Impact of the COVID-19 Pandemic on the Psychological Well-Being of Health Care Professionals in India

Introduction and Objective Health care professionals (HPs) have been at the forefront facing the pressures and uncertainties of the COVID-19 pandemic, and thus have a higher psychological vulnerability. The incidence of psychological distress, which can negatively affect an HP's work efficiency and long-term well-being, has not been studied in depth in India.Materials and Methods A multicentric study was conducted using the digital means of communication across Max Healthcare between June and August 2020. HPs in the department of oncology, including doctors, nurses, and other support staff, were invited to voluntarily participate in the self-administered online survey. A total of 87 HPs in oncology (41 doctors, 28 nurses, and 18 in other fronts) were assessed using the 12-item General Health Questionnaire (GHQ-12). Outcome of interest was psychological distress (defined as a GHQ-12 score >15).Results The overall incidence of psychological distress among HPs in oncology during the COVID-19 pandemic was 17.20%. Significantly higher levels of psychological distress were observed among HPs with a history of psychiatric illness ( p = 0.003), and among HPs with a work experience of less than 10 years ( p = 0.017).Conclusion The COVID-19 pandemic had a significant impact on the psychological well-being of HPs in India. This study implicated the recognition of the psychological well-being of HPs in oncology as an unmet need during the COVID-19 pandemic, further recommending efforts toward increasing accessibility of mental health services for them.

A Prospective Approach on Covid-19 Forecasting Using LSTM

The novel Corona virus has been proclaimed as a worldwide pandemic through World Health Organization in the March 2020 has immensely affected the world with its ferocity. By observation, the scientists got to know that it transmits from one human to other by droplets which range from larger respiratory droplets to smaller aerosols or direct contact with an infected person. Its impurity has been assessed to have an incubation time of 6.4 days than a simple reproduction amount of 2.24-3.58.[19] The transmission rate and spread of infection is quite rapid as compared to other fatal viral infections encountered till date. A massive loss of human life was faced even by the developed countries which had the best health-care facilities. According to WHO, COVID-19 has been confirmed in 238,521,855 people over the world, with 4,863,818 deaths as of October 9th, 2021. After experiencing the second covid wave, the number of cases had got dropped drastically but the increase in their number in the recent days is a major cause of concern. This stresses us to build some prediction models which could help in providing relief to the virus-prone areas. In this study, we are using time series for predicting forthcoming cases of corona virus. © 2022 IEEE.

A hybrid convolutional neural network model to detect COVID-19 and pneumonia using chest X-ray images

A hybrid convolutional neural network (CNN)-based model is proposed in the article for accurate detection of COVID-19, pneumonia, and normal patients using chest X-ray images. The input images are first pre-processed to tackle problems associated with the formation of the dataset from different sources, image quality issues, and imbalances in the dataset. The literature suggests that several abnormalities can be found with limited medical image datasets by using transfer learning. Hence, various pre-trained CNN models: VGG-19, InceptionV3, MobileNetV2, and DenseNet are adopted in the present work. Finally, with the help of these models, four hybrid models: VID (VGG-19, Inception, and DenseNet), VMI(VGG-19, MobileNet, and Inception), VMD (VGG-19, MobileNet, and DenseNet), and IMD(Inception, MobileNet, and DenseNet) are proposed. The model outcome is also tested using five-fold cross-validation. The best-performing hybrid model is the VMD model with an overall testing accuracy of 97.3%. Thus, a new hybrid model architecture is presented in the work that combines three individual base CNN models in a parallel configuration to counterbalance the shortcomings of individual models. The experimentation result reveals that the proposed hybrid model outperforms most of the previously suggested models. This model can also be used in the identification of diseases, especially in rural areas where limited laboratory facilities are available. © 2022 Wiley Periodicals LLC.

LASUA: A Lightweight Authentication Scheme with User Anonymity for IoT-Enabled Mobile Cloud

Mobile Cloud Computing (MCC) also known as on-demand computing uses cloud computing to deliver applications to mobile devices. This new computational paradigm model which plays a big part in the Internet of Things (IoT), has increased its popularity even more during Covid-19 pandemic and became a necessity when schools, businesses and hospitals must work remotely. We can access and process remote data which are stored over the cloud server in real-time by connecting to a wireless network. For accessing any cloud server, a mutual authentication and key agreement between a mobile user and a cloud server provider is required. However, existing authentication schemes for MCC fail to provide user anonymity, server anonymity and user untraceability. Therefore, we propose a Lightweight Authentication Scheme with User Anonymity (LASUA) which artfully employs Elliptic Curve Cryptography (ECC), random number, time stamps, one-way hash functions, concatenation, XOR operations and fuzzy extractor for biometric to enable various security features including anonymity and resistance against various attacks. LASUA utilises the hardness of ECC to provide top-notch security with low computation and communication cost, a perfect solution for resource constrained devices. © 2022 IEEE.

An Augmented SLAM Method with a Visual-Lidar- Equipped Unmanned Vehicle for Detecting Control Measures against COVID-19

In epidemic prevention and control measures, unmanned devices based on autonomous driving technology have stepped into the front lines of epidemic prevention, playing a vital role in epidemic prevention measures such as protective measures detection. Autonomous positioning technology is one of the key technologies of autonomous driving. The realization of high-precision positioning can provide accurate location epidemic prevention services and a refined intelligent management system for the government and citizens. In this paper, we propose an unmanned vehicle (UV) positioning system REW_SLAM based on lidar and stereo camera, which realize real-time online pose estimation of UV by using high-precision lidar pose correction visual positioning data. A six-element extended Kalman filter (6-element EKF) is proposed to fusion lidar and stereo camera sensors information, which retains the second-order Taylor series of observation and state equation, and effectively improves the accuracy of data fusion. Meanwhile, considering improving lidar outputs quality, a modified wavelet denoising method is introduced to preprocess the original data of lidar. Our approach was tested on KITTI datasets and real UV platform, respectively. By comparing with the other two algorithms, the relative pose error and absolute trajectory error of this algorithm are increased by 0.26 m and 2.36 m on average, respectively, while the CPU occupancy rate is increased by 6.685% on average, thereby proving the robustness and effectiveness of the algorithm.

Plant-Derived Antimicrobial Peptides Are Effective in Combating the Pathogenicity of SARS-CoV-2, a Novel Therapeutic Approach

The pandemic that started in 2019 in Wuhan caused a vast number of deaths worldwide due to the absence of effective therapy against SARS-CoV-2. The present study investigates the interaction of AMP with viral protein and host receptors. We screened plant-derived antimicrobial peptides (AMP) from the docking web server with the help of PDB ID. We selected five anti-microbial peptides based on their antiviral and physiological activities. The interaction of anti-microbial peptide and Mpro was analyzed using the HADDOCK web server. The results revealed that the minimum Z-score was obtained by the 6LU7-1N4N complex followed by 6LU7-1GPS docked complex. The docking results showed the interaction potency of AMP with 6LU7. The dynamic simulation study of 100ns was performed to check the stability of the docked complexes of AMP and 6LU7. From the stable and positive results of dynamics studies, we can conclude that these selected AMPs have immense potential to be used as therapeutic agents for the treatment of disease. © 2022 The authors and IOS Press.

Influenza-Associated Hospitalization Rates and Proportion of Hospitalizations with Influenza and SARS-CoV-2 Coinfection, FluSurv-NET, October 1, 2021-April 23, 2022

Background. Influenza-associated hospitalization rates were low during the 2020-21 season. We describe influenza-associated hospitalization rates and prevalence of influenza and SARS-CoV-2 coinfection among patients hospitalized with influenza during 2021-22. Methods. We used data from the Influenza Hospitalization Surveillance Network (FluSurv-NET), a population-based surveillance system for laboratoryconfirmed influenza-associated hospitalizations active from October-April of each year. We calculated cumulative and weekly hospitalization rates per 100,000 population and compared preliminary rates during 2021-22 with prior season rates (2010-11 through 2020-21). We determined the proportion of influenza-associated hospitalizations with SARS-CoV-2 coinfection during 2021-22. Results. During October 1, 2021-April 23, 2022, 3,262 influenza-associated hospitalizations were reported to FluSurv-NET;the cumulative hospitalization rate of 11.1 was higher than 2011-12 and 2020-21 season rates, but lower than rates observed during all other seasons since 2010-11 (Figure 1A). After peaking in the week ending January 1, 2022 (MMWR week 52), weekly hospitalization rates declined until the week ending February 19, 2022 (MMWR week 7) when they began to rise modestly, similar to patterns observed during several prior seasons (Figure 1B). Among the 3,262 hospitalizations, 87 (2.7%) had SARS-CoV-2 coinfection;the prevalence by age group was as follows: 0-17 years 3.4%, 18-49 years 2.8%, 50-64 years 3.5%, 65-74 years 2.5%, >= 75 years 1.6%. Among the 3,262 influenza-associated hospitalizations, the prevalence of SARS-CoV-2 coinfection by month (October 2021- April 2022), respectively, was 11.4%, 2.5%, 2.6%, 8.9%, 3.4%, 0.8%, and 0.5%. Conclusion. SARS-CoV-2 coinfection was uncommon among patients hospitalized with influenza during 2021-22. Likely due to ongoing COVID-19 mitigation measures, the influenza-associated hospitalization rate during 2021-22 was lower than rates observed in most seasons in the decade preceding the COVID-19 pandemic. A late rise in weekly influenza hospitalization rates in 2021-22 might have been a result of relaxation of COVID-19 mitigation measures and/or a late season peak in influenza activity. (Figure Presented).

Red Blood Cell-Derived Nanoerythrosomes Mediated Efficient Delivery Of Mrna Vaccine Candidate Against COVID-19

Introduction: The COVID-19 pandemic has been a major public health concern throughout the world. Various ventures of vaccine candidates are being studied rigorously in this regard and one such candidate is the receptor binding domain (RBD) of spike protein which interacts with angiotensin converting enzyme 2 (ACE2) on the host cell's membrane. Exploiting this interaction, many scientists across the world attempted to develop mRNA vaccine against SARSCoV- 2. A major lacuna associated with mRNA vaccines is their delivery through a suitable carrier, especially given the stability issues associated with mRNA vaccines. Aims & Objectives: The aim of our research is to develop an efficient mode of delivery of the self-amplifying mRNA (saRNA) against COVID 19. We have developed small vesicles from erythrocyte ghosts, known as nanoerythrosomes, which are in the nanometre range and focussed on development of nanoerythrosomes for delivery of mRNA-based vaccines. Material(s) and Method(s): Nanoerythrosomes were prepared from erythrocytes using osmotic and ultrasonic frequency stress and loaded with saRNA vaccine candidate. Thereafter, the nanoerythrosomes were characterized using Dynamic Light Scattering (DLS) and Transmission Electron Microscopy (TEM) to confirm their homogeneity, integrity and size. The mRNA loaded nanoerythrosomes were used to deliver the mRNA in Vero E6 cells to evaluate its uptake. Result(s): The characterization of nanoerythrosomes using DLS and TEM revealed their size in the range of 100-200 nm. The delivery mediated by nanoerythrosomes was comparable to the Lipofectamine mediated uptake of saRNA indicating the excellent delivery efficacy of nanoerythrosomes. The added advantage of nanoerythrosomes mediated delivery is that they are rapidly taken up from blood by macrophages of the reticuloendothelial system (RES) that is present in liver, lung, and spleen. Thus the combination of saRNA and nanoerythrosomes can accelerate the uptake and antigen presentation in reticuloendothelial system and will provide an outstanding platform for the development of SARS-CoV2 vaccine. Conclusion(s): We developed a new approach to deliver mRNA vaccine candidates using nanoerythrosomes and successfully demonstrate its efficacy in vitro. This strategy can be further extended for the delivery of other vaccine candidates. (Figure Presented).

LightMobileNetV2: A Lightweight Model for the Classification of COVID-19 Using Chest X-Ray Images

Deep Learning is most widely used in the area of medical imaging. Due to its success, many works of literature use deep learning methodsto classify COVID-19 related cases. Currently, the world is facing the second and third waves of this deadly disease. Therefore, the need of the hour is to develop some user-friendly lightweight model that could easily detect the disease with little effort. It is found that early diagnosis is the only way to defeat this deadly virus. This paper tried to classify the chest X-ray(CXR) images into different categories, such as normal lung opacity, viral pneumonia, and COVID-19 positive using a transfer learning mechanism. For this classification task, we have removed eight blocks of the pre-trained MobileNetV2model, and then it is fed to the classifier consisting of a dropout and linear layers. The proposed model is approximately 9times lighter than the original MobileNetV2 and performing almost with the same accuracy. Experimental evaluation proves that the proposed model gives satisfactory results compared with the original and other recent works. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

FACTORS INFLUENCING RESTAURANT SELECTION IN THE COVID-19 ERA: A STUDY OF CONSUMER PREFERENCES IN INDIA

COVID-19 struck the humanity at the end of 2019 and since then it has been ravaging the mankind. Since then the economies have been badly affected;businesses have shut down and the restaurant businesses are no exception to it. Now, when the vaccination programs are being carried out by the governments all around the world, including India, and restrictions are going away, the customers will be coming out to the restaurants. This paper intends to study what are the factors which will make the Indian customers choose a restaurant and to find out if there have been effects of the pandemic on the criteria of restaurant selection. To find the answers to these, a questionnaire with ten various factors was designed and circulated by using Google Form. The data thus collected was analyzed by applying one sample t-test and Gap analysis. The hypothesis was tested and it was found that the pandemic had an impact on the restaurant selection criterion. ‘Personal hygiene of the staff', ‘quality of food ingredients' and ‘taste of food' are the most important factors for customers in deciding to choose a restaurant and ‘location' with no impact on restaurant selection. © D. A. Tsenov Academy of Economics, Svishtov,.

Intravenous Branched Chain Amino Acid Infusion Is Associated with Early but Ill-Sustained Recovery of Overt Hepatic Encephalopathy in Acute-on- Chronic Liver Failure: A Pilot Protocol

Background: Hepatic encephalopathy (HE) in acute-on- chronic liver failure (ACLF) is associated with significant morbidity and mortality. There is paucity of data regarding HE management in patients with ACLF and most of the evidence is extrapolated from patients with cirrhosis. We conducted a prospective, randomized controlled clinical trial to study the efficacy of intravenous branched chain amino acids (IV-BCAA) with lactulose versus lactulose alone for improvement in HE scores at 24h, day 3 & day 7. Duration of ICU stay and survival at days 7 and 28 was compared. Method(s): CANONIC ACLF patients with HE grades >= 2 were assessed for eligibility and randomized into two groups -experimental arm (IV-BCAA -500mL/ day for 3 days + Lactulose;n=39) and comparator arm (Lactulose alone;n=37). Six patients developed COVID-19 after randomization & were excluded (4-experimental arm & 2-comparator arm). Grade of HE was assessed by West Haven Classification and Hepatic Encephalopathy Scoring Algorithm (HESA). ACLF severity was determined by CLIF-C ACLF and MELD scores. All patients received standard of care for HE and ACLF management. Result(s): Both groups were similar in baseline characteristics including grade of HE (2.85 +/- 0.75 vs 2.82 +/- 0.66;P = 0.864) and CLIF-C ACLF score (54.19 +/- 5.55 vs 54.79 +/- 5.74;P = 0.655). Overall survival was 40% at 28 days (48.5% vs 31.4%;P=0.143). Significant improvement in HESA score by >=1 grade at 24h was seen in 14 patients (40%) in BCAA arm and 6 patients (17.14%) in control group (P=0.034) which translated to a shorter ICU stay in the BCAA arm (Table 1). Median change in HESA score at 24h was significantly more in BCAA arm than control arm (P=0.006), however, this was not sustained at day 3 or 7. Ammonia levels did not correlate with the grade of HE (Spearman's correlation coefficient(rho) = -0.0843;P=0.295). Conclusion(s): Intravenous BCAA leads to early but ill-sustained improvement in grade of HE and reduced ICU stay in ACLF.

Molecular Docking studies on the Anti-viral activity of Cellulose Acetate Phthalate (CAP) as an adjuvant against SARS-CoV-2 by Protease Mpro

Even after a year, the COVID-19 pandemic produced by the SARS-CoV-2 remains a major source of concerns for scientists. Surprisingly, the primary protease is a key target because of its role in viral propagation. No significant data is available regarding the off-label indications of pharmaceutical adjuvants so far. CAP stands for "Cellulose Acetate Phthalate", an industrial polymer utilized in the enteric coating of tablets and capsules. CAP has been shown in certain trials to have anti-HIV properties by using the co-receptor location. Thus, in the present work, CAP was used to test against SAR-primary CoV-2's protease Mpro using in-silico method. Auto Dock was used to evaluate selected CAP molecules against SAR-CoV-2, and Discovery studio visualizer was used to create 3D and 2D interaction photos. CAP's binding energies were-3.05kcal/mol,-3.78kcal/mol and-3.01kcal/mol during blind docking, site specific docking, and docking in presence of N3 inhibitor, respectively. Additionally, the discovery studio visualizer was utilized to observe the interacting amino acids with CAP structure. Interestingly, the data from the discovery studio visualizer showed that it established H-bonds with Mpro residues, TYR37, TYR101, and LYS100 during blind docking and LYS88, TYR101, and LYS100 during site specific docking. The findings indicated that CAP binds non-competitively to allosteric sites and that it may have synergistic effects with other anti-viral agents. Moreover, further research is required to justify its synergistic activity as anti-viral agent. Copyright © 2022, Anka Publishers. All rights reserved.

An Analytical Study To Assess Prevalence Of Covid 19 Breakthrough Infections Among Healthcare Workers And Its Association With Covid Vaccines In India

Introduction: Despite high level of COVID vaccine efficacy, small percentage of fully vaccinated individuals develop symptomatic or asymptomatic covid-19 infection, termed as Breakthrough [BT] Covid-19 infection. Aim(s): to study characteristics of breakthrough Covid-19 infections among health care workers in a tertiary care center. Method(s): This was a hospital based retrospective Cohort study. Health care workers of medical college and hospital, Jaipur, Rajasthan who were completely immunized against Covid-19 with Government approved vaccines (Covishield or Covaxin) were approached in the year 2021. The study was conducted for three months, from March, 2021 till June, 2021. Result(s): Covishield was the prominent vaccine to be administered by majority, 92%. 23.7% is the incidence of breakthrough infection in our study. Conclusion(s): People vaccinated with Covaxin show lesser incidence of COVID-19 breakthrough infections as compared to those vaccinated with Covishield. Copyright © 2022, Anka Publishers. All rights reserved.

Driving through sustainable systems: a Study of Air Quality Index of Delhi during COVID-19 Pandemic

The impact of lockdown during covid-19 pandemic on air quality in terms of pollution was investigated in the Delhi/NCR region in this study. The National Air Quality Index (NAQI) uses air quality data for six pollutant measures (PM10, PM2.5, SO2, CO, NO2 and O3) from monitoring stations across the megacity to demonstrate the spatial pattern of air quality before and during the lockdown period due to pandemic. The objective of this study is to investigate the interrelationship among the various parameters the Pearson’s correlation analysis was conducted. The results found were able to demonstrate that during lockdown air quality was significantly improved. It was also found that among other pollutants, level of NO2 and CO have also declined during- lockdown phase. It was observed that during this period of lockdown, the air quality index on maximum number of days was found to be good and satisfactory in Delhi that was the clear indication of an improvement in air quality due to a reduction in pollution and emissions of vehicles and industries. It can be implemented to further work on parameters to improve the air quality in future.

Correlation between NEWS, CT Severity Score and RT-PCR Cycle Threshold Value among Mild and Moderate COVID-19 Patients

Introduction: The clinical diagnosis of COVID-19 is supplemented by clinical severity indices. These indices are the National Early Warning Score (NEWS, which aids in risk stratification), CT severity score (radiological severity score), and Reverse Transcription-Polymerase Chain Reaction (RT-PCR) cycle threshold (Ct value, which provides a semi-quantitative measure of viral load). Aim(s): To assess the correlation between NEWS at admission, RT-PCR Ct value and CT severity score in mild and moderate COVID-19 patients. Methods and Materials: This prospective cohort study was conducted in Maulana Azad Medical College and Lok Nayak hospital, New Delhi, from January to June 2021. The study included 50 subjects (25 with mild COVID-19 and 25 with moderate COVID-19). NEWS was calculated at admission and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Ct value was estimated using real-time RT-PCR. CT severity score was calculated based on High Resolution Computed Tomography (HRCT) chest findings. The correlation among the parameters was determined using Pearson correlation formula. Result(s): The mean age of subjects in the mild and moderate COVID-19 groups were 49.52 years and 51.84 years, respectively. The mean RT-PCR Ct value of E gene was 24.48 and Rdrp gene was 24.56 in the mild COVID-19 group;while in the moderate group it was 23.72 for both E gene and Rdrp genes. The correlation between NEWS and Ct value of E gene (r-value=-0.06, p-value=0.68), Ct value of Rdrp gene (r-value=-0.03, p-value=0.79) and the correlation between CT severity score and Ct value of E gene (r-value=-0.05, p-value=0.73), Ct value of Rdrp gene (r-value=-0.06, p-value=0.68) was negative and insignificant. The mean CT severity score in mild COVID-19 group was 3.92, and in moderate COVID-19 group was 9.88. A significant positive correlation was found between the CT severity score and NEWS at admission. Conclusion(s): The clinical severity of COVID-19 as estimated by NEWS corroborates with CT severity score while the relationship between RT-PCR Ct value and clinicoradiological severity needs to be ascertained by further research. Copyright © 2022 Journal of Clinical and Diagnostic Research. All rights reserved.

COVID-associated mucormycosis: A case series

Coronavirus disease 2019 (COVID-19) infections may be associated with a wide range of bacterial and fungal coinfections. Mucormycosis is more often seen in immunocompromised individuals, and complications of orbital and cerebral involvement are likely in diabetic ketoacidosis and with concomitant use of steroids. The most common risk factor associated with mucormycosis is diabetes mellitus in India. Early identification of high-morbidity conditions is crucial for optimal treatment and improved outcomes. A total of 20 patients with post-COVID mucormycosis were studied. Uncontrolled diabetes and excessive usage of steroids are two of the main factors aggravating the illness, and both of these must be properly checked. Early diagnosis and prompt management are required for a good prognosis and to achieve a less fulminant disease course in cases of postcoronavirus mucormycosis. © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

A Framework for Automatic Fake Content Identification

Fake news emerged as a challenge for society now a day. Easy accessibility and low cost to the internet makes the fake news propagation task easy. In the Covid-19 pandemic situation, it is required to reduce the proliferation of misleading content to reduce its severe impact. Many existing works are based on lexico-syntactic features using a small training sample size. To address this issue, this study used the Gossip-cop dataset for evaluation. Various supervised techniques of the ML model and advanced deep learning techniques are implemented for intense research. Dataset is crawled from Gossipcop fact-checking websites. The dataset consists of 4,947fake news with text and 16,694 real news. The result of these algorithms helps in differentiating false content from reliable news and improved the accuracy achieved using existing techniques. © 2021 IEEE.

Multisystem Inflammatory Syndrome in a Young Adult During the Second Wave of COVID-19 Pandemic in India ABS0116)

Aim and background: Since June 2020, there have been several reports of multisystem inflammatory syndrome in adults (MIS-A). There is a paucity of a description of MIS-A from India. Materials and methods: A 26-year-old, healthy male, with a previous history of COVID-19, without any known history of chronic disease, with clinical characteristics resembling MIS-A was hospitalised on May 30, 2021. Results: Case presentation: The patient presented with 1 week of persistent high-grade fever (102-degree F) with chills and rigor. The concomitant complaints were left-sided pain in the buccal cavity, left facial swelling, intra-orbital pain, and watery eyes. The respiratory rate was 24/minute, SpO2 was 96% on room air. Ever since the recovery from COVID-19 (1 week back), there was severe pain in the throat with difficulty in breathing, generalised weakness, and loss of appetite. BP was 130/80 mm Hg. The hospital course was notable for profound systemic inflammation, requiring ICU admission. MRI revealed discrete subcentimetric bilateral deep cervical lymph nodes. Blood tests at admission revealed, lymphopenia 15.3%, CRP 61.84 mg/L, total leucocyte count 12.93 (1000/μL), neutrophils 78.7%. Red distribution width (RDW) was marginally elevated to 15%. The patient was managed by IV fluids, IV immunoglobulin. Scrub typhus was excluded by IgM ELISA IgM with a negative titre (0.095). Widal test was negative and excluded enteric fever. d-dimer was within normal limits (125 ng/ mL). Borderline elevation of hepatic enzymes was noted. There was a high SARS-CoV-2 IgII titres (12050.4). The patient improved following intravenous immunoglobulin (IVIG), IV ascorbic acid, dexamethasone, supportive care and was discharged on day 4, with methylprednisolone for 1 week. Conclusion: Specific treatment is yet to be determined. However, dexamethasone and IVIG allowed controlling the inflammatory process. MIS-A, as a delayed immune complication, requires early recognition, with a multidisciplinary approach and aggressive therapeutic intervention, to yield favourable outcomes. MIS-A should be considered in adults, during the recovery phase from COVID-19. This is perhaps, the first description of MIS-A from India during the second wave of the COVID-19 pandemic. The role of IVIG needs further exploration.

Facilitators and Barriers to Infant Immunization during COVID-19 Pandemic

Introduction: The world is enveloped with the coronavirus disease 2019 (COVID-19) Pandemic with modern medicine and public health facing their most significant challenges ever posed. As the number of COVID-19 cases increased worldwide, an important issue of concern was the continuation of routine immunization services for children. This study has been conceptualized to assess the effect of the COVID-19 pandemic on infant Immunization. Materials and Methods: This study was a descriptive study conducted in an urban community amongst healthy children < 1-year-old from January 2018 to September 2021. Immunization records of infants were obtained from data generated during each immunization session and strength, weakness, opportunity, and threat analysis was done using a questionnaire. Results: During the study, a total of 3518 vaccinations were done, a total of 3010 vaccinations (85.5%) were done on time, and the total delayed vaccinations were 508 (14.5%). The difference among the years was statistically significant, with the highest delay in the year 2020 (P < 0.001). However, in the year 2021, the number of vaccinations carried out from April to September was 568, with delayed vaccination of only 10.9%. Conclusion: The Armed Forces childhood immunization program could be sustained during the COVID-19 pandemic due to a multitude of contributing factors such as adherence to national guidelines that prioritized vaccination, infrastructure, and availability of trained workforce and most importantly commitment to strict COVID appropriate behavior.