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Background: The COVID-19 pandemic has resulted in about 75.2M cases and 1.67M deaths worldwide, as on 18th December 2020 data live updates of World Health Organizations. In response to this pandemic, this study analyzes the global issue of rising and falling of COVID-19 cases and changing scenario of economies. Method(s): The data has been extracted from January 2020 to December 2020 from some of the reliable sources of the World like WHO Coronavirus disease (COVID-19) dashboard, Worldometer, and Centers for Disease Control and Prevention (CDC). It also represents the global scenario of the COVID-19 pandemic and its social determinants around the world. Result(s): There has been spatial heterogeneity in the number of cases and the number of deaths among regions worldwide. There is a great impact on the countries economy, both on the supply and demand side. It shows that several factors affect the determinants of health at various levels like income, healthcaresystem, education, etc also play a major role in it. Conclusion(s): The increasing cases worldwide have adversely affected the economy and have led to a scarcity of resources which further caused the collapse of the economy and trade.Copyright © 2020 Ubiquity Press. All rights reserved.
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Purpose: Psychosocial assessment prior to liver transplantation is essential to ensure that caregivers and pediatric patients are adequately prepared for this complex process. There are several standardized pre-transplant psychosocial assessment tools in the adult literature. However, no such tool exists for pediatric liver transplant. In our study, we aim to develop a patient-centered, standardized questionnaire for the pre-transplant evaluation of pediatric liver transplant patients. Method(s): In the first phase of our study, we recruited parents and adolescent patients who have undergone liver transplantation at Texas Children's Hospital to participate in separate focus groups. Each focus group was led by trained graduate students, took approximately 1 hour, and was digitally recorded and transcribed. The purpose of these focus groups was to give patients and their parents the opportunity to discuss and highlight their experiences with the transplantation process, with an emphasis on perceived challenges during the process. Result(s): The majority (67%) of families interviewed strongly agree that they experienced stress during the transplant process (Figure 1). Family support mitigated this stress for many, as well as being adequately educated about the process. A third (33%) of families had difficulty attending appointments post-operatively (Figure 2). Most had private insurance, but some families report alternate methods of payment (Figure 3). Conclusion(s): The focus groups show that there are many psychosocial challenges our patients face, most notably with transportation and separation of family units with out-of-state patients and with large and frequently changing medical teams among all patients. Patients transplanted during the COVID-19 pandemic noted difficulty with hospital restrictions during long stays. The qualitative data gathered in this phase of the study will be applied with data from the adult literature in order to develop specific items for our pre-transplant psychosocial assessment tool. Future studies will focus on validation of our tool in a larger cohort of pediatric liver transplant patients.
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One of the biggest health challenges that the world has faced in recent times is the pandemic due to coronavirus disease known as SARS-CoV-2, or Covid-19 as officially named by the World Health Organization (WHO). To plan medical facilities in a certain location in order to combat the disease in near future, public health policy makers expect reliable prediction of the number of Covid-19 positive cases in that location. The requirement of reliable prediction gives rise to the need for studying growth in the number of Covid-19 positive cases in the past and predicting the growth in the number in near future. In this study, the growth in the number of Covid-19 positive cases have been modelled using several machine learning based regression techniques viz., Multiple Linear Regression, Decision Tree Regression and Support Vector Regression. Further, different feature selection techniques based on Filter and Wrapper methods have been applied to select the suitable features based on which prediction is to be done. This study proposes the best observed method for modelling the pattern of growth in number of Covid-19 cases in the near future for a locality and also the best selection method that can be employed for obtaining the optimal feature set. It has been observed that unregularized Multiple Linear regression model yields promising results on the test data set, compared to the other regression models, for predicting the future number of Covid-19 cases and Backward Elimination feature selection method performs better than other feature selection methods. © 2022 IEEE.
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With the outbreak of the global pandemic covid-19, most educational institutions across India have moved towards the usage of online teaching platforms Viz., Google Meet, Zoom, Webex, and Microsoft teams to process learning continuity. In research and development, it is observed that meager importance is given to address the issues of securing e-learning systems. Securing an e-learning system is a unique challenge faced in India as many systems are accessed and managed through the internet by numerous users distributed over diverse networks. Moreover, the online teaching platforms are open, distributed, and interactive;hence, it becomes challenging to ensure that every user has access to the correct information. Building trust will leverage the usage of online teaching systems in terms of security, usability, and protection of personal information. The key focus of this paper is to analyze the existing online and remote learning tools and identify the level of cyberattacks. This article also explores recent progress in novel ICT engineering paradigms in cyber assurance and protection. The paper proposes a cyber security framework using cutting-edge technologies like AI and Deep Learning to fight against cyber-attacks.
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The Coronavirus disease 2019 SARS-CoV-2 is a disease which causes fear to human lives that has taken thousands and hundreds of lives globally. The pandemic which has resulted in a global health emergency is currently a much sought-after research topic. The frequently mutating virus which has originated from Chiroptera and subsequently got transmitted to other mammals including humans. However, at the genomic level, it is yet to be unraveled what makes humans more prone to getting infected by the coronaviruses. Here, we have implemented a Machine Learning model known as K-means Clustering that uses the combination of different features to determine the risk of infection. In this research paper, the K-means clustering method is used since it is a good performer for Clustering analysis. The algorithm can group the sequences of the dataset into five clusters based on the Elbow plot and co-linearity of co-efficient. Using dimensional reduction technique PCA is used with a 3D visualization and a heat map to showcase the correlation efficiency between the mutated and original sequence considered. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Background:Ample of studies have been carried out on the causative agent, pattern of illness, treatment options which mainly concern regarding the patients and general population affected from COVID -19, however few studies have fo- cused on its adverse effects on front line health care workers ( HCW ) and other employees of health care facilities. The present retrospective study was planned to analyse the clinico-viro-epidemiological profile of different covid clusters in HCWs and non-health care employees of AIIMS, Bhubaneswar. Methods:A hospital based retrospective study was carried out on the HCWs and other employees of AIIMS, Bhubanes- war, who tested positive SARS-CoV-2 infection by RT-PCR test. The clinical and demographic information were analysed with corresponding virological data of the patient. Results:Of the 671 employees of AIIMS, Bhubaneswar who tested positive for SARS-CoV-2, 92 were from eight clusters that could be traced. The eight clusters involved 4 clusters each from both the HCWs group containing 66 individuals and non-HCWs group with 32. Male to female ratio was 2.5:1. Maximum 55(59.7%) individuals belonged to 20 -30yrs age group followed by 30-40yrs 28(30.4%) and least 3(3.2%) in 50-60yrs. Asymptomatic COVID positive individuals were more as compared to symptomatic in all the age groups. All the individuals with cycle threshold value (CT) ≤ 20 were symptomatic;of the 21 persons with CT value 21-30, seven were symptomatic and 14 were asymptomatic. Majority with >30 CT value (35/44) were asymptomatic. Conclusions:Frontline HCWs are constantly at increased risk of getting infection, but the disease burden and post -covid stigma can be substantially decreased among non-HCWS if COVID appropriate behaviour are strictly implemented and followe
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Background:The Coronavirus disease 2019 (COVID 19) pandemic has resulted in reduced performance of non-emergent surgeries and procedures across the nation. About four-fifth of COVID-19 infections remain asymptomatic. With an incu- bation period of 7-14 days, patients can also remain in the pre-symptomatic stage. Hence, knowledge of the prevalence of disease among the asymptomatic is important to prevent spread of disease to the health care professional as well as for patient safety. The present study sought to assess the frequency of positivity of COVID 19 among pre -procedural/pre-operative patients. Methods:A retrospective study of all asymptomatic pre-procedural cases was conducted from 10th June 2020 till 10th November 2020. Nasal swabs were collected from patients 48 hours before procedures (including elective and emer- gency surgeries, patient scheduled to receive chemotherapy, radiotherapy, patients undergoing biopsy, endoscopy). RT - PCR test was done for all samples. Case-specific data, results of all PCR tests, and answers to screening questions (about symptoms, exposure, and travel) were obtained Results: 5320 tests were conducted during the study period. Of these, data could be analysed for 2117 tests done. 51.1% were male patients and the median age group of the cohort was 46 years. 254 of 2117 (11.9%) belonged to the paediatric age group. Of 2117, 35 samples were rejected because of sample leakage or improper labelling. Out of the remaining 2082 samples;338 were positive;1606 were negative, and 138 inconclusive. We received second sample for 117 of the 138 inconclusive samples of which 18 were positive, 93 were negative and 6 remained inconclusive. Thus, the total positivity was 17.1%. Conclusions:This study confirms the high proportion of asymptomatic patients with COVID -19 positivity;and suggests the value of screening by RT-PCR during COVID-19 pandemics.
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Background:From the day of the detection of 1st case in India on 30th January 2020, COVID -19, has infected 8.96 mil- lion people in India, from around 128 million samples tested. The clinico -epidemiological characteristics of COVID 19 have been varied in different countries. The present study was undertaken to understand the clinico -epidemiological characteristics of COVID-19 in Odisha. Methods:This was a retrospective, single centre study. The epidemiological, demographic & clinical parameters were analysed of the samples tested in AIIMS Bhubaneswar between March 2020 to November 2020. Results:A total of 56,547 samples were tested for SARS CoV-2 by RT-PCR from March 24th 2020 till 15th November 2020. Of the total samples tested, 9754 were tested positive, with an average positivity rate of 17.25%. The mean age of the patients 38.21 years, with male to female ratio of 3:1. Among the various age groups, the majority affected were the middle ages (31-50 years) constituting around 38.77% (n = 3782) of the total cases followed by 15 -30 years (31.48%, n=3071) &> 50 years (23.64% n = 2305) & was least in children (<14years) with 6.11% (n = 596). Among the COVID -19 positives, 64.5% (n=6295) were asymptomatic & only 35.5% (n=3459) were symptomatic. Of the symptomatic patients, 81.1% (n=2805) presented with mild, 17.7 %( n=612) cases moderate, and only around 1.12% (n=39) had severe COVID - 19 disease. Of the severe cases, majority belong to the age group 31-50 (38.46%, n = 17), followed by 15-30 (15.3%, n=11). The monthly trend showed an increasing trend up to September, with maximum positivity rate of 38%, followed by a decline during October (14.7%) & November (5.8%) Conclusions: In this study of 9754 patients with confirmed COVID-19 in Odisha, the characteristic findings included younger age, male predominance, high proportion of asymptomatic patients & a declining trend in the positivity rate over the months
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Background:The spread of COVID 19 has not been uniform across various states of India, which encounters significant spatio-temporal variations in the climatic conditions. As, seasonal cycle plays a dynamic role in spread of respiratory In- fections, we aimed to ascertain the Influence of temperature, humidity and seasonal variability on COVID positivity in a tertiary care testing hospital of Odisha Methods:Samples collected from patients attending AIIMS, Bhubaneswar and from other districts for detection of Covid-19 were tested at our lab by RTPCR. A retrospective month wise comparative analysis of the Covid -19 positivity rate of samples tested during the months of March to November 2020 was done with temperature and humidity Results:Out of 56,874 samples tested, 9,484(16.6%) were positive by real time reverse transcriptase PCR. As Odisha is a costal state it has high humidity and temperature as compared to rest of India. The mean humidity along with the mean temperature were com- pared to COVID positivity [Formula presented] Conclusions:In our study period over 9 months, Mon- soon months showed surge in positive cases peaking in August and September, and autumn months showed a downward trend.
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Background:COVID-19 pandemic is posing a major burden on society. Measures taken to reduce its spread critically de- pend on timely and accurate identification of virus-infected individuals by the most sensitive and specific method availa- ble, i.e. real-time reverse transcriptase PCR (RT-PCR). RT PCR can detect SARS-CoV-2 as early as day one of symptom onset. There are various RT PCR kits approved by FDA & ICMR, performance of which vary widely. Here, we assessed the performance of four PCR kits with the ICMR NIV Screening & Confirmatory assay used for diagnosis of COVID -19 in Od- isha. Methods:A total of 20 samples, which included five positives, one inconclusive & 14 negative samples by NIV assay were evaluated in the four commercially available RT-PCR kits ie;Q-line Molecular (Q-line), Allplex™ 2019-nCoV Assay (Allplex), Liferiver Novel Coronavirus (COVID-19) Multiplex RT PCR (Liferiver), LabGun™ COVID-19 kit (LabGun). Results:The sensitivity of the four PCR kits varied with the high cycle threshold (Ct) value (30-35 by NIV) & the lower Ct value (<30 by NIV). Among the negative results of NIV (n=14), LabGun, Allplex kits showed 100% concordance, while Q - line & Life river were shown to have 92.8% & 50% concordance respectively. In the inconclusive results (n=1), only All- plex Assay documented a concordance of 100% with the NIV assay, while the Q -line (n=6) & Life river (n=7) showed higher number of inconclusive results. The different kits showed lesser variations with positive results (n=5), with Life river, Allplex & LabGun showing 100% concordance for positive results with NIV assay. However, Q -line was able to de- tect only 1 positive out of all positives. Conclusions:PCR kits vary in sensitivity & it is imperial to evaluate the various kits in order to deliver accurate results at optimum time in order to detect the cases to initiate adequate treatment & control measures
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Aim: To implement postdischarge home-based kangaroo mother care (KMC) for low-birth-weight neonates during the SARS-CoV-2 pandemic through a quality-improvement (QI) initiative Materials and Methods: Neonates with a discharge weight of < 1800 g and their mothers were enrolled. The potential barriers for home-based KMC during the SARS-CoV-2 pandemic were evaluated using fishbone analysis, and a variety of measures were introduced in multiple Plan–Do–Study–Act (PDSA) cycles. Neonatal and maternal characteristics at the baseline and the implementation phases were compared using the Fisher’s exact test and unpaired t test. Data on implementation of home-based KMC and its duration (h/d) were analyzed using line charts or run charts. Results: A total of 29 eligible mother–neonate dyads were studied;the mean ± SD of the discharge weight and postmenstrual age of neonates was 1747 ± 187 g and 34.49 ± 2.07 weeks, respectively. After the implementation of 2 PDSA cycles, the percentage of home-based KMC increased from 37.5% (baseline) to 72.7%, and the median duration of KMC increased from 3 to 7 hours per day. Conclusion: Thorough evaluation of problems and proper QI measures helped in successfully implementing home-based KMC for the benefit of low-birth-weight neonates during the SARS-CoV-2 pandemic. © 2021, Himalaya Wellness Company. All rights reserved.
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The “Severe Acute Respiratory Syndrome-Corona Virus-2” (SARS-CoV-2) disease gives a challenge to the healthcare facilities and economic systems across the world. To overcome this COVID-19 pandemic different vaccines are produced across the world like Pfizer-BioNTech, Moderna, AstraZeneca-University of Oxford, Johnson & Johnson, Russia’s Sputnik V, Sinovac Biotech, Novavax, CanSino Biologics, and COVAXIN Bharat Biotech. These vaccines are injected to improved the immunity to fight against the SARS-CoV-2 infection. All these vaccine storage, efficiency, price are different and all vaccines work different variants of the virus. Some of the vaccines are mRNA type, Some are inactivated SARS-CoV-2, some are different. Our work is using the Multi-Criteria Decision Making (MCDM) technique, we ranking the vaccine with respect to different criteria. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The COVID-19 cases and the death toll are increasing in India with time so is the demand for an improved healthcare system. This critical situation demands a huge medical infrastructure with sufficient medical personnel. This pandemic has also led to an increase in demand for medical equipment in different parts of India, which is causing clinical consternations during treatment procedures. This paper confers the current situation being faced by the healthcare system in India and provide a descriptive analysis of the current situation, which would act as a situational guide for the policymakers. This paper has also reviewed recent literature on the current healthcare crises including the occurrence of mucormycosis in India and even highlights the shortcomings of the vaccination policy in the country. © 2021 New Zealand Mathematical Society and Department of Mathematics, University of Auckland.