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Rowe BR, Canosa A, Meslem A, Rowe F. Increased airborne transmission of COVID-19 with new variants, implications for health policies. BUILDING AND ENVIRONMENT 2022; 219:109132. [PMID: 35578697 PMCID: PMC9095081 DOI: 10.1016/j.buildenv.2022.109132] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/19/2022] [Accepted: 04/20/2022] [Indexed: 06/15/2023]
Abstract
New COVID-19 variants, either of higher viral load such as delta or higher contagiousness like omicron, can lead to higher airborne transmission than historical strains. This paper highlights their implications for health policies, based on a clear analytical understanding and modeling of the airborne contamination paths, of the dose following exposure, and the importance of the counting unit for pathogens, itself linked to the dose-response law. Using the counting unit of Wells, i.e. the quantum of contagium, we develop the conservation equation of quanta which allows deriving the value of the quantum concentration at steady state for a well-mixed room. The link with the monitoring concentration of carbon dioxide is made and used for a risk analysis of a variety of situations for which we collected CO2 time-series observations. The main conclusions of these observations are that 1) the present norms of ventilation, are both insufficient and not respected, especially in a variety of public premises, leading to high risk of contamination and that 2) air can often be considered well-mixed. Finally, we insist that public health policy in the field of airborne transmission should be based on a multi parameter analysis such as the time of exposure, the quantum production rate, mask wearing and the infector proportion in the population in order to evaluate the risk, considering the whole complexity of dose evaluation. Recognizing airborne transmission requires thinking in terms of time of exposure rather than in terms of proximal distance.
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Affiliation(s)
- Bertrand R Rowe
- Rowe Consulting, 22 chemin des moines, 22750 Saint Jacut de la Mer, France
| | - André Canosa
- CNRS, IPR (Institut de Physique de Rennes)-UMR 6251, Université de Rennes, 35000 Rennes, France
| | - Amina Meslem
- Université de Rennes, LGCGM, 3 Rue du Clos Courtel, BP 90422, 35704, Rennes, CEDEX 7, France
| | - Frantz Rowe
- Nantes Université, LEMNA, Nantes, France
- SKEMA Business School, KTO, Sophia-Antipolis, France
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Ding W, Nayak J, Swapnarekha H, Abraham A, Naik B, Pelusi D. Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data. Neurocomputing 2021; 457:40-66. [PMID: 34149184 PMCID: PMC8206574 DOI: 10.1016/j.neucom.2021.06.024] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 06/02/2021] [Accepted: 06/11/2021] [Indexed: 12/11/2022]
Abstract
The unprecedented surge of a novel coronavirus in the month of December 2019, named as COVID-19 by the World Health organization has caused a serious impact on the health and socioeconomic activities of the public all over the world. Since its origin, the number of infected and deceased cases has been growing exponentially in almost all the affected countries of the world. The rapid spread of the novel coronavirus across the world results in the scarcity of medical resources and overburdened hospitals. As a result, the researchers and technocrats are continuously working across the world for the inculcation of efficient strategies which may assist the government and healthcare system in controlling and managing the spread of the COVID-19 pandemic. Therefore, this study provides an extensive review of the ongoing strategies such as diagnosis, prediction, drug and vaccine development and preventive measures used in combating the COVID-19 along with technologies used and limitations. Moreover, this review also provides a comparative analysis of the distinct type of data, emerging technologies, approaches used in diagnosis and prediction of COVID-19, statistics of contact tracing apps, vaccine production platforms used in the COVID-19 pandemic. Finally, the study highlights some challenges and pitfalls observed in the systematic review which may assist the researchers to develop more efficient strategies used in controlling and managing the spread of COVID-19.
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Affiliation(s)
- Weiping Ding
- School of Information Science and Technology, Nantong University, China
| | - Janmenjoy Nayak
- Aditya Institute of Technology and Management (AITAM), India
| | - H Swapnarekha
- Aditya Institute of Technology and Management (AITAM), India
- Veer Surendra Sai University of Technology, India
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COVID-19 digital contact tracing applications and techniques: A review post initial deployments. TRANSPORTATION ENGINEERING 2021; 5:100072. [PMCID: PMC8132499 DOI: 10.1016/j.treng.2021.100072] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/30/2021] [Accepted: 05/17/2021] [Indexed: 05/24/2023]
Abstract
The coronavirus disease 2019 (COVID-19) is a severe global pandemic that has claimed millions of lives and continues to overwhelm public health systems in many countries. The spread of COVID-19 pandemic has negatively impacted the human mobility patterns such as daily transportation-related behavior of the public. There is a requirement to understand the disease spread patterns and its routes among neighboring individuals for the timely implementation of corrective measures at the required placement. To increase the effectiveness of contact tracing, countries across the globe are leveraging advancements in mobile technology and Internet of Things (IoT) to aid traditional manual contact tracing to track individuals who have come in close contact with identified COVID-19 patients. Even as the first administration of vaccines begins in 2021, the COVID-19 management strategy will continue to be multi-pronged for the foreseeable future with digital contact tracing being a vital component of the response along with the use of preventive measures such as social distancing and the use of face masks. After some months of deployment of digital contact tracing technology, deeper insights into the merits of various approaches and the usability, privacy, and ethical trade-offs involved are emerging. In this paper, we provide a comprehensive analysis of digital contact tracing solutions in terms of their methodologies and technologies in the light of the new data emerging about international experiences of deployments of digital contact tracing technology. We also provide a discussion on open challenges such as scalability, privacy, adaptability and highlight promising directions for future work.
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Li T, Cobb C, Yang JJ, Baviskar S, Agarwal Y, Li B, Bauer L, Hong JI. What makes people install a COVID-19 contact-tracing app? Understanding the influence of app design and individual difference on contact-tracing app adoption intention. PERVASIVE AND MOBILE COMPUTING 2021; 75:101439. [PMID: 36569467 PMCID: PMC9760841 DOI: 10.1016/j.pmcj.2021.101439] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/12/2021] [Accepted: 06/11/2021] [Indexed: 05/06/2023]
Abstract
Smartphone-based contact-tracing apps are a promising solution to help scale up the conventional contact-tracing process. However, low adoption rates have become a major issue that prevents these apps from achieving their full potential. In this paper, we present a national-scale survey experiment ( N = 1963 ) in the U.S. to investigate the effects of app design choices and individual differences on COVID-19 contact-tracing app adoption intentions. We found that individual differences such as prosocialness, COVID-19 risk perceptions, general privacy concerns, technology readiness, and demographic factors played a more important role than app design choices such as decentralized design vs. centralized design, location use, app providers, and the presentation of security risks. Certain app designs could exacerbate the different preferences in different sub-populations which may lead to an inequality of acceptance to certain app design choices (e.g., developed by state health authorities vs. a large tech company) among different groups of people (e.g., people living in rural areas vs. people living in urban areas). Our mediation analysis showed that one's perception of the public health benefits offered by the app and the adoption willingness of other people had a larger effect in explaining the observed effects of app design choices and individual differences than one's perception of the app's security and privacy risks. With these findings, we discuss practical implications on the design, marketing, and deployment of COVID-19 contact-tracing apps in the U.S.
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Affiliation(s)
- Tianshi Li
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Camille Cobb
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Jackie Junrui Yang
- Stanford University, 450 Jane Stanford Way, Stanford, 94305, CA, United States
| | - Sagar Baviskar
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Yuvraj Agarwal
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Beibei Li
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Lujo Bauer
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
| | - Jason I Hong
- Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, 15213, PA, United States
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Dong Y, Yao YD. IoT Platform for COVID-19 Prevention and Control: A Survey. IEEE ACCESS : PRACTICAL INNOVATIONS, OPEN SOLUTIONS 2021; 9:49929-49941. [PMID: 34812390 PMCID: PMC8545211 DOI: 10.1109/access.2021.3068276] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 03/09/2021] [Indexed: 05/18/2023]
Abstract
As a result of the worldwide transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic. Currently, with unavailable pharmaceutical treatments and low vaccination rates, this novel coronavirus results in a great impact on public health, human society, and global economy, which is likely to last for many years. One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented. Internet of things (IoT) platform is preferred to be utilized to achieve this goal, due to its ubiquitous sensing ability and seamless connectivity. IoT technology is changing our lives through smart healthcare, smart home, and smart city, which aims to build a more convenient and intelligent community. This paper presents how the IoT could be incorporated into the epidemic prevention and control system. Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing & Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking. We investigate and review the state-of-the-art literatures of these five interventions to present the capabilities of IoT in countering against the current COVID-19 pandemic or future infectious disease epidemics.
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Affiliation(s)
- Yudi Dong
- Department of Electrical and Computer EngineeringStevens Institute of TechnologyHobokenNJ07030USA
| | - Yu-Dong Yao
- Department of Electrical and Computer EngineeringStevens Institute of TechnologyHobokenNJ07030USA
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Introducing the Special Issue on “Ubiquitous Sensing for Smart Health Monitoring”. INFORMATION 2021. [DOI: 10.3390/info12020074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Sensors continue to pervade our surroundings in undiminished ways [...]
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de Fazio R, Giannoccaro NI, Carrasco M, Velazquez R, Visconti P. Wearable devices and IoT applications for symptom detection, infection tracking, and diffusion containment of the COVID-19 pandemic: a survey. FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING 2021; 22. [PMCID: PMC8616032 DOI: 10.1631/fitee.2100085] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Until a safe and effective vaccine to fight the SARS-CoV-2 virus is developed and available for the global population, preventive measures, such as wearable tracking and monitoring systems supported by Internet of Things (IoT) infrastructures, are valuable tools for containing the pandemic. In this review paper we analyze innovative wearable systems for limiting the virus spread, early detection of the first symptoms of the coronavirus disease COVID-19 infection, and remote monitoring of the health conditions of infected patients during the quarantine. The attention is focused on systems allowing quick user screening through ready-to-use hardware and software components. Such sensor-based systems monitor the principal vital signs, detect symptoms related to COVID-19 early, and alert patients and medical staff. Novel wearable devices for complying with social distancing rules and limiting interpersonal contagion (such as smart masks) are investigated and analyzed. In addition, an overview of implantable devices for monitoring the effects of COVID-19 on the cardiovascular system is presented. Then we report an overview of tracing strategies and technologies for containing the COVID-19 pandemic based on IoT technologies, wearable devices, and cloud computing. In detail, we demonstrate the potential of radio frequency based signal technology, including Bluetooth Low Energy (BLE), Wi-Fi, and radio frequency identification (RFID), often combined with Apps and cloud technology. Finally, critical analysis and comparisons of the different discussed solutions are presented, highlighting their potential and providing new insights for developing innovative tools for facing future pandemics.
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Affiliation(s)
- Roberto de Fazio
- Department of Innovation Engineering, University of Salento, Lecce, 73100 Italy
| | | | - Miguel Carrasco
- Facultad de Ingeniería y Ciencias, Universidad Adolfo Ibáñez, Peñalolén, Santiago, 7941169 Chile
| | - Ramiro Velazquez
- Facultad de Ingeniería, Universidad Panamericana, Aguascalientes, 20290 Mexico
| | - Paolo Visconti
- Department of Innovation Engineering, University of Salento, Lecce, 73100 Italy
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