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Since the World Health Organization declared SARS-CoV-2 (COVID-19) a pandemic in March 2020, serious efforts have been made to understand the epidemiology, molecular mechanisms, pathology, and clinical evolution of this disease. Oxidative stress (OX-S) has been implicated in the etiologies of many diseases, including SARS-CoV-2. Recent studies suggest that superoxide radicals and the products of lipid peroxidation, such as the electrophilic aldehyde, 4-hydroxynonenal (4-HNE), are important mediators of the pathological effects of oxidative stress during microbial and viral infections. Numerous studies have confirmed that viral infections induce inflammatory responses that generate excessive amounts of reactive oxygen species and 4-HNE protein adducts in plasma and in various tissues, including alveolar epithelium and endothelium. In this book chapter, we will highlight and discuss the apparent and plausible relationships between SARS-CoV-2 virulence and oxidative stress/lipid peroxidation, which affect cellular and DNA repair mechanisms and immune response. © 2023 Elsevier Inc. All rights reserved.
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Background: India saw one of the stringent lockdowns during the COVID-19 pandemic. In the wake of this period, the normal functioning of medical services was affected. People were reluctant to seek medical attention and notification of Tuberculosis dipped. The aim of the study was to estimate the proportion of non-adherence to anti-tubercular treatment and to identify the factors affecting the non-adherence to treatment. Methods: A retrospective community-based study was conducted among 284 tuberculosis patients. They were interviewed using a pre-designed questionnaire consisting of WHO dimensions of non-adherence and lockdown related questions. Results: The proportion of non-adherence to treatment was found to be 5.3%. Factors like chronic diseases, depression, without knowledge on how the disease is transmitted and that medication can be discontinued once the symptoms subsided, alcohol consumption, and trouble accessing medicine were found to be the determining factors in non-adherence to the treatment. Conclusions: Non-adherence to anti-tuberculosis treatment in our study was low but the various dimensions of adherence along with lockdown related factors had significant impact on it. To further minimize non-adherence during emergency like the lockdown due to COVID-19 pandemic, corrective measures must be explored and implemented.
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Due to the fast advancement of Internet technology, the popularity of Online Social Networks (OSN) over the Internet is increasing day by day. In the modern world, people are using OSN to communicate with others around the world who may or may not know each other. OSN has become the most convenient means to transmit media (news/content) and gather or spread information in the world. The posts (contents) on OSN affect and impact people, and minds at least for some time. These contents are important because they play a crucial role in taking the decision. The posts which are available on the OSN may be information or just misinformation. The misinformation may be a type of fake news or rumour. This is very difficult for people to differentiate whether the posts are information or rumour. Therefore, the development of techniques that can prevent the transmission of false information or rumours that might harm society in any way is critical. In this paper, a model is developed based on the epidemic approach, for examining and controlling fake information dissemination in OSN. The proposed model illustrates how different misinformation debunking measures impact and how misinformation spreads among different groups. In this article, we explain that the proposed model will be able to recognize and eradicate fake news from OSN. The model is written as a system of differential equations. Its equilibrium and stability are also carefully examined. The basic reproduction number $(R_{0})$ is calculated, which is an important parameter in the study of message propagation in OSN. If $R_{0} < 1$ , the propagation of rumor in the OSN will be minimal;nevertheless, if $R_{0} > 1$ , the fake information/rumor will continue in OSN. The effects of disinformation of rumours in OSN in the real world are explored. In addition, the model covers the fake information/rumour dissemination control mechanism. The comparative study shows that the proposed model provides a better mechanism to prevent the dissemination of fake information in OSN in comparison to other previous models Extensive theoretical study and computation analysis have also been used to validate the proposed model © 2013 IEEE.
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Introduction: COVID-19 is caused by a novel virus and is known to be an infectious respiratory disease affecting more than 200 countries and union territories of the world. 80% of the patients are shown to have mild to moderate disease. Illness prevention is the mainstay of getting away from the condition with the non-availability of vaccines or medicine. Methods: The aim & objective of this study is to describe the behavioral insight (knowledge, attitude & practice) regarding preventive measures of COVID-19 among the teaching hospital staff. An institutional-based descriptive study was conducted among 168 staff, including lab technicians, doctors, staff nurses, and other supporting staff of a tertiary hospital using a convenient sampling technique. The data were obtained by interviewing staff with a pre-tested semi-structured schedule. Result: The study results showed that most of the respondents were found to have good knowledge, attitude, and practice towards preventive measures such as social distancing, hand hygiene, face mask, and PPE Kit. 88% of participants were using 3 layered medical masks, and most of them (63%) were using a regular wash of face mask. Among most respondents, no gap between knowledge and practice was seen;however, proper use, handling, and disposal of face masks and other PPE was a concern. Conclusion: Therefore, there is a need to improve the knowledge of COVID-19 among healthcare workers, which is possible with the availability of good quality Information Education and Communication (IEC) materials. © 2022 IJPH.
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Background: India saw one of the stringent lockdowns during the COVID-19 pandemic. In the wake of this period, the normal functioning of medical services was affected. People were reluctant to seek medical attention and notification of Tuberculosis dipped. The aim of the study was to estimate the proportion of non-adherence to anti-tubercular treatment and to identify the factors affecting the non-adherence to treatment. Methods: A retrospective community-based study was conducted among 284 tuberculosis patients. They were interviewed using a pre-designed questionnaire consisting of WHO dimensions of non-adherence and lockdown related questions. Results: The proportion of non-adherence to treatment was found to be 5.3%. Factors like chronic diseases, depression, without knowledge on how the disease is transmitted and that medication can be discontinued once the symptoms subsided, alcohol consumption, and trouble accessing medicine were found to be the determining factors in non-adherence to the treatment. Conclusions: Non-adherence to anti-tuberculosis treatment in our study was low but the various dimensions of adherence along with lockdown related factors had significant impact on it. To further minimize non-adherence during emergency like the lockdown due to COVID-19 pandemic, corrective measures must be explored and implemented. © The Author(s). 2022 Open Access.
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In the Covid-19 pandemic, if residents do not take action to prevent the virus from spreading, the process of softening the curve of the coronavirus will be complicated in the face of the worldwide Covid-19 scenario. Without vaccination, the only method to combat the disease is social isolation. The proposed system employs the You Only Look Once, Version 3 (YOLOv3) object detection model to identify persons in the background and bind boxes around them, and assign IDs for in-depth tracking of recognized people. This study focuses on public space surveillance and determining whether or not people maintain social distance as per Covid-19 guidelines. YOLOv3 is an efficient tracking method that produces positive results with a moderate mean Average Precision(MAP) and Frame Per Second (FPS) score for monitoring community deviations in real-Time. In this study, YOLOv3 is used for object capture, and the OpenCV library is used for image processing. Proposed work is helpful in areas where big crowds are expected, such as retail malls, movie theatres, railway stations, airports, and public places. © 2022 IEEE.
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The covid-19 pandemic was affected many sectors due to disintegration in work. The supply chain was affected and the firms had to face the labor shortage due to illness, death and travel restrictions. The goods could not reach the customers on time and the companies suffered a loss due to its deterioration. In this paper, we study about supply chain network for the cooperative dairy industry. We study how labor shortage affects the supply chain. We derive an equilibrium supply chain model with the labor shortage and risk factors to increase the company's profitability. In the end, we look at some examples that how profit is affected by the labor shortage. © 2021 IEEE.
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COVID-19 made a huge impact on the world due to its rapid transmission and no treatments being available for it. The virus affected more people and spread to various countries than what was predicted when COVID-19 initially began spreading. There have been numerous pandemics and epidemics in the 21st century yet COVID-19 has affected more people and spread widely. The primary objective of the study was to explore history, spread and associated parameters of existing viruses especially COVID-19. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed for a systematic search to identify eligible published articles. Clinical data, regarding COVID-19 patients, was obtained from previously published articles. The main cause of COVID-19 spreading rapidly was noted to be due to a high percentage of asymptomatic patients, transmission being air-borne, and the lack of knowledge and preventative measures being implemented when the virus began spreading. The common co-morbidity that found in patients was Diabetes Mellitus, Hypertension, and Coronary Heart Disease. The common symptoms, found through the Meta-analysis, that the patients faced included cough (55.4%), fever (68.4%), fatigue (20.3%), and shortness of breath (18.1%). The proportion of asymptotic positive cases was measured 58.3% (95%CI: 24.7% - 87.9%) while mortality proportion was found to be 6.7% (fixed-effect model) and 13.4% (random-effect model). The Meta-analysis indicated that a higher percentage of males were affected by COVID-19 than females and more patients are found to be asymptomatic. Moreover, the mortality rate of patients that have had COVID-19 was found to be low.