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1.
44th AMOP Technical Seminar on Environmental Contamination and Response 2022 ; : 148-157, 2022.
Article in English | Scopus | ID: covidwho-1958484

ABSTRACT

Environment and Climate Change Canada’s (ECCC’s) Emergencies Science and Technology Section (ESTS) is tasked with providing scientific and technical advice to its federal partners during environmental emergencies including oil spill incidents. In addition, ESTS maintains a wide array of field instrumentation and equipment, which is available to support different areas of a spill response such as detection and monitoring, health and safety, and sampling. During a response, ESTS needs to quickly, and effectively, convey to ECCC Environmental Emergencies Officers what tools and equipment could be available for the response, and how they can help meet ECCCs objectives for the response. This can often be a challenge, especially when ESTS personnel cannot deploy on-site alongside the instrumentation and equipment, as the information must be provided in an easily understandable format, yet thorough enough to ensure proper usage of the particular tool or piece of equipment. To address these challenges, ESTS has begun the development of a suite of job aids or “Tactical Sheets”. Each Tactical Sheet contains necessary, condensed, information on a field method or equipment maintained by ESTS for use at an environmental emergency. The goal of these Tactical Sheets is to highlight what the specific objectives for ECCC are, and how a given piece of equipment or method can help meet that objective at a response. These Tactical Sheets come with a number of features including a standardized format, a visually appealing design layout, a required equipment list, a simplified procedure, and a summary of the typical use for the particular tool or piece of equipment. ESTS has begun trialing these Tactical Sheets at certain incidents throughout the Covid-19 pandemic to increase ESTS’ capability of providing remote support when on-site presence is not an option. These Tactical Sheets are meant to bolster ESTS’ portfolio of support options available to our partners during environmental emergency responses. This paper will present information on the program to update field methods used during an environmental emergency by ECCC. © 2022 44th AMOP Technical Seminar on Environmental Contamination and Response. All rights reserved.

2.
Medical Imaging 2022: Image Processing ; 12032, 2022.
Article in English | Scopus | ID: covidwho-1901888

ABSTRACT

We propose a fast and robust multi-class deep learning framework for segmenting COVID-19 lesions: Ground-Glass opacities and High opacities (including consolidations and pleural effusion), from non-contrast CT scans using convolutional Long Short-Term Memory network for self-attention. Our method allows rapid quantification of pneumonia burden from CT with performance equivalent to expert readers. The mean dice score across 5 folds was 0.8776 with a standard deviation of 0.0095. A low standard deviation between results from each fold indicate the models were trained equally good regardless of the training fold. The cumulative per-patient mean dice score (0.8775±0.075) for N=167 patients, after concatenation, is consistent with the results from each of the 5 folds. We obtained excellent Pearson correlation (expert vs. automatic) of 0.9396 (p<0.0001) and 0.9843 (p<0.0001) between ground-glass opacity and high opacity volumes, respectively. Our model outperforms Unet2d (p<0.05) and Unet3d (p<0.05) in segmenting high opacities, has comparable performance with Unet2d in segmenting ground-glass opacities, and significantly outperforms Unet3d (p<0.0001) in segmenting ground-glass opacities. Our model performs faster on CPU and GPU when compared to Unet2d and Unet3d. For same number of input slices, our model consumed 0.83x and 0.26x the memory consumed by Unet2d and Unet3d. © 2022 SPIE

3.
Lung India ; 39(SUPPL 1):S158-S159, 2022.
Article in English | EMBASE | ID: covidwho-1857718

ABSTRACT

Background: Covid-19 affected our population in multiple waves. We have looked for the differences in frequency and the weight/impact of symptoms between the first and the second waves. Method: The post-covid-19 subjects attending our out-patient department for post-covid-19 problems after the 1st and he 2nd waves were enquired retrospectively about the demography with the frequency and severity of different symptoms cough, breathlessness, throat pain, nasal discharge, fever, body-ache, weakness, diarrhoea, constipation, pedal/finger swelling, headache, expectoration. anosmia, and loss of taste) that they suffered from. The weight/impact of a symptom was derived by multiplying the duration of symptoms (in days) with the severity (in Likert scale;0 to 5;0=none and 5=maximum possible symptoms). The data was analysed statistically using unpaired 't-test' and 'chi-square test' to compare between the two covid-19 waves. Result: 185 and 222 subjects' data were included for the 1st and the 2nd waves of covid-19 respectively. The gender ratio was similar but the mean age was significantly lower in the victims of the second wave (56.17±13.64, 51.32±15.59;p=0.0017). As regards the symptom-frequency, fever (p=0.0154), constipation (p=0.0243), headache (p=0.0014), anosmia (p=<0.0001) and loss of taste (p=0.0009) were significantly worse in the 2nd wave. The symptom severity of cough (p=0.0184), throat pain (p=0.039), mild weakness (p=0.0063), anosmia (p=0.0004) and loss of taste (p=0.0026) were also higher in the 2nd wave of Covid-19. Conclusion: It appears that each wave of the pandemic was distinct as regards the symptomatology. Such peculiarity in the clinical dynamics of Covid-19 needs to be noticed and followed in future.

4.
Lung India ; 39(SUPPL 1):S130, 2022.
Article in English | EMBASE | ID: covidwho-1857120

ABSTRACT

Background: The second wave of Covid-19 had a huge number of asymptomatic, false negative (indeterminant) and symptomatic untested cases (query Covid). Objective: The aim is to understand the dynamics among these groups to know their impact on the spread of the diseases. Methods: In a prospective online survey we collected data using snowball sampling method via social media, from in and around Kolkata with the help of Google forms. The data included Covid related symptoms, evaluation, and behavior related to treatment during first and second wave of the disease. The discrepancies and duplicities were first excluded, and 989 respondents' data were statistically analyzed using SPSSver26. Results: The percentage of RT-PCR confirmed symptomatic and asymptomatic Covid cases were 21.84% (n=216) and 2.12% (n=21) respectively. Symptomatic but unconfirmed cases (query Covid) were 17.18% (n=170) and symptomatic false-negative cases (indeterminant) were 93 (9.40%). Rest 489 (49.44%) did not have any symptoms or never tested positive. The analysis revealed the reasons for doing RT-PCR test include a) less symptoms severity (47.06%), b)considering test unnecessary (22.94%),c) home collection unavailability(14.71%) and d)longer waiting time for results(8.82%). According to regression analysis, compared to confirmed Covid symptomatic group, only 47% [OR: 0.13(0.57-0.30) p<0.0001] of query covid patients consulted doctor for test or treatment and 21% [OR:9.55 (1.97-46.16), p<0.001] of indeterminant cases took medicine based on advice of friends/ relatives. Conclusion: There is a high percentage of untested (query Covid) and probable false negative cases (indeterminant) likely going unreported. The reasons for poor testing and seeking medical attention inadequately needs to be addressed and further investigated.

6.
Embase;
Preprint in English | EMBASE | ID: ppcovidwho-326611

ABSTRACT

Antiviral compounds displaying several remarkable features have been identified by a uniquely enabling drug screen and advanced through validation in two animal models, and in human primary bronchial epithelial cells grown to an air-liquid interface (ALI) and infected with SARS-CoV-2 (Brazil). Activity is observed in the nanomolar range in mammalian cells in vitro against the six viral families causing most human respiratory viral disease, irrespective of strain, including SARS-CoV-2 delta variant. A substantial barrier to development of viral resistance is demonstrated for influenza (FLUV). The drug target is an allosteric site on a novel host multiprotein complex (MPC) formed transiently, in an energy-dependent fashion, and composed of proteins implicated in viral lifecycles and innate immunity. The composition of this host MPC is modified in viral family-specific ways by FLUV and CoV, and substantially restored to the uninfected state with drug treatment. SQSTM1/p62, a key regulator of the autophagy pathway of innate immunity is i) found in the target MPC from uninfected cells, ii) lost upon infection, and iii) restored by drug treatment of infected cells, as assessed by drug resin affinity chromatography. A small subset of 14-3-3 is identified as the host protein to which the drug is bound. Advanced compounds with good oral bioavailability, half-life, lung exposure, and safety are approaching criteria for a Target Product Profile. We propose these novel drug targets to comprise a previously unappreciated molecular basis for homeostasis that is modified by viruses to facilitate their propagation and is restored by treatment with the therapeutic compounds presented. This discovery has transformative implications for treating respiratory viral-related disease, applicable to everything from COVID-19, seasonal influenza, common 'winter viruses' (respiratory syncytial virus, parainfluenza virus, rhinovirus, etc.), emerging respiratory viruses, and prevention of virus-induced asthma/COPD exacerbations. Treating respiratory viral disease with these host-targeted pan-respiratory viral family active compounds early, upon onset of symptoms of viral upper respiratory infection, irrespective of cause, should protect against progression to lower respiratory tract or systemic infection, the hallmarks of serious illness.

7.
Journal of Content, Community and Communication ; 14(8):197-209, 2021.
Article in English | Scopus | ID: covidwho-1687838

ABSTRACT

Covid-19 pandemic has impacted societal well-being in different and interacting contexts and its long duree consequences on human health, both biological and psychological serves to be a key element in the public discourse. The “pandemic-lockdown” in the Indian context made the health and social faultlines existing in the country hypervisible making one question the ‘normal’ we were existing with, in the pre-Covid times. As the virus took its toll on the fragile health system, nearly crushing it, individual’s rights to a safe and dignified life got threatened in the private spaces. The psycho-social effects of the pandemic arising from the exploitation in the public/private domains can be recognized as infringements with severe and sustained negative repercussions on the vulnerable sections of society. While analysing the intersecting vulnerabilities on varied fronts, another intense predicament related to women and elderly abuse in the (un)safe homely space awaits address and redressal. The nature of stressors underlying such abuse reflects on a complex interplay among several factors at an individual, community, and collective levels. The use of digital platforms, social media sites, and teleconsultation in moments of unprecedented crisis suggests towards creating an alternative paradigm for addressing the psychosocial dimension of the pandemic that lies intertwined with the “underlying injustices and social conditions”. In the backdrop of the Covid context, this paper would analyse how teleconsultation and telepsychiatry became an apparent channel to ensure health based services and extend support and safety to those victims and survivors of family abuse who remain marginalized in the society on sexist and ageist constructs © 2021,Journal of Content, Community and Communication.All Rights Reserved

8.
Indian Journal of Pharmaceutical Sciences ; 83(3):556-561, 2021.
Article in English | Web of Science | ID: covidwho-1332559

ABSTRACT

Favipiravir and remdesivir are investigational drugs for coronavirus disease 2019 that is caused by severe acute respiratory syndrome coronavirus 2. The active forms of these drugs are reported to target and inhibit viral RNA dependent RNA polymerase, which is derived from 3-chymotrypsin like protease, a viral replicase enzyme. The present in silico study explores the comparative efficacy of these drugs to inhibit 3-chymotrypsin like protease and RNA dependent RNA polymerase, to plan therapeutic options for patients based on their disease severity. Active favipiravir and remdesivir molecules bind to 3-chymotrypsin like protease with energies of 6.18 and -6.52 kcal/mol in contrast to -5.62 and -3.91 kcal/mol for RNA dependent RNA polymerase. Further, hydrophobic interactions and salt bridge formations cement drug bindings with 3-chymotrypsin like protease, but not with RNA dependent RNA polymerase. Molecular dynamic simulation experiments, performed under certain experimental constraints reveal that the root mean square flexibilities of active residues in drug complexes with 3-chymotrypsin like protease are lower than in free 3-chymotrypsin like protease making the former more stable than the latter because of their rigidity and stabilities. Both drugs may hence serve as good therapeutic options for early stages of coronavirus disease 2019. However, more severe symptoms may be treated better with favipiravir due to its better binding with RNA dependent RNA polymerase, as compared to remdesivir. The "one drug does not fit all" concept is true for coronavirus disease 2019 as it is being currently realized by clinicians all around the world. Hence precise knowledge about critical interactions of these drugs with the viral enzymes will help medicos make vital therapeutic decisions on interventional options for patients who report to hospitals without over symptoms or with varying degrees of disease severity.

9.
Indian Journal of Pharmaceutical Education and Research ; 55(2):517-526, 2021.
Article in English | Web of Science | ID: covidwho-1256937

ABSTRACT

Background: Drug development strategies for treating COVID-19 focus on actives that either physically block angiotensin-converting enzyme-2 (ACE-2) receptors (viral entry point), or those, which inactivate viral proteases like 3CLpro or RdRp, inside the infected host cells. Objectives: The objective of the present study is to virtually screen phytochemicals for both these purposes. Methods: Molecular docking, molecular dynamic simulation (MDS) and multiple sequence alignment were employed. Results: All the screened phytochemical actives showed negative binding energies with their respective targets, attesting good complex stabilities. Among each set of ten actives, for blocking ACE-2 receptors and for inactivation of 3CLpro and RdRp, Dichamanetin-ACE-2, Glabrene-3CLpro and Naringenin-RdRp complexes were most stable, with binding energies of -9.8, -9.11 and -7.7 Kcal/mol respectively. MDS studies of these representative actives and their complexes, also attested to complex stabilities. Multiple sequence alignment analysis of nine significant amino acid residues of the Homo sapiens ACE-2 receptor, with nine different species, showed conservation of several residues. Conclusion: A set of phytochemicals actives can block ACE-2 receptors and prevent the entry of SARS-CoV-2 into host endothelial cells. Two other sets of actives can inactivate viral 3CLpro and RdRp enzymes and prevent replication of SARS-CoV-2 inside host cells. They all can hence be further explored for the control of COVID-19.

10.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-8294

ABSTRACT

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of lung lesions is prohibitively time-consuming. We propose a new fully automated deep learning framework for rapid quantification and differentiation between lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional Long Short-Term Memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed 5 times with separate hold-out sets using 5-fold cross-validation to segment ground-glass opacity and high opacity (including consolidation and pleural effusion). The performance of the method was evaluated on CT data sets from 197 patients with positive reverse transcription polymerase chain reaction test result for SARS-CoV-2. Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score coefficient of 0.876 $\pm$ 0.005;excellent correlations of 0.978 and 0.981 for ground-glass opacity and high opacity volumes. In the external validation set of 67 patients, there was dice score coefficient of 0.767 $\pm$ 0.009 as well as excellent correlations of 0.989 and 0.996 for ground-glass opacity and high opacity volumes. Computations for a CT scan comprising 120 slices were performed under 2 seconds on a personal computer equipped with NVIDIA Titan RTX graphics processing unit. Therefore, our deep learning-based method allows rapid fully-automated quantitative measurement of pneumonia burden from CT and may generate results with an accuracy similar to the expert readers.

11.
J. Phys. Conf. Ser. ; 1797, 2021.
Article in English | Scopus | ID: covidwho-1139928

ABSTRACT

During this Covid - 19 pandemic situation, encryption of medical images takes a major role in medical information systems as well as in telemedicine. However according to government rule, it is essential to hide the information of the patients. Recent development in computer network enhances a lot of facilities in communication area. Unfortunately, hackers are misusing this facility and always try to attack on the transmitted information in insecure network. For secure transmission of medical images, it is essential to encrypt the information before transmitting. In this communication, we are going to present a novel approach of medical image encryption using cyclic coding. We have proved that it is quite difficult to decrypt the original information from encoded data in one common mode of attacking- chosen ciphertext attack. Moreover, we have proved the effectiveness of the encryption using correlation coefficients. Our proposed scheme is suitable for efficient encoding of multiple medical images. © 2021 Institute of Physics Publishing. All rights reserved.

12.
Foreign Trade Review ; 55(4):511-534, 2020.
Article in English | Web of Science | ID: covidwho-969390

ABSTRACT

The COVID pandemic seems to have raised the question, 'whether existing supply chain (SC) disruption philosophies and strategies continue to remain valid?'. This article assesses the differences in the business scenarios pre-and post-COVID. The authors capture the mathematical and operational relationships amongst the relevant factors and propose a System Dynamics (SD) model to carry out the simulations. The approach considers the impact of the force majeure condition, that is, COVID period on individuals' income, prices and demand of goods, cost of input and supply of finished goods. The results show that earnings may increase demand but, disruption in supplies of raw materials and finished products nullify the effect. On the other hand, even if flow returns to normal, reduced income affects normal goods businesses.

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