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1.
Economic Research-Ekonomska Istrazivanja ; : 15, 2022.
Article in English | English Web of Science | ID: covidwho-1882858

ABSTRACT

We examine the impact of the recent restrictions/bans imposed by several nations on air travel to India in the light of the increasing number of infections amid the second wave of covid-19. We employ the standard event study method on a sample of 34 airline stocks across seven nations to find that the recent restrictions/bans on air travel significantly impact the global airline industry, although the country-specific impacts are not similar. We find that the post-event reaction in all nations has been different from those evidenced during the global pandemic declaration. We are the first to examine these impacts during the current wave of the pandemic. It contributes to the literature on the effects of the pandemic on the global airline industry. Further, it also provides practical explanations to the investors on how the airline stocks react to the persistence of the pandemic.

2.
American Journal of Respiratory and Critical Care Medicine ; 205:3, 2022.
Article in English | English Web of Science | ID: covidwho-1880424
3.
Applications of Computational Intelligence in Multi-Disciplinary Research ; : 187-204, 2022.
Article in English | Scopus | ID: covidwho-1872835

ABSTRACT

In recent years, IoT has been revolutionizing the technology landscape, leading to explosive growth in fields like automated manufacturing, asset management, and wearable consumer healthcare products. IoT’s presence can be seen in all domains. Ever since IoT gained its entry into the medical field, there has been a magnificent transformation in the healthcare domain. Personal healthcare is now made a reality with IoT offering solutions in several dimensions like remote healthcare;smart clothing such as smartwatches, smart bands, and smart pants;and telemedicine like smart pills and personal care robots. This chapter gives a comprehensive walkthrough of IoT in the healthcare ecosystem, addressing the different applications of IoT in healthcare, the architecture models, challenges faced by IoT in healthcare, security practices and issues, and the future of IoT in the domain. In the first section, IoT applications in healthcare are discussed, which include patient-centric applications like remote health monitoring and critical care monitoring;and hospital-centric IoT applications such as the deployment of the staff, reducing charting times, and real-time location of medical equipment, subsequently followed by a discussion on how the data collected from the patient-centric and hospital-centric applications contribute to the ease of other domains like health insurance;and then, IoT’s support toward the pharmaceutical industry to restrict counterfeit medicine is discussed. Secondly, the implementation designs of healthcare IoT are discussed. Apart from the traditional cloud services, new offerings like fog and edge computing have seen a spike in recent years. Fog and edge computing are considered intelligent and flexible architectures. The subsequent section deals with architecture designs and the advantages and challenges of the two computing models. The next section demonstrates the actual implementation methodologies of the two applications in the following domains in detail: (1) Heart disease prediction and (2) healthcare IoT-based affective state mining using deep convolutional neural networks. The following section discusses the challenges faced by IoT in the healthcare domain. In general, the challenges can be categorized into technological challenges;people-oriented challenges like the acceptance of IoT in the healthcare domain;and finally, security bottlenecks. The data generated and maintained by the IoT platforms serves as a gold mine for different healthcare professionals for future research and development in the medical field and the health insurance providers and pharmaceutical industries for their benefits. Hence, more emphasis is given to the security and privacy aspects of how the domain handles sensitive data of the patients. The next section provides insights into the security issues along with the cyber threats and attacks faced by healthcare IoT and the defensive mechanisms. Furthermore, this chapter deals with the IoT’s role in combatting the novel coronavirus that has caused an unprecedented global pandemic. Finally, the future of IoT is talked about. With the advent of 5G and an upsurge in artificial intelligence, the different dimensions of the IoT that are expected to see an outburst of growth are discussed. © 2022 Elsevier Inc. All rights reserved.

4.
Lung India ; 39(SUPPL 1):S136-S137, 2022.
Article in English | EMBASE | ID: covidwho-1857457

ABSTRACT

Background: Mucormycosis is an invasive-fungal infection, often associated with extremely severe complications in immuno-compromised patients. The prevalence of mucormycosis in India is about 80 times higher than other developed countries. But the clinical presentation of pulmonary mucormycosis has wide diversity. Case Study: We are reporting a case of a 45-year-old man admitted to our side as a case of post-COVID sequelae in the setting of a new left sided loculated pyo-pneumothorax. He is a known case of type 2 diabetes and hypothyroidism for 1.5 years and 3 years respectively. Prior to our rescue, he underwent pigtail insertion in the loculated collection, but there was no output. So, the drain was removed and the patient was planned for pneumonectomy. On visiting to our side, appropriate investigation and interventions were done. On bronchoscopy a large fungating fragile blackish growth was seen coming out from left main bronchus. Histopathological report of the endobronchial biopsy revealed mucormycosis. The patient was planned for Liposomal Amphotericin-B (LAMB) but unfortunately developed anaphylaxis. He was managed accordingly and was taken on oral Posaconazole therapy. On follow up visit remarkable clinical and radiological improvement was noted. Discussion: The above-mentioned case showed the management of a not so mimicking case of usual pulmonary mucormycosis without opting for surgical intervention. Thus, limiting the patient from the postsurgical complications. Conclusion: This case illustrates the heterogeneousness of mucormycosis, regardless of patient profile. Bronchoscopic findings and mycology report helped us to rule out other differential diagnosis.

5.
Lung India ; 39(SUPPL 1):S40-S41, 2022.
Article in English | EMBASE | ID: covidwho-1857233

ABSTRACT

Background: There are many complications seen post covid ranging from fatigue, headache, shortness of breath to serious conditions like opportunistic infections, deep venous thrombosis, pulmonary embolism, pneumothorax, lung fibrosis etc. The number of ACE-2 receptors is increased in various organs and this is responsible for the spread of the virus throughout the body, where it produces proinflammatory and profibrotic responses, thus leading to the various complications. Methods: Patients recovered from COVID-19 infection previously both clinically and microbiologically who had new onset of symptoms for which they presented to the OPD or emergency of the Department of Respiratory Medicine were included in the study. Repeat RTPCR negative patients, and age less than 18 years were excluded. Results: Mortality and complications of COVID-19 are more common in males than females. Patients with preexisting metabolic disorders like obesity, type 2 diabetes mellitus, hypertension, non-alcoholic fatty liver disease being inflammatory conditions, not only exhibit an elevated cytokine storm, but are also directly associated with increased replication of the coronavirus. age more than 70 years may have other factors contributing to the increased risk of complications. Patients with severe illness who needed invasive ventilations or long duration of hospital stay were more prone for tissue damage that led to persistent symptoms. The most common post covid symptoms are fatigue, shortness of breath, anosmia and mental disorders. However more serious conditions that includes hematological complications like blood coagulation, pulmonary complications like respiratory failure, pulmonary fibrosis, pulmonary thromboembolism, pneumothorax, pulmonary infections, cardiovascular complications like deep venous thrombosis, myocardial infarction etc. can also occur. Conclusion: COVID-19 is associated with a lot of complications there causes need to be studied in detail.

6.
Journal of Integrated Science and Technology ; 10(2):61-66, 2022.
Article in English | Scopus | ID: covidwho-1843221

ABSTRACT

Due to a lack of data on various parameters with COVID-19 in the Indian population, this study was carried out to understand the relation among gender, age and comorbidities in Indian population. The data was collected using a questionnaire-based survey form that included questions on demographic characteristics, infection and any pre-underlying conditions (n=1146). The data showed that the male patients had suffered more from COVID-19 (58.6%). Also, the patients suffering from comorbidity are more likely to suffer from a severe form of COVID-19 and obesity/overweight was identified as the most prevalent (n=69) comorbid condition, followed by diabetes (n=35), thyroid (n=19) and hypertension (n=11). In severe COVID-19 cases, 85% of patients had a comorbid condition. In another study of COVID-19 hospitalized-cases, about 97% of patients were found to have an underlying medical condition. Among these, diabetes (55.9%) was identified as the most prevalent comorbidity. Males and older people are at a higher risk of developing COVID-19 infection in Indian population. The comorbid conditions also predisposed individuals to COVID-19 and aggravated the infection. © 2022. ScienceIN.

7.
Texila International Journal of Public Health ; 9(4), 2021.
Article in English | GIM | ID: covidwho-1841775

ABSTRACT

The COVID-19 caused by novel single-stranded RNA enveloped severe acute respiratory syndrome coronavirus-2 (SARS CoV-2) first appeared in Wuhan, China. A lot of focus has been given to pulmonary complications. According to several case reports, cardiovascular associated clinical manifestations include myocarditis, arrhythmias, veno-thromboembolic events, acute coronary syndrome (ACS), and pericarditis. Different modalities in diagnosis like 2D, doppler can help in the early diagnosis of right ventricular function. This study evaluates the cardiac changes in recovered COVID-19 positive patients by 2D echocardiogram and other modalities. In this prospective observational study, 139 participants recently recovered from COVID-19 illness were identified and recruited after obtaining the Informed concerned form (ICF). The patients once enrolled were subjected to 2D echo and ECG as part of routine clinical practice. Out of 139 patients, 89 (64.03%) were males, and the rest were females. Based on the severity scale, 13 (9.35%) participants had suffered a severe form of COVID-19 infection. Right ventricular functional assessment, right ventricular global strain (RVGLS) was abnormal in 72 (51.80%) participants. Arrhythmias were reported in 31 (22.30%) participants;among them, 30 participants had sinus bradycardia. Our study demonstrates the association between COVID-19 and cardiac changes/ incidence of cardiovascular complications in recovered COVID-19 patients. This study provides first-hand evidence of the incidence of abnormal LVGLS and RVGLS in COVID-19 recovered patients. In addition, there was a higher incidence of arrythmias.

8.
International Journal of Electronic Finance ; 11(2):175-187, 2022.
Article in English | Scopus | ID: covidwho-1833690

ABSTRACT

The present study investigates the impact of COVID-19 on the volatility of BSE Sensex stock index. The weekly data on COVID-19 fatality cases, an independent variable, in India from 1 March 2020 to 27 December 2020 has been taken from the official website of the World Health Organization. The weekly data on a dependent variable (Sensex) and control variables (crude oil, Bitcoin, Ethereum, Litecoin) have also been considered for the period under study. The GARCH(1, 1) model has been used to extract the volatility series of the variables that are considered in the investigation, and vector error correction model (VECM) is also applied. Further, robust tests like ADF, variance decomposition test, impulse response test have been performed to check the validity of the results. The findings suggest the significant negative effect of COVID-19 fatality cases on BSE Sensex stock index during the specified study period. This negative coefficient of COVID-19 fatality cases in India reflects the increasing volatility of the BSE Sensex stock index. © 2022 Inderscience Enterprises Ltd.

9.
12th International Conference on Computer Communication and Informatics, ICCCI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1831783

ABSTRACT

This paper presents the precautionary robot which can warn and also help the people from affecting with deadly corona virus. We know that the Novel Corona virus had shown a great impact on the world population, many of the people are dying due to this deadly virus because of not following the safety measures and not taking any precautions to overcome the virus.Health-care workersare playing a major role in this pandemic by helping the affected patients to recover from the virus infections. Not only health-care workers but also robots are playing a major part in this pandemic. Robots are being used in laboratories and hospitals for various purposes like disinfection, spraying, manufacturing of medicines/vaccines, surveillance and many more applications. Robots are also equally contributed as healthcare workers around the world to adapt the present needs in order to combat with COVID-19. Mainly in this pandemic robot act as a tool, used in applications which are focused primarily in the area of health and services. The proposed work is to design and implement a robot for the covid applications. This robot is proposed by analyzing the present day's scenario on this pandemic. The proposed robot is user friendly and works particularly for 4 functions like mask detection on people, sanitizer spraying/disinfecting, temperature detection, and finally moving from one place to another place in the hospital or wherever it is required. © 2022 IEEE.

10.
Journal of SAFOG ; 14(1):35-40, 2022.
Article in English | EMBASE | ID: covidwho-1822541

ABSTRACT

Importance: Given the high mortality and cost of health care, especially in isolation settings, the idea of using nebulized hydrogen peroxide may play a very significant role in inactivation of coronavirus, thus reducing the infectivity period leading to reduced requirement of isolation and improving morbidity and mortality in people suffering with coronavirus disease-2019 (COVID-2019). Aim and objective: Objective of this study was to determine the efficiency of nebulized hydrogen peroxide (H2O2) in reducing the viral load and disease severity of patients suffering with COVID-19. Design: Double-blinded randomized control trial. HOPE in COVID-19 study. Setting: Tertiary care COVID hospital (single center). Participants: Moderate sick COVID-19-positive patients were included in the study after they qualified the inclusion criteria. Intervention: Patients were nebulized using 1 mL of ozonized 3% H2O2 after diluting with 4 mL of normal saline three times a day for 5 days. The control group was nebulized with normal saline only. Main outcome: Outcome was assessed for reduction in oxygen requirement (number of days on oxygen), symptoms resolution (dyspnea, cough, and fever), and number of days it took to be RT-PCR negative for COVID-19. Results: The early data from trial showed promising trends toward a better outcome. The study showed that in the case group who were nebulized with hydrogen peroxide resulted in better outcome in terms of parameters assessed in the study and the differences from the control group were statistically significant (p ≤0.001, CI 95%). Outcome in the form of mortality (odds ratio 0.29, 95% CI 0.02–3.14, p = 0.31, z = 1.007) was statistically insignificant. The number needed to treat for our study was 10.

11.
Neurology Asia ; 27(1):117-123, 2022.
Article in English | Web of Science | ID: covidwho-1798520

ABSTRACT

Background & Objective: Neurological manifestations of novel-coronavirus disease (COVID-19) have been described in various studies. None of these studies has compared the findings in COVID-19 patients with COVID-negative patients presenting with similar clinical symptomatology during the same period. We undertook this case-control study with an aim to establish a direct relationship between COVID-19 infection and CNS related clinical and imaging presentations. Methods: This study was a review of retrospectively collected data of the patients who presented with different neurological symptoms to a tertiary care hospital in India. Based on results of Reverse transcriptase-polymerase chain reaction for SARS-Co-V-2, patients were classified into COVID-19 positive and COVID-19 negative groups. MRI findings in both groups were reviewed for acute ischemic stroke, intracranial bleed and other acute imaging abnormalities. Basic demographic information and stroke-related co-morbidities were also compared. Results: Eighty four patients in COVID-19 positive group and 323 patients in COVID-19 negative group underwent brain MRI for acute neurological symptoms during the same period. There was no statistically significant difference in presenting symptoms, sex distribution and risk factors for stroke. There was a higher prevalence of increased coagulability in COVID-19 positive group (p-value = 0.009). No statistically significant association was observed for infarcts or their hemorrhagic transformation, intracranial bleed, intracranial infection or dural sinus thrombosis. An association was found between acute diffuse leukoencephalopathy and COVID-19 infection (p value < 0.05). Conclusion: The current study points towards a weak direct association between COVID-19 infection and acute abnormalities in MRI brain studies, especially in patients with pre-existing co-morbidities.

12.
Indian Pediatr ; 59(4):339-340, 2022.
Article in English | PubMed | ID: covidwho-1782131

ABSTRACT

Multisystem inflammatory syndrome in children (MIS-C) is notorious for its cardiac involvement. We present a single center data of 71 children, of which 57.7% had myocarditis and 26.8% had coronary artery aneurysms. 45.1% required intensive care support and 29.6% needed inotropes - 91.5% received IVIG.  All patients responded to therapy with no mortality.

13.
3rd International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2021 ; : 2027-2030, 2021.
Article in English | Scopus | ID: covidwho-1774619

ABSTRACT

The proposed research aims at the analysis of spread of coronavirus and factors that contributed significantly in the rise or fall of death rate by correlating it with various social indicators. We will be using data analytics and visualization techniques to get significant insights from data collected from World Health Organization (WHO), John Hopkins University and other data repositories and reputable sources. © 2021 IEEE.

14.
Appl Soft Comput ; 122: 108780, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1763588

ABSTRACT

Ever since the outbreak of COVID-19, the entire world is grappling with panic over its rapid spread. Consequently, it is of utmost importance to detect its presence. Timely diagnostic testing leads to the quick identification, treatment and isolation of infected people. A number of deep learning classifiers have been proved to provide encouraging results with higher accuracy as compared to the conventional method of RT-PCR testing. Chest radiography, particularly using X-ray images, is a prime imaging modality for detecting the suspected COVID-19 patients. However, the performance of these approaches still needs to be improved. In this paper, we propose a capsule network called COVID-WideNet for diagnosing COVID-19 cases using Chest X-ray (CXR) images. Experimental results have demonstrated that a discriminative trained, multi-layer capsule network achieves state-of-the-art performance on the COVIDx dataset. In particular, COVID-WideNet performs better than any other CNN based approaches for diagnosis of COVID-19 infected patients. Further, the proposed COVID-WideNet has the number of trainable parameters that is 20 times less than that of other CNN based models. This results in fast and efficient diagnosing COVID-19 symptoms and with achieving the 0.95 of Area Under Curve (AUC), 91% of accuracy, sensitivity and specificity respectively. This may also assist radiologists to detect COVID and its variant like delta.

15.
18th IEEE India Council International Conference, INDICON 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1752412

ABSTRACT

In India, the second wave of the COVID-19 pandemic has resulted in a significant shortage of medicines and increased morbidity. COVID-19 has also had a profound influence on the psychological well-being of health professionals, who are surrounded by agony, death, and isolation as a result of the epidemic. The goal of this cross-sectional study is to look into the mental health of Indian healthcare workers during the second wave of the COVID-19 outbreak. From March 2021 to May 2021, a self-administered questionnaire based on the COVID-19 Stress Scale was delivered online to healthcare professionals (N = 836) in north India. An ensemble learning technique - Extreme Gradient Boosting (XGBoost) was applied to predict individual stress levels with 10-fold cross-validation. XGBoost had predicted stress with an average accuracy of 0.8889. According to the findings of this study, around 52.6 percent of healthcare professionals in the sample meet the threshold for severe psychiatric morbidity. In addition, advanced methodologies (SHAP values) were employed to determine which features had a significant impact on stress prediction. Medicine shortages and trouble concentrating were found to be the two most significant CSS predictors. © 2021 IEEE.

16.
6th International Conference on Image Information Processing, ICIIP 2021 ; 2021-November:405-408, 2021.
Article in English | Scopus | ID: covidwho-1741198

ABSTRACT

Chronic Obstructive Pulmonary Disease is the 2nd most common genesis of Non-Communicable Diseases (NCD)-related deaths in India. Not everyone had the chance to go to a medical facility or hospital for problems/diseases other than COVID-19 amidst lockdown as there was uncertainty of getting infected by COVID-19. To cater this issue this device/software can detect and diagnose diseases such as pneumonia, heart failure, chronic obstructive pulmonary disease (COPD), emphysema, asthma, bronchitis, foreign body in the lungs or airways etc. This process uses methodology of signal, sound and audio processing and image analysis. Normal sound samples of healthy human body would be taken in consideration and then be compared with the samples of the person whom it is tested on, different levels or frequency range of sounds/body noises that a person makes differs in different analysis, for example 'crackles' these are high pitched breath sounds made when the small air sacs get liquid filled and the person may have pneumonia or a heart failure. This not only work as a warning system that is early but also can reduce human workload and can deplete human error while using a stethoscope for the same. © 2021 IEEE.

17.
6th International Conference on Image Information Processing, ICIIP 2021 ; 2021-November:152-157, 2021.
Article in English | Scopus | ID: covidwho-1741192

ABSTRACT

The COVID-19 epidemic has forced several organizations to undergo major shift, to examine essential aspects of their economic cycles and to make use of invention to maintain activities whilst maintaining a shifting rule scene and unique method. This review provides a comprehensive understanding via a framework of facts and an original approach of huge no of key issues and fundamental subtleties impacting organizations and society from COVID-19. The views for different welcoming industry professionals are analyzed and broken down when the specific interpretations may be understood Web learning, modern technology, man-made brainpower, data board, social communication, security of networks, information giant, blockchain, security, multi-faceted invention and approach from the present emergency standpoint and influence on such specific areas. The master perspectives give the extent of the elements optimum comprehension, distinguishing central questions and proposals for hypothesis and practice by utilizing chest X-Ray pictures with ML approach. In the paper, the use of these ML methods to cope with the COVID-19 pandemic flow situation is a promising aspect, just as the prevention of Covid infection model is proposed. Result shows the proposed hybrid approach gives better accuracy as compared to other © 2021 IEEE.

18.
6th International Conference on Image Information Processing, ICIIP 2021 ; 2021-November:422-426, 2021.
Article in English | Scopus | ID: covidwho-1741191

ABSTRACT

Coronavirus Disease or COVID-19 pandemic has taken over the world by storm. It has horrifying effect on the health of the people. Continuously rising number of COVID-19 cases has and still creating huge stress on the governing bodies of all countries, and they are finding it hard to find solution for the situation. This project's goal is to explore machine learning and develop a COVID-19 model that can predict number of cases with high accuracy. The proposed study employs SVR and PR models to forecast the number of recovered cases, confirmed cases, deaths, and daily case count. The data is collected from the 1st of March to the 30th of April 2020. The confirmed number of cases as of April 30th were 35043, with 1147 total deaths and 8889 recovered patients. The model was created in Python 3.8.5. We will look at various machine learning prediction algorithms and compare them. In conclusion, supervised learning algorithms proved to be better than unsupervised learning algorithms. These prediction models can help us to brace for another COVID-19 wave and to ensure the availability of the required resources. © 2021 IEEE.

19.
J Hosp Infect ; 122: 173-179, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1729910

ABSTRACT

BACKGROUND: An unprecedented rise in the number of COVID-19-associated mucormycosis (CAM) cases has been reported in India. Myriad hypotheses are proposed for the outbreak. We recently reported uncontrolled diabetes and inappropriate steroid therapy as significant risk factors for the outbreak. However, Mucorales contamination of hospital environment was not studied. AIM: To perform a multi-centre study across India to determine possible Mucorales contamination of hospital environment during the outbreak. METHODS: Eleven hospitals from four zones of India representing high to low incidence for mucormycosis cases were included in the study. Samples from a variety of equipment used by the patients and ambient air were collected during May 19th, 2021 through August 25th, 2021. FINDINGS: None of the hospital equipment sampled was contaminated with Mucorales. However, Mucorales were isolated from 11.1% air-conditioning vents and 1.7% of patients' used masks. Other fungi were isolated from 18% of hospital equipment and surfaces, and 8.1% of used masks. Mucorales grew from 21.7% indoor and 53.8% outdoor air samples. Spore counts of Mucorales in air were significantly higher in the hospitals of North and South zones compared to West and East zones (P < 0.0001). Among Mucorales isolated from the environment, Rhizopus spp. were the most frequent genus. CONCLUSION: Contamination of air-conditioning vents and hospital air by Mucorales was found. Presence of Mucorales in these areas demands regular surveillance and improvement of hospital environment, as contamination may contribute to healthcare-associated mucormycosis outbreaks, especially among immunocompromised patients.


Subject(s)
COVID-19 , Mucorales , Mucormycosis , Disease Outbreaks , Hospitals , Humans , India/epidemiology , Mucormycosis/epidemiology
20.
3rd IEEE Bombay Section Signature Conference, IBSSC 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1713999

ABSTRACT

As per researchers worldwide, the practice of social distancing and wearing masks may have to be continued till the end of 2022 or even after considering the deadly and unpredictable nature of the COVID-19 virus that has gripped our world. In spite of all the rules and regulations in place we still find people breaking the rules. Also, it is to be noted that many officials who are tasked with enforcing the rules have either been severely affected or have lost their lives. Our work focuses on creating a holonomic robot, that can detect violations to mask and social distancing rules and generate alerts. Our work uses OpenCV and CNN model for face mask detection and pre-trained Mobile-Net Single Shot Object Detection (SSD) model to detect people and check if social distancing is adhered to. © 2021 IEEE.

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