shutdown of hotels and large commercial establishments in Rohtak and Durgapur. Methodology: The geographical area of the research and data collection was limited to the city of Rohtak in Haryana and Durgapur in the state of West Bengal. Population of the study is limited to the region of Rohtak and Durgapur. The number of participants or respondents were 42. The paper is exploratory in design and follows a qualitative methodological approach. The data was collected with the help of an online self-report questionnaire. Results: Over a period of 95 days, the interviews of hosts and tourists were conducted. The content analysis revealed eight themes in all the recorded interviews. A majority of tourists and host communities were impacted by the pandemic in psychological aspects by 35.7%, followed by accommodation and protocols by 33.3% each. Conclusion: There have been various studies that have been conducted in the backdrop of COVID-19 pandemic but not many of them have highlighted the importance of host communities which are an indispensable part of our society as well as the hospitality sector.

Metronidazole, acyclovir and tetrahydrobiopterin may be promising to treat COVID-19 patients, through interaction with interleukin-12.

COVID-19 patients have shown overexpressed serum levels of several pro-inflammatory cytokines, leading to a high mortality rate due to numerous complications. Also, previous studies demonstrated that the metronidazole (MTZ) administration reduced pro-inflammatory cytokines and improved the treatment outcomes for inflammatory disorders. However, the effect and mechanism of action of MTZ on cytokines have not been studied yet. Thus, the current study aimed to identify anti-cytokine therapeutics for the treatment of COVID-19 patients with cytokine storm. The interaction of MTZ with key cytokines was investigated using molecular docking studies. MTZ-analogues, and its structurally similar FDA-approved drugs were also virtually screened against interleukin-12 (IL-12). Moreover, their mechanism of inhibition regarding IL-12 binding to IL-12 receptor was investigated by measuring the change in volume and area. IL-12-metronidazole complex is found to be more stable than all other cytokines under study. Our study also revealed that the active sites of IL-12 are inhibited from binding to its target, IL-12 receptor, by modifying the position of the methyl and hydroxyl functional groups in MTZ. Three MTZ analogues, metronidazole phosphate, metronidazole benzoate, 1-[1-(2-Hydroxyethyl)-5-nitroimidazol-2-yl]-N-methylmethanimine-oxide, and two FDA-approved drugs acyclovir (ACV), and tetrahydrobiopterin (THB) were also found to prevent binding of IL-12 to IL-12 receptor similar to MTZ by changing the surface and volume of IL-12 upon IL-12-drug/ligand complex formation. According to the RMSD results, after 100 ns MD simulations of human IL-12-MTZ/ACV/THB drug complexes, it was also observed that each complex was swinging within a few Å compared to their corresponding docking poses, indicating that the docking poses were reliable. The current study demonstrates that three FDA-approved drugs, namely, metronidazole, acyclovir and tetrahydrobiopterin, are potential repurposable treatment options for overexpressed serum cytokines found in COVID-19 patients. Similar approach is also useful to develop therapeutics against other human disorders.

Anti SARS-CoV-2 Antibody Kinetics up to 6 months of follow-up: Result from a Nation-wide Population-based, Age Stratified Sero-Epidemiological Prospective Cohort Study in India (preprint)

Repeated serological testing tells about the change in the overall infection in a community. This study aimed to evaluate changes in antibody prevalence and kinetics in a closed cohort over six months in different sub-populations in India. The study included 10,000 participants from rural and urban areas in five states and measured SARS-CoV-2 antibodies in serum in three follow-up rounds. The overall seroprevalence increased from 73.9% in round one to 90.7% in round two and 92.9% in round three. Among seropositive rural participants in round one, 98.2% remained positive in round two, and this percentage remained stable in urban and tribal areas in round three. The results showed high antibody prevalence that increased over time and was not different based on area, age group, or sex. Vaccinated individuals had higher antibody prevalence, and nearly all participants had antibody positivity for up to six months.

MXRFCS: Design of an augmented Multidomain XRay Feature representation model for identification of CoVID Severity levels (preprint)

The COVID-19 pandemic has placed an enormous strain on healthcare systems worldwide, leading to a need for more efficient methods of identifying the severity of COVID-19 patients to efficiently allocate resources. Existing Xray processing models for identification of COVID-19 are either highly complicated or showcase lower efficiency when applied for real-time scenarios. To overcome these issues, this paper presents a novel approach for identifying the severity of COVID-19 patients using an augmented multimodal X-ray feature representation model. The proposed model combines X-ray images, clinical data, and demographic information to create a robust representation of individual patient condition. The collected information is converted into multidomain feature sets, including frequency, Gabor, Wavelet and entropy components. A customized deep neural network is trained on this representation to predict the severity level of COVID-19 patients. To evaluate the performance of the proposed model, we used a dataset of X-ray images and clinical data from COVID-19 patients. Our results demonstrate that the proposed model outperforms existing methods for identifying COVID-19 severity levels, achieving an accuracy of 98.5% on multiple dataset samples. The proposed model's performance was observed to be promising in terms of precision, recall and delay, thus has the potential to aid in the early identification and effective management of severe COVID-19 cases, thus contributing to the global effort to combat the COVID-19 pandemic under clinical use cases.

Adhesive Capsulitis After COVID-19 Vaccination: A Case Series.

ABSTRACT: Of the many bizarre complications of administration of the COVID 19 vaccine, adhesive capsulitis is almost unheard of, although shoulder injury related to vaccine administration, which by definition has symptom onset within 48 hrs and is caused by faulty injection technique, has been rarely reported. Nine cases of adhesive capsulitis, five males and four females with a mean age of 48.7 ± 12.7 yrs, presenting within 1 mo of intramuscular Covishield vaccine on the ipsilateral deltoid and fulfilling the standard UK FROST Multicenter Study diagnostic criteria are reported. The mean time interval from vaccination until symptom onset was 12.3 ± 3.1 days, and mean symptom duration was 9.4 ± 2.4 wks. Conventional treatment with nonsteroidal anti-inflammatory drugs, followed by intra-articular steroid injection coupled with suprascapular nerve steroid block, improved the pain score and range of movement in 8 wks. The exact pathogenesis remains an enigma, although mechanisms such as local spread via deltoid muscle microvasculature, nerves, or shoulder injury related to vaccine administration causing secondary adhesive capsulitis have been hypothesized. While adhesive capsulitis is a very common diagnosis in the physiatric outpatient setting, the possible association with Covishield vaccination, the Indian version of the Oxford AstraZeneca recombinant ChAdOx1 nCoV-19 vaccine, is almost absent in existing literature and hence likely to be missed by clinicians, which necessitates this report.

Telemedicine: History and Success Story of Remote Surgical Education in India.

Initiation of telemedicine in medical education in India was at par with developed countries but acceptance and progress have been slow. However, the recent coronavirus disease-19 (COVID-19) pandemic leading to disruption of Halstedian model of surgical teaching has changed the traditional dynamics of perception of this mode of education. Sanjay Gandhi PostGraduate Institute of Medical Sciences (SGPGIMS), has been a pioneer and introduced the telemedicine system into surgical education as early as in year 2001. In this article, we reviewed the literature on tele-education in surgical field in Indian scenario, with particular emphasis on tele-education activities at the SGPGIMS, with respect to current thinking and future prospects on surgical training.

Objective Evaluation of Olfactory and Taste Dysfunction Among COVID-19 Patients: A Cross Sectional Study from Tribal India.

There is a varying prevalence of olfactory and taste dysfunction (OTD) in COVID-19 patients, with a higher prevalence reported in the European population as compared to the Asian population. Psychophysical tests are crucial to determine the exact frequency, extent and clinical characteristics of these OTDs. The present study objectively evaluated the OTD for patients treated in the Dedicated COVID-19 Hospital (DCH) in Shahdol. This prospective cross-sectional study was conducted after IEC approval in DCH Shahdol for a period of four months among RT-PCR positive patients, and they were evaluated using validated chemosensitive psychophysical test during ENT consultation to identify OTD. The sample size was calculated as 92 considering prevalence (p) of OTD as 41.3% by applying formula: n = (Z1-a/2)2 × p (1-p) / d 2. The information pertaining to the subjects was kept anonymous and confidential. During data analysis, an association was significant for p value < 0.05. It was observed that 45.5% of subjects reported either loss of taste or smell. During objective evaluation, olfactory and taste dysfunction was observed among 42.4% of subjects (95/224). The Chi-square analysis reflected statistically significant difference (p < 0.05) between subjects with OTD and without OTD for the variables such as days from onset of symptoms to admission, and symptoms (fever, sore throat and shortness of breath). Taste and smell are among the important senses and in India they are mostly subjectively evaluated for COVID-19 induced OTD which results in underreporting of these symptoms. So, a gold standard objective evaluation should be taken into consideration to evaluate OTD.

Vaccination coverage and breakthrough infections of COVID-19 during the second wave among staff of selected medical institutions in India.

India experienced the second wave of SARS-CoV-2 infection from April 3 to June 10, 2021. During the second wave, Delta variant B.1617.2 emerged as the predominant strain, spiking cases from 12.5 million to 29.3 million (cumulative) by the end of the surge in India. Vaccines against COVID-19 are a potent tool to control and end the pandemic in addition to other control measures. India rolled out its vaccination programme on January 16, 2021, initially with two vaccines that were given emergency authorization-Covaxin (BBV152) and Covishield (ChAdOx1 nCoV- 19). Vaccination was initially started for the elderly (60+) and front-line workers and then gradually opened to different age groups. The second wave hit when vaccination was picking up pace in India. There were instances of vaccinated people (fully and partially) getting infected, and reinfections were also reported. We undertook a survey of staff (front line health care workers and supporting) of 15 medical colleges and research institutes across India to assess the vaccination coverage, incidence of breakthrough infections, and reinfections among them from June 2 to July 10, 2021. A total of 1876 staff participated, and 1484 forms were selected for analysis after removing duplicates and erroneous entries (n = 392). We found that among the respondents at the time of response, 17.6% were unvaccinated, 19.8% were partially vaccinated (received the first dose), and 62.5% were fully vaccinated (received both doses). Incidence of breakthrough infections was 8.7% among the 801 individuals (70/801) tested at least 14 days after the 2nd dose of vaccine. Eight participants reported reinfection in the overall infected group and reinfection incidence rate was 5.1%. Out of (N = 349) infected individuals 243 (69.6%) were unvaccinated and 106 (30.3%) were vaccinated. Our findings reveal the protective effect of vaccination and its role as an essential tool in the struggle against this pandemic.

A cross-sectional study on anxiety due to COVID-19 and its predictors among undergraduate medical students in a tertiary care teaching hospital of Kolkata, West Bengal.

Background: Medical education is recognized as stressful globally. COVID-19 pandemic is an additional source of anxiety to the medical students. Objectives: This study was conducted to assess the prevalence and to identify the factors associated with anxiety due to COVID-19 among undergraduate medical students in a teaching hospital of Kolkata, West Bengal. . Methods: An observational cross-sectional study was conducted among 363 undergraduate medical students using the stratified random sampling of a medical college from June to July 2021. Data were collected using a predesigned, pretested, and structured online questionnaire, including "Coronavirus Anxiety Scale." Descriptive statistics were used to estimate the prevalence of anxiety. Pearson's Chi-square test was performed to find out the factors associated with anxiety due to COVID-19. Results: About 25.6% of the medical students were found to have anxiety due to COVID-19. About 28.9% of them reported COVID-19 infection in family in recent past and 11.0% had themselves tested positive. Nearly 20% reported loss of family members, relatives, and close friends due to COVID-19. The factors associated with anxiety due to pandemic were socioeconomic status, social stigma, sleep disturbances, history of COVID-19 in family, loss of job. and vaccination status of family members missing practical classes and exam-related anxiety. Conclusion: The study found that one-fourth of the medical students had anxiety due to COVID-19. Social stigma due to COVID-19 and loss of job of parents were the most significant predictors. It is recommended that targeted psychological and clinical interventions need to be taken to alleviate students' anxiety due to COVID.

To investigate the importance of the CBC, derived parameters, and morphology of peripheral blood cells in COVID-19 patients

Aim: To investigate the importance of the CBC, derived parameters, and morphology of peripheral blood cells in Covid-19 patients. Material and methods: According to their symptoms, patients were classified as asymptomatic, mild, or moderate-severe. This research included all paediatric and adult patients who had two CBC samples available (one at admission and another during discharge) throughout their hospital stay. Those who were already undergoing therapy for their cancer, haematological illness, liver disease, or chronic lung disease were not allowed to participate. Results: Patients' ages varied from 8 to 71. The patients' average age was 36.15+or-14.58 years. Sixty percent of research participants were male, making up a sex ratio of 1.5:1. (M: F). The average white blood cell count was 6.87+or-3.51 x109/L, the average red blood cell count was 4.61+or-0.88 x106/microL, and the average haemoglobin level was 12.80+or-2.15 g/dl upon admission. The average absolute neutrophil count was 3.81+or-3.46x109/L, the average absolute lymphocyte count was 2.31+or-1.40x109/L, the average absolute monocyte count was 0.38+or-0.31x109/L, and the average absolute eosinophil count was 0.15+or-0.18x109/L. Overall, the average number of platelets per microliter of blood was 149.21+or- 80.25. Neutrophil to lymphocyte ratio (NLR) at admission was 3.806;platelet to lymphocyte ratio (PLR) was 116.32+or-13.1;lymphocyte to monocyte ratio (LMR) was 8.91+or-5.25, and derivative neutrophil to lymphocyte ratio (d-NLR) was 2.61+or-1.36. Twenty (40%) of the patients were asymptomatic at admission, while 44% had mild symptoms, and 16% required oxygen and ventilator support due to moderate to severe symptoms. The RT-PCR test was positive for all of the patients examined. There was a noteworthy shift in both the mean WBC and mean platelet counts after the follow-up evaluation. No correlation was seen between clinical state on admission and any of the other CBC measures (p>0.05) Conclusion: The significance of CBC values and morphological inspection of the peripheral blood smear at baseline and subsequent assessment is highlighted in the research.

A cross-sectional study on the role of hematological and inflammatory biomarkers as predictor of mortality at the time of admission among COVID-19 patients

Whole world experienced COVID-19 pandemic with more than 155 million cases and >3.4 million deaths. Vasculitis and immune system activation plays a critical role in pathogenesis, especially in severely ill and non-survivors COVID-19 patients. Aims and Objectives: The aim of the study was to establish the role of hematological indices and inflammatory biomarker as predictors of mortality among non-survivor and survivor COVID-19 cases at the time of admission. Materials and Methods: The cross-sectional study was conducted at a dedicated COVID-19 referral hospital from July 2020 to August 2020, among 300 real time-polymerase chain reaction confirmed COVID-19 cases. Demographic, clinical, comorbidity, laboratory investigation, and outcome data were collected from patient's medical record. Outcome variables -- discharged (survived) or death (non-survived) were considered for comparison of various hematological indices and inflammatory biomarkers. Data are represented as median, IQR (Q1-Q3) and difference between median and proportions were calculated by Mann--Whitney U-test and χ² test. A predictive power of laboratory parameters between survivors and non-survivors was evaluated using receiver operant curve (ROC) analysis and area under the ROC curve (AUC). Results: The median age of non-survivors was significantly higher than survivors. Hypertension was significantly associated with non-survivors. Hematological parameters such as total leukocyte count, absolute neutrophil count, Neutrophil: Lymphocyte ratio were significantly increased with lymphocytopenia (P=0.001), and Inflammatory biomarkers such as C-reactive protein (CRP), lactate dehydrogenase, D-dimer, ferritin, procalcitonin, and NT-Pro BNP, all were significantly increased in non-survivors patients (P=0.001). CRP and neutrophil lymphocyte ratio (NLR) showed "Good" predictive value for mortality with cutoff value of 74.0 mg/l (AUC=0.841, Sensitivity=80.4%, Specificity=73.0%) and 5.65 (AUC=0.805, Sensitivity=76.1%, Specificity=73.0%), respectively. Pro-BNP showed "Fair" predictive value for mortality with cutoff value of 330.5 pg/ml (AUC=0.726, Sensitivity=73.9%, Specificity=58.2%). Conclusion: We suggest that CRP, NLR, and Pro-BNP can be used as a screening tool to predict mortality in COVID-19 patients for timely intervention to save valuable life, especially when sensitivity toward severity of COVID-19 among medical health professionals and general public is on decline. [ABSTRACT FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Comparative analysis of SARS-CoV-2 envelope viroporin mutations from COVID-19 deceased and surviving patients revealed implications on its ion-channel activities and correlation with patient mortality.

One major obstacle in designing a successful therapeutic regimen to combat COVID-19 pandemic is the frequent occurrence of mutations in the SARS-CoV-2 resulting in patient to patient variations. Out of the four structural proteins of SARS-CoV-2 namely, spike, envelope, nucleocapsid and membrane, envelope protein governs the virus pathogenicity and induction of acute-respiratory-distress-syndrome which is the major cause of death in COVID-19 patients. These effects are facilitated by the viroporin (ion-channel) like activities of the envelope protein. Our current work reports metagenomic analysis of envelope protein at the amino acid sequence level through mining all the available SARS-CoV-2 genomes from the GISAID and coronapp servers. We found majority of mutations in envelope protein were localized at or near PDZ binding motif. Our analysis also demonstrates that the acquired mutations might have important implications on its structure and ion-channel activity. A statistical correlation between specific mutations (e.g. F4F, R69I, P71L, L73F) with patient mortalities were also observed, based on the patient data available for 18,691 SARS-CoV-2-genomes in the GISAID database till 30 April 2021. Albeit, whether these mutations exist as the cause or the effect of co-infections and/or co-morbid disorders within COVID-19 patients is still unclear. Moreover, most of the current vaccine and therapeutic interventions are revolving around spike protein. However, emphasizing on envelope protein's (1) conserved epitopes, (2) pathogenicity attenuating mutations, and (3) mutations present in the deceased patients, as reported in our present study, new directions to the ongoing efforts of therapeutic developments against COVID-19 can be achieved by targeting envelope viroporin.

Suramin, penciclovir, and anidulafungin exhibit potential in the treatment of COVID-19 via binding to nsp12 of SARS-CoV-2.

COVID-19, for which no confirmed therapeutic agents are available, has claimed over 48,14,000 lives globally. A feasible and quicker method to resolve this problem may be 'drug repositioning'. We investigated selected FDA and WHO-EML approved drugs based on their previously promising potential as antivirals, antibacterials or antifungals. These drugs were docked onto the nsp12 protein, which reigns the RNA-dependent RNA polymerase activity of SARS-CoV-2, a key therapeutic target for coronaviruses. Docked complexes were reevaluated using MM-GBSA analysis and the top three inhibitor-protein complexes were subjected to 100 ns long molecular dynamics simulation followed by another round of MM-GBSA analysis. The RMSF plots, binding energies and the mode of physicochemical interaction of the active site of the protein with the drugs were evaluated. Suramin, Penciclovir, and Anidulafungin were found to bind to nsp12 with similar binding energies as that of Remdesivir, which has been used as a therapy for COVID-19. In addition, recent experimental evidences indicate that these drugs exhibit antiviral efficacy against SARS-CoV-2. Such evidence, along with the significant and varied physical interactions of these drugs with the key viral enzyme outlined in this investigation, indicates that they might have a prospective therapeutic potential in the treatment of COVID-19 as monotherapy or combination therapy with Remdesivir.

The Nicobarese tribes and their coastal fishing activities during the COVID-19 pandemic-related restrictions- preliminary findings.

We interviewed the Nicobarese tribal community (N = 95) of Car Nicobar Island situated in the Andaman and Nicobar archipelago, India to analyze the impact of COVID-19-related restrictions on their coastal fishing activities. Our surveys revealed a significant reduction (p < 0.001) in the average monthly income and fish catches during pre and post-COVID-19 scenarios. Constraints faced during the pandemic-related restrictions and the possible solutions to reinforce the fishing activities were highlighted for sustainable resource management in Car Nicobar Island.

A Review of the Machine Learning Algorithms for Covid-19 Case Analysis.

The purpose of this article is to see how machine learning (ML) algorithms and applications are used in the COVID-19 inquiry and for other purposes. The available traditional methods for COVID-19 international epidemic prediction, researchers and authorities have given more attention to simple statistical and epidemiological methodologies. The inadequacy and absence of medical testing for diagnosing and identifying a solution is one of the key challenges in preventing the spread of COVID-19. A few statistical-based improvements are being strengthened to answer this challenge, resulting in a partial resolution up to a certain level. ML have advocated a wide range of intelligence-based approaches, frameworks, and equipment to cope with the issues of the medical industry. The application of inventive structure, such as ML and other in handling COVID-19 relevant outbreak difficulties, has been investigated in this article. The major goal of this article is to 1) Examining the impact of the data type and data nature, as well as obstacles in data processing for COVID-19. 2) Better grasp the importance of intelligent approaches like ML for the COVID-19 pandemic. 3) The development of improved ML algorithms and types of ML for COVID-19 prognosis. 4) Examining the effectiveness and influence of various strategies in COVID-19 pandemic. 5) To target on certain potential issues in COVID-19 diagnosis in order to motivate academics to innovate and expand their knowledge and research into additional COVID-19-affected industries.

Probabilistic fuzzy set and particle swarm optimization based computational method for fuzzy time series forecasting (preprint)

Computational methods for time series forecasting have always an edge over conventional methods of forecasting due to their easy implementation and prominent characteristics of coping with large amount of time series data. Many computational methods for fuzzy time series (FTS) forecasting have been developed in past using fuzzy set, intuitionistic fuzzy set (IFS), and hesitant fuzzy set (HFS) for incorporating uncertainty, non-determinism, and hesitation in time series forecasting. Since probabilistic fuzzy set (PFS) incorporates both probabilistic and non-probabilistic uncertainties simultaneously, we have proposed PFS and particle swarm optimization (PSO) based computational method for FTS forecasting. First, we have developed a PFS based computational method for FTS forecasting and then it is integrated with PSO to enhance the accuracy in forecasted outputs. Unlike other PSO based for FTS forecasting method, PSO is used to optimize both number of partitions and length of intervals. Three diversified time series data of enrolments of the University of Alabama, market price of State Bank of India (SBI) share at Bombay stock exchange (BSE) India, and death cases due to COVID-19 in India are used to compare the performance of PFS based computational method of FTS forecasting before and after its integration with PSO in terms of root mean square error (RMSE). After integration of PFS based computational method with PSO, accuracy in the forecasted outputs is increased significantly and its performance is found better than many other existing FTS forecasting methods. Goodness of the proposed FTS forecasting method is also tested using tracking signal and Willmott index.

The offline-to-online shift of medical education during COVID-19 pandemic: A mixed method study of medical teachers and students from India (preprint)

Introduction: Most institutes worldwide have experienced a forced shift to online mode education during COVID 19 pandemic. As in Indian Medical Institutions e-learning is not a well-established mode of teaching, it disrupts the newly implemented competency based medical education (CBME). This sudden shift in educational methods introduced new experiences, opportunities, and difficulties among medical teachers and students. In this study we explore undergraduate medical students and teachers’ perception, detailed insights and learning experience on online medical education. Method: This is an institution based mixed methods study conducted at three medical institutes in India. A self-prepared semi structured questionnaire was applied to extract various prospective of teaching and assessment through online mode. Qualitative descriptive design was applied using focused group discussion. All FGDs were audio-recorded, transcribed verbatim and analyzed using thematic content analysis to identify themes and subthemes regarding perceptions of online and offline education. Result: A total of 323 medical students out of 510 and 35 medical teachers out of 71 were included in the study. Most students and teachers agreed to the fact that they faced technical difficulties, perceived less connected, and felt difficulty in achieving desired competencies. In qualitative analysis five major themes (Learning Environment, Technology, Competency, Health issues, Assessment) and multiple subthemes were identified. Conclusion: Improvement of the online teaching methods with appropriate technical advancement may help to reduce the gap between the online and offline teaching learning modalities.