An integrated sustainable medical supply chain network during COVID-19

Multi-level impacts of the COVID-19 lockdown on agricultural systems in India: The case of Uttar Pradesh

Purpose Many investigations are going on in monitoring, contact tracing, predicting and diagnosing the COVID-19 disease and many virologists are urgently seeking to create a vaccine as early as possible Even though there is no specific treatment for the pandemic disease, the world is now struggling to control the spread by implementing the lockdown worldwide and giving awareness to the people to wear masks and use sanitizers The new technologies, including the Internet of things (IoT), are gaining global attention towards the increasing technical support in health-care systems, particularly in predicting, detecting, preventing and monitoring of most of the infectious diseases Similarly, it also helps in fighting against COVID-19 by monitoring, contract tracing and detecting the COVID-19 pandemic by connection with the IoT-based smart solutions IoT is the interconnected Web of smart devices, sensors, actuators and data, which are collected in the raw form and transmitted through the internet The purpose of this paper is to propose the concept to detect and monitor the asymptotic patients using IoT-based sensors Design/methodology/approach In recent days, the surge of the COVID-19 contagion has infected all over the world and it has ruined our day-to-day life The extraordinary eruption of this pandemic virus placed the World Health Organization (WHO) in a hazardous position The impact of this contagious virus and scarcity among the people has forced the world to get into complete lockdown, as the number of laboratory-confirmed cases is increasing in millions all over the world as per the records of the government Findings COVID-19 patients are either symptomatic or asymptotic Symptomatic patients have symptoms such as fever, cough and difficulty in breathing But patients are also asymptotic, which is very difficult to detect and monitor by isolating them Originality/value Asymptotic patients are very hazardous because without knowing that they are infected, they might spread the infection to others, also asymptotic patients might be having very serious lung damage So, earlier prediction and monitoring of asymptotic patients are mandatory to save their life and prevent them from spreading

Detection and monitoring of the asymptotic COVID-19 patients using IoT devices and sensors

SARS-CoV-2 is a novel virus, responsible for causing the COVID-19 pandemic that has emerged as a pandemic in recent years. Humans are becoming infected with the virus. In 2019, the city of Wuhan reported the first-ever incidence of COVID-19. COVID-19 infected people have symptoms that are related to pneumonia, and the virus affects the body's respiratory organs, making breathing difficult. A real-time reverse transcriptase-polymerase chain reaction (RT-PCR) kit is used to diagnose the disease. Due to a shortage of kits, suspected patients cannot be treated promptly, resulting in disease spread. To develop an alternative, radiologists looked at the changes in radiological imaging, like CT scans, that produce comprehensive pictures of the body of excellent quality. The suspected patient's computed tomography (CT) scan is used to distinguish between a healthy individual and a COVID-19 patient using deep learning algorithms. A lot of deep learning methods have been proposed for COVID-19. The proposed work utilizes CNN architectures like VGG16, DeseNet121, MobileNet, NASNet, Xception, and EfficientNet. The dataset contains 3873 total CT scan images with “COVID” and “Non-COVID.” The dataset is divided into train, test, and validation. Accuracies obtained for VGG16 are 97.68%, DenseNet121 is 97.53%, MobileNet is 96.38%, NASNet is 89.51%, Xception is 92.47%, and EfficientNet is 80.19%, respectively. From the obtained analysis, the results show that the VGG16 architecture gives better accuracy compared to other architectures.

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COVID-19 Detection Based on Lung Ct Scan Using Deep Learning Techniques

Education institutions like Schools, colleges, and universities in India are currently based on traditional learning methods and follow the conventional setting of face-to-face interaction/lectures in a classroom. Most of the academic sector started unified learning, still most of them struct with old steps. The unexpected Plague of a deadly infection called COVID-19 caused by (SARS-Cov-2) trembled the whole world. The WHO announced it as a disease outbreak. This circumstance challenged the whole education system worldwide and compelled educators to change to an online mode immediately. Many educational organizations that were earlier unwilling to change their traditional didactic practice had no choice but to move exclusively to online teaching–learning. This article provides an elaborate discussion about the education sector's impact during a disease outbreak in India. It offers a detailed discussion regarding how India adopts the e-learning approach in this critical situation. Further, it describes how to cope with the challenges related to e-learning.

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Adoption of E-Learning during Lockdown in India

The situations of COVID-19 will certainly have an adverse effect over and above health care on factors of the internet of things (IoT) market. To overcome all the above issues, IoT devices and sensors can be used to track and monitor the movement of the people, so that necessary actions can be taken to prevent the spread of coronavirus disease (COVID-19). Mobile devices can be used for contact tracing of the affected person by analyzing the geomap of the travel history. This will prevent the spread and reset the economy to the normal condition.,To respond to the global COVID-19 outbreak, the social-economic implications of COVID-19 on specific dimensions of the global economy are analyzed in this study. The situations of COVID-19 will certainly have an adverse effect over and above health care on factors of the IoT market. To overcome these issues IoT devices and sensors can be used to track and monitor the movement of the people so that necessary actions can be taken to prevent the spread of COVID-19. Mobile devices can be used for contact tracing of the affected person by analyzing the geomap of the travel history. This will prevent the spread and reset the economy to the normal condition. A few reviews, approaches, and guidelines are provided in this article along these lines. Moreover, insights about the effects of the pandemic on various sectors such as agriculture, medical industry, finance, information technology, manufacturing and many others are provided. These insights may support strategic decision making and policy framing activities for the top level management in private and government sectors.,With insecurities of a new recession and economic crisis, key moments such as these call for strong and powerful governance in health, business, government, and large society. Instant support measures have to be initiated and adapted for those who can drop through the cracks. Mid- and long-term strategies are required to stabilize and motivate the economy during this recession.,A comprehensive social-economic development strategy that consists of sector by sector schemes and infrastructure that supports business to ensure the success of those with reliable and sustainable business models is necessary. From the literature analysis and real world observations it is concluded that the IoT, sensors, wearable devices and computational technologies plays major role in preserving the economy of the country by preventing the spread of COVID-19.

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Jayalakshmi P

Papers

Social economic impact of COVID-19 outbreak in India