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1.
Aging (Albany NY) ; 14(11): 4624-4633, 2022 Jun 02.
Article in English | MEDLINE | ID: covidwho-1879716

ABSTRACT

Since the late 2020, the evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern has been characterized by the emergence of spike protein mutations, and these variants have become dominant worldwide. The gold standard SARS-CoV-2 diagnosis protocol requires two complex processes, namely, RNA extraction and real-time reverse transcriptase polymerase chain reaction (RT-PCR). There is a need for a faster, simpler, and more cost-effective detection strategy that can be utilized worldwide, especially in developing countries. We propose the novel use of direct RT-qPCR, which does not require RNA extraction or a preheating step. For the detection, retrospectively, we used 770 clinical nasopharyngeal swabs, including positive and negative samples. The samples were subjected to RT-qPCR in the N1 and E genes using two different thermocyclers. The limit of detection was 30 copies/reaction for N1 and 60 copies/reaction for E. Analytical sensitivity was assessed for the developed direct RT-qPCR; the sensitivity was 95.69%, negative predictive value was 99.9%, accuracy of 99.35%, and area under the curve was 0.978. This novel direct RT-qPCR diagnosis method without RNA extraction is a reliable and high-throughput alternative method that can significantly save cost, labor, and time during the coronavirus disease 2019 pandemic.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19 Testing , Clinical Laboratory Techniques/methods , Cost-Benefit Analysis , Humans , RNA, Viral/genetics , Real-Time Polymerase Chain Reaction/methods , Retrospective Studies , SARS-CoV-2/genetics , Sensitivity and Specificity
2.
2022 IEEE Delhi Section Conference, DELCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1846074

ABSTRACT

Immunisation is the procedure of providing a vaccine to a person in order to protect him or her against disease. This process has been widely recognized and adopted as one of the world's most successful and cost-effective health interventions. Vaccines have been saving millions of lives worldwide from deadly infectious diseases and viruses, such as hepatitis, measles and polio. However, the COVID outbreak in the late 2019 has witnessed huge devastation on the global health front. For now, vaccine is the only cost-effective health intervention to control the spread of virus and completely eradicating it. Technological breakthroughs are making a significant contribution to the improvement of healthcare. Blockchain technology is one example of such a disruptive technology. Blockchains have the potential to improve the healthcare system in a variety of ways. In this paper, we have thoroughly discussed how we can create vaccine awareness across the globe by focusing on parents, healthcare workers, frontline workers, policymakers, media, and ultimately how everyone must work together to ensure that every individual in every country gets the vaccine. We also discussed how blockchain technology may be applied to many sectors of healthcare and the benefits it can provide in terms of enhancing global network healthcare systems. © 2022 IEEE.

3.
2022 IEEE Delhi Section Conference, DELCON 2022 ; 2022.
Article in English | Scopus | ID: covidwho-1846068

ABSTRACT

COVID-19 continues to have a devastating impact on people's lives worldwide. In order to combat this condition, it is critical to test affected people in a timely and cost-effective manner. Radiological examination is one of the most efficient ways to attain this goal, with the most widely available and least expensive alternative being a CXR. The artificial intelligence and data science communities have aided in the global response to COVID-19, a novel coronavirus. Detection and diagnosis techniques have focused on developing rapid diagnostic approaches based on chest X-rays and deep learning. In this paper, we have analyzed the impact of augmentation in COVID-19 CXR images with normal lung opacity and viral pneumonia images and presented a model for the detection of COVID-19. © 2022 IEEE.

4.
Kuei Suan Jen Hsueh Pao/Journal of the Chinese Ceramic Society ; 50(4):1143-1159, 2022.
Article in Chinese | Scopus | ID: covidwho-1835964

ABSTRACT

Scintillators as the core materials of radiation detection play an important role in industrial nondestructive testing, medical imaging, high energy physics and safety inspection, etc.. Theexisting scintillator research faces both opportunities and challenges, especially in the context of COVID-19 pandemic period. It is of great practical significance to develop cost-effective scintillators and optimize their overall performance. The nano-glass composites (i.e., glass ceramics) have some advantages like high emission efficiency of scintillator crystals, simple preparation and low cost as an effective star scintillator. Based on the different luminescence centers, such scintillators can be broadly divided into rare-earth element ions doped or rare-earth-free luminescent nanocrystals embedded materials. This review represented recent development on the preparation of these materials, the relationship between the types of nanocrystals and their luminescence properties, and the potential applications of these materials in high-energy X-ray and gamma-ray detection. In addition, the existing problems in the research were discussed and the future development direction of nano-glass composite scintillators was also prospected. © 2022, Editorial Department of Journal of the Chinese Ceramic Society. All right reserved.

5.
Water Res ; 219: 118535, 2022 Jul 01.
Article in English | MEDLINE | ID: covidwho-1819627

ABSTRACT

Wastewater-based surveillance (WBS) has been widely used as a public health tool to monitor the emergence and spread of SARS-CoV-2 infections in populations during the COVID-19 pandemic. Coincident with the global vaccination efforts, the world is also enduring new waves of SARS-CoV-2 variants. Reinfections and vaccine breakthroughs suggest an endemic future where SARS-CoV-2 continues to persist in the general population. In this treatise, we aim to explore the future roles of wastewater surveillance. Practically, WBS serves as a relatively affordable and non-invasive tool for mass surveillance of SARS-CoV-2 infection while minimizing privacy concerns, attributes that make it extremely suited for its long-term usage. In an endemic future, the utility of WBS will include 1) monitoring the trend of viral loads of targets in wastewater for quantitative estimate of changes in disease incidence; 2) sampling upstream for pinpointing infections in neighborhoods and at the building level; 3) integrating wastewater and clinical surveillance for cost-efficient population surveillance; and 4) genome sequencing wastewater samples to track circulating and emerging variants in the population. We further discuss the challenges and future developments of WBS to reduce inconsistencies in wastewater data worldwide, improve its epidemiological inference, and advance viral tracking and discovery as a preparation for the next viral pandemic.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/epidemiology , Humans , Pandemics , RNA, Viral , Waste Water , Wastewater-Based Epidemiological Monitoring
6.
Int J Infect Dis ; 119: 87-94, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1814521

ABSTRACT

OBJECTIVES: To evaluate the cost-effectiveness of a booster strategy in the United States. METHODS: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy of the Pfizer-BioNTech BNT162b2 (administered 6 months after the second dose) among older adults from a healthcare system perspective. RESULTS: Compared with 2 doses of BNT162b2 without a booster, the booster strategy in a 100,000 cohort of older adults would incur an additional cost of $3.4 million in vaccination cost but save $6.7 million in direct medical cost and gain 3.7 quality-adjusted life-years in 180 days. This corresponds to a benefit-cost ratio of 1.95 and a net monetary benefit of $3.4 million. Probabilistic sensitivity analysis indicates that a booster strategy has a high chance (67%) of being cost-effective. Notably, the cost-effectiveness of the booster strategy is highly sensitive to the population incidence of COVID-19, with a cost-effectiveness threshold of 8.1/100,000 person-day. If vaccine efficacies reduce by 10%, 30%, and 50%, this threshold will increase to 9.7/100,000, 13.9/100,000, and 21.9/100,000 person-day, respectively. CONCLUSION: Offering the BNT162b2 booster to older adults aged ≥65 years in the United States is likely to be cost-effective. Less efficacious vaccines and boosters may still be cost-effective in settings of high SARS-CoV-2 transmission.


Subject(s)
COVID-19 , SARS-CoV-2 , Aged , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Cost-Benefit Analysis , Humans , United States/epidemiology , Vaccination
7.
Green Energy and Technology ; : 103-109, 2022.
Article in English | Scopus | ID: covidwho-1802615

ABSTRACT

Due to the impact of unexpected circumstances such as COVID-19, several adaptations have been made to the current working environment which makes it more conducive for less travel. For example, because of the pandemic more individuals are working from home and do not need to travel daily to and from a workplace. In addition, some workplace practices such as the ‘10-day fortnight’ have been introduced. Furthermore, due to virtual meetings and conferences there is less demand for international and domestic business flights. Although this potentially means less daily travel, this also has negative implications as individuals are more likely to choose a method of transport that's convenient and cost effective. This often means using a personal vehicle. Public transport has been negatively impacted because of the pandemic and will require a significant behavioural change to recover and consolidate its position as a viable alternative to the personal vehicles. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

8.
47th Annual Conference of the IEEE-Industrial-Electronics-Society (IECON) ; 2021.
Article in English | Web of Science | ID: covidwho-1799287

ABSTRACT

Electric Vehicles (EVs) have become prominent on our roadways. They are cost-effective, save our precious time and create a pollution-free environment. High efficiency inductive wireless charging systems for electric vehicles (EVs) have proved convenient and user friendly compared to their wired charging counterparts. Wireless EVs (WEVs) are unusual in most countries due to the associated techno-economic problems. Hence, it becomes essential to study in detail about the same before deploying a WEV charging infrastructure. This paper examines the economic aspects of wireless charging systems (WCS) for EVs. The impacts of the COVID-19 and real-estate availability for constructing and commissioning various (WCS) are discussed. Additionally, the cost involved in converters/ inverters, coils, battery for WCS are enumerated.

9.
EPMA J ; 13(2): 315-334, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1797482

ABSTRACT

Breast cancer incidence is actually the highest one among all cancers. Overall breast cancer management is associated with challenges considering risk assessment and predictive diagnostics, targeted prevention of metastatic disease, appropriate treatment options, and cost-effectiveness of approaches applied. Accumulated research evidence indicates promising anti-cancer effects of phytochemicals protecting cells against malignant transformation, inhibiting carcinogenesis and metastatic spread, supporting immune system and increasing effectiveness of conventional anti-cancer therapies, among others. Molecular and sub-/cellular mechanisms are highly complex affecting several pathways considered potent targets for advanced diagnostics and cost-effective treatments. Demonstrated anti-cancer affects, therefore, are clinically relevant for improving individual outcomes and might be applicable to the primary (protection against initial cancer development), secondary (protection against potential metastatic disease development), and tertiary (towards cascading complications) care. However, a detailed data analysis is essential to adapt treatment algorithms to individuals' and patients' needs. Consequently, advanced concepts of patient stratification, predictive diagnostics, targeted prevention, and treatments tailored to the individualized patient profile are instrumental for the cost-effective application of natural anti-cancer substances to improve overall breast cancer management benefiting affected individuals and the society at large.

10.
2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering, CSDE 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1794842

ABSTRACT

COVID-19 pandemic has a devastating impact on human health and well-being. Numerous biological tools have been utilised for COVID detection, but most of the tools are costly, time-extensive and need personnel with domain expertise. Thus, a cost-effective classifier can solve the problem where cough audio signals showed potentiality as an screening classifier for COVID-19 diagnosis. Recent ML approaches on coughbased covid-19 detection need costly deep learning algorithms or sophisticated methods to extract informative features. In this paper, we propose a low-cost and efficient envelope approach, called CovidEnvelope, which can classify COVID-19 positive and negative cases from raw data by avoiding above disadvantages. This automated approach can select correct audio signals (cough) from background noises, generate envelope around the informative audio signal, and finally provide outcomes by computing area enclosed by the envelope. It has been seen that reliable data-sets are also important for achieving high performance. Our approach proves that human verbal confirmation is not a reliable source of information. Finally, the approach reaches highest sensitivity, specificity, accuracy, and AUC of 0.96, 0.92, 0.94, and 0.94 respectively to detect Covid-19 coughs. Our approach outperformed other existing models on data pre-processing and inference times, and achieved accuracy and specificity of 0.91 and 0.99 respectively, to distinguish COVID-19 coughs from other coughs, resulted from respiratory diseases. The automatic approach only takes 1.8 to 3.9 minutes to compute these performances. Overall, our approach is fast and sensitive to diagnose the people living with COVID-19, regardless of having COVID19 related symptoms or not. In this connection, the model can be implemented easily in mobile-devices or web-based applications, and countries with poor health facilities will be highly beneficiary for covid diagnosis and measuring prognostication. © IEEE 2022.

11.
2021 International Conference on Electrical, Computer, and Energy Technologies, ICECET 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1779099

ABSTRACT

Covid-19 pandemic has set the world on fire. It has impacted every aspect of our society. One of the worst affected parts is the countries' health systems. Our goal is to provide a proof of concept for cost effective telemedicine system which can be used by hospitals for monitoring of thousands of patients at once, thus medical personnel exposure to the virus is minimized. In this paper we aim to put this system through the best practices of software testing so we can determine if it achieves its primary functions, keeping in line with the general idea of cost effectiveness. Black box testing with the exploratory approach was used for functionality and feature testing as it gives the most accurate real-world results. During the tests, several bugs were found and fixed. Because of the fact, that the testers were actual medical personnel, we have received valuable information on how to improve the quality of the product, so it can be even more ease to use and provide the necessary robustness and data visualization. © 2021 IEEE.

12.
7th IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1769637

ABSTRACT

Medical imaging modalities have been showing great potentials for faster and efficient disease transmission control and containment. In the paper, we propose a cost-effective COVID-19 and pneumonia detection framework using CT scans acquired from several hospitals. To this end, we incorporate a novel data processing framework that utilizes 3D and 2D CT scans to diversify the trainable inputs in a resource-limited setting. Moreover, we empirically demonstrate the significance of several data processing schemes for our COVID-19 and pneumonia detection network. Experiment results show that our proposed pneumonia detection network is comparable to other pneumonia detection tasks integrated with imaging modalities, with 93% mean AUC and 85.22% mean accuracy scores on generalized datasets. Additionally, our proposed data processing framework can be easily adapted to other applications of CT modality, especially for cost-effective and resource-limited scenarios, such as breast cancer detection, pulmonary nodules diagnosis, etc. © 2021 IEEE

13.
5th International Conference on Information Systems and Computer Networks, ISCON 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759093

ABSTRACT

The idea of data mining has been around for longer than a century, yet come into a more prominent public core interest in the 1930s. As time passed, the measure of information in numerous frameworks developed to bigger than terabyte size, which can no longer be maintained manually. Additionally, for the effective presence of any business, finding hidden examples in information is viewed as fundamental. Accordingly, several software tools were created to find covered up information and make assumptions. Salesforce Einstein is an Artificial Intelligence-based tool, provided by Salesforce.com. Salesforce Einstein tool is designed to enable companies to become smarter and predictive about their customers. It analyzes your historical data against set boundaries or parameters and generates recommended actions for the companies accordingly. In this project, we are using the Salesforce Einstein tool to create insights into Covid data. © 2021 IEEE.

14.
3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759050

ABSTRACT

In this paper, a novel method to effectively mitigate the spread of COVID-19 at the local level due to contact with any surfaces has been introduced. Our innovation - a device called 'Touch-less Doorbell' can well prove to be an essential safety shield for the common public in their fight against this pandemic. This idea of the contactless doorbell will stand out from conventional ones installed in our houses in terms of being durable, energy-efficient and cost-effective. Once an infected person uses the doorbell, the virus holds onto that and spreads accordingly when an uninfected person touches the same. The existing doorbell itself can be reused by integrating some power electronics components without entirely replacing the existing one. Thus, the doorbell can be made to operate in the touchless as well as touch enabled mode. The touch-less doorbell circuitry comprises of an operational amplifier as a voltage comparator, a potentiometer and photodiode along with the relay setting and switching circuit. Hence, the comparator circuit and switching circuit forms the two essential parts;with the comparator circuit comparing the sensor's threshold with reference value and switching circuit (consisting of a transistor) for turning the bell ON. A detailed cost analysis of the proposed model has also been performed concluding it to be a budget friendly option without compromising on the product's quality. © 2021 IEEE.

15.
3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1759037

ABSTRACT

The present covid-19 pandemic necessitates the need for a cost effective and efficient remote health monitoring mechanisms for the collection, transmission, evaluation, and communication of patient health data from electronic devices since many find it difficult to go for regular medical checkup due to safety concerns. Therefore, we require a remote health monitoring system that can monitor different body parameters and transmit it to a health care provider in a remote location. This paper describes the design and development of a remote health monitoring system capable of measuring ECG, Heart rate and SpO2 using AD8232, MAX30100 or MAX30102 and transfer this information to physicians using IoT. The ESP32 module is used to establish the IoT connectivity and share the vital information to medical practitioners for real-time analysis through a smartphone or Tab. In the present work, Blynk IoT cloud platform is used to communicate with hardware and software. The size of the designed PCB board is less than 60mm x 60 mm, therefore the size and weight of the device are very small and able to attach on the patient's cloth or in the body with the help of a Velcro belt. This helps the patient to easily carry the device without any discomfort. © 2021 IEEE.

16.
Journal of Food Processing and Preservation ; 2022.
Article in English | Scopus | ID: covidwho-1752596

ABSTRACT

Fresh fruits and vegetables carry a heavy load of microorganisms which may cause the risks of food-borne illness to the consumer. Even after washing with water, there is a need for sanitization and disinfection to drop down a load of harmful microbes under the safe limit. Sanitizers and disinfectants are not only cost-effective but also nonhazardous and eco-friendly. Moreover, they should not hamper the organoleptic and nutritional properties of fresh produce. With rising demand for safe, nutritious, and fresh fruits and vegetables, many new disinfectants and treatments are commercially available. During this COVID-19 outbreak, knowledge of sanitizers and disinfectants for fresh fruits and vegetables is very important. This review focuses on working principles, applications, and related legislation of physical and chemical disinfection technologies (chlorine, chlorine dioxide, ozone, organic acids, electrolyzed water, irradiation, ultrasound etc.) and their effectiveness for shelf-life extension of fresh produce. Novelty impact statement: This review article gives comprehensive information about potential sanitizers and disinfectants for fresh produce discussing their mechanisms and relevant legislation in one place. The article will help the readers to opt for the suitable method for disinfecting fresh produce and also will provide a reference to use these methods within permissible limits as per legislation. Such information is very much relevant in the present Covid-19 pandemic scenario. © 2022 Wiley Periodicals LLC.

17.
2021 IEEE International Conference on Computing, ICOCO 2021 ; : 276-281, 2021.
Article in English | Scopus | ID: covidwho-1730963

ABSTRACT

With the outbreak of the highly-contagious SARS-CoV-2 virus and its accompanying coronavirus disease 2019 (COVID-19), many government agencies adopted contact tracing to measure and mitigate the spread of the virus. Contact tracing aims to keep track of the individual's movements and activities and identify all those who they come in contact with. This study is focused on designing a cost-effective, efficient, and accurate system for information logging and temperature screening with a complementary contact tracing feature. The system provides an automated, safe, and physical-distance-aware alternative to manual temperature measurement and data logging practiced by most commercial establishments. The system uses an Arduino and a Raspberry Pi, along with infrared temperature sensors utilizing proper calibration methods to yield temperature reading difference of 0.1-0.3 degree-Celsius taken at 10 cm distance. User identification is done by reading either specifically-registered RFID tags or system-generated identity-QR code. Temperature is subsequently read, date and time stamped, and logged into the system. This allows for automated and exact association of the user logged information with their corresponding temperature. © 2021 IEEE.

18.
24th International Conference on Computer and Information Technology, ICCIT 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1714044

ABSTRACT

Covid 19 continues to have a catastrpoic effect on the world, causing terrible spots to appear all over the place. Due to global epidemics and doctor and healthcare personel shortages, developing an AI-based system to detect COVID in a timely and cost-effective method has become a requirement. It is also essential to detect covid from chest X-ray and CT radiographs due to their accuracy in detecting lung infection and as well as to understand the severity. Moreover, though the number of infected people around the globe is enormous, the amount of covid data set to build an AI system is scarce and scattered. In this letter, we presented a Chest CT scan data (HRCT) set for Covid and healthy patients considering a varying range of severity of COVID, which we published on kaggle, that can assist other researchers to contribute to healthcare AI. We also developed three deep learning approaches for detecting covid quickly and cheaply. Our three transfer learning-based approaches, Inception v3, Resnet 50, and VGG16, achieve accuracy of 99.8%, 91.3%, and 99.3%, respectively on unseen data. We delve deeper into the black boxes of those models to demonstrate how our model comes to a certain conclusion, and we found that, despite the low accuracy of the model based on VGG16, it detects the covid spot of images well, which we believe may further assist doctors in visualizing which regions are affected. © 2021 IEEE.

19.
2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1714025

ABSTRACT

The battle over the worst spread of novel covid 19 pandemic has infested over billions of people all over the globe every day. So that the early self-prediction is more important to combat Covid-19. The Internet of Things (IoT) is an efficient and helpful technology in the medical care for self-prediction of COVID-19 disease. In order to provide efficient system, considering the cost effectiveness is also be important. So, in this paper, different IoT based sensors are being used to sense the sensory based data (Temperature, Blood Pressure, Pulse Rate and Oxygen) to reduce the cost. The proposed IoT model is designed to identify the symptoms and generate the efficient report by analyzing the previous readings which also reduces the consulting cost and number of doctor visits. Thus, AN EFFICIENT SENSORY BASED COST-EFFECTIVE IOT MODEL FOR PRIOR PREDICTION OF COVID-19 is proposed. © 2021 IEEE.

20.
2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1714017

ABSTRACT

The COVID-19 epidemic compelled régimes around the globe to enact quarantine in order to protect the virus from transmitting. According to the documentation, wearing a face mask at work minimizes the chance of spreading. Use of AI to provide an innocuous milieu in a production setup that is both efficient and cost-effective. Face mask detection will be enabled utilizing a mixed model combining machine learning and deep learning. We will utilize Open CV to do real-time face detection from a live feed through our camera using a face mask detection library that comprises of photos with and without a mask. In this work, this dataset is utilized to create a COVID-19 face mask detector with CV utilizing Open CV, Python, Tensor Flow, and other tools. The mail aim of the work is to find whether the being on the image/cinematic rivulet is exhausting a face mask or not through the aid of deep learning and computer revelation. By using this face mask detection, we are going to make a gateway system. This system allows people in only if they wear a face mask. We use Raspberry pi to make this system and an a4899 driver module to control the stepper motor. The gateway is controlled by the motor which is connected to the driver module. © 2021 IEEE.

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