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COVID-19: Defense Strategies and Technologies

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (31 August 2021) | Viewed by 14138

Special Issue Editor


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Guest Editor
Department of Electrical and Information Engineering, Polytechnic University of Bari, Bari, Italy
Interests: photovoltaic systems; renewable energy technologies; smart cities technologies; infrared analysis; cloud-based applications for the energy; diagnostics and prognostics
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Special Issue Information

Dear Colleagues,

Coronaviruses (CoV) are a large family of respiratory viruses that can cause mild to moderate diseases, from the common cold to respiratory syndromes such as MERS (Middle East Respiratory Syndrome) and SARS (Severe Acute Respiratory Syndrome). They are so called because of the crown-shaped tips that are present on their surface. The International Committee on Taxonomy of Viruses (ICTV) has given the new coronavirus the name Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). Instead, the World Health Organization (WHO) has announced that the respiratory disease caused by this virus has been called COVID-19, which stands for CO-rona VI-rus D-isease, and the year of identification, 2019. Currently, the Covid-19 pandemic is already the most serious problem in the world and has not yet exploded in developing countries, where health care systems will not be able to guarantee the contrast offered by developed countries.

To limit the impact of COVID-19 on the social and economic life of the world population, it is urgent to collect, share and disseminate any research result. In fact, even if this field is mainly studied by doctors, biologists, epidemiologists, and so on, nevertheless, other experts such as engineers, informatics, physicists, etc., can also make an important contribution to eradicate it. In this view, the joint Special Issue is focused on the challenging issues covered by the journals “Smart Cities” and “Sustainability”. Big data-based technologies can monitor the contagion speed globally and locally, as well as technologies can dynamically classify places or contexts (e.g. outdoor or indoor concert) on a different risk level of infection at Covid-19. Moreover, these technologies could also extend to other dangerous viruses, albeit different.

These solutions can be effectively exploited in smart cities, i.e. cities with digital infrastructures that enables a real-time dialogue among individual devices, providing and receiving information and updates on the virus and/or on the most dangerous contexts. Contagion trackability by App or web-based technologies is one of the main tools used by the countries that have started to reduce the limitations. Forecasting models of the contagion and strategies to reduce the contagion speed must be discussed in a wider field of expertise. The comparison of the results from the data-driven and the model-driven approaches can support the important and urgent decisions of the governments. The different speed of contagion resulting from the decisions of different governments could also be used to create policy-driven models. For example, some governments that initially applied no or slight restrictions were faced with a more rapid spread of contagion and subsequently had to follow the Italian model, which was the most drastic in Europe. Other related issues concern pollution in a dual role. On the one hand, pollution is hypothesized as a vehicle of contagion, because the virus binds with some polluting substances; on the other hand, pollution is significantly reduced after the restrictions applied by governments (as visible from satellite images), due to the reduction of the circulating vehicles and the closure of the factories. Again, the restrictions have impact on all the human activities that involve the energy consumption, from the industries to the houses, because the restrictions impose to stay at home; then, the residential consumption is totally changed with respect to the average consumption of the same period in the previous years. Consequently, the power flows in distribution and transmission lines are totally changed with respect to the previous years. Considering that, in several countries, the energy produced by the Renewable Energy Sources (RES) and injected into the grid must be used before the energy produced by fossil fuel based generators, it results that nowadays – with a reduced energy demand – the contribution (in per cent) of the energy supplied by the unpredictable RES is greater than the standard threshold; therefore, new settings are needed. This situation has impacts on the operation of the grid and on the financial aspects of the business plans of generators based on renewable energy and on fossil fuel.

Topics of interest for this issue include, but are not limited, to the areas:

  • big data
  • data-fusion
  • sensor fusion
  • IoT
  • image processing
  • electronic devices
  • telemedicine
  • wearable devices;
  • artificial intelligence;
  • machine learning;
  • deep learning;
  • forecasting models;
  • data-driven models;
  • policy-driven models;
  • model-driven strategies;
  • impact of pollution and on pollution;
  • climate effects;
  • impact on distribution lines;
  • impact on transmission lines;
  • smart-grids and micro-grids.

You may choose our Joint Special Issue in Smart Cities.

Prof. Silvano Vergura
Guest Editor

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Published Papers (3 papers)

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Research

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25 pages, 2749 KiB  
Article
Data-Driven Epidemic Intelligence Strategies Based on Digital Proximity Tracing Technologies in the Fight against COVID-19 in Cities
by Dario Esposito, Giovanni Dipierro, Alberico Sonnessa, Stefania Santoro, Simona Pascazio and Irene Pluchinotta
Sustainability 2021, 13(2), 644; https://doi.org/10.3390/su13020644 - 12 Jan 2021
Cited by 9 | Viewed by 3222
Abstract
In a modern pandemic outbreak, where collective threats require global strategies and local operational defence applications, data-driven solutions for infection tracing and forecasting epidemic trends are crucial to achieve sustainable and socially resilient cities. Indeed, the need for monitoring, containing, and mitigating the [...] Read more.
In a modern pandemic outbreak, where collective threats require global strategies and local operational defence applications, data-driven solutions for infection tracing and forecasting epidemic trends are crucial to achieve sustainable and socially resilient cities. Indeed, the need for monitoring, containing, and mitigating the ongoing COVID-19 pandemic has generated a great deal of interest in Digital Proximity Tracing Technology (DPTT) on smartphones, as well as their function and effectiveness and insights of population acceptance. This paper introduces and compares different Data-Driven Epidemic Intelligence Strategies (DDEIS) developed on DPTTs. It aims to clarify to what extent DDEIS could be effective and both technologically and socially suitable in reaching the objective of a swift return to normality for cities, guaranteeing public health safety and minimizing the risk of epidemic resurgence. It assesses key advantages and limits in supporting both individual decision-making and policy-making, considering the role of human behaviour. Specifically, an online survey carried out in Italy revealed user preferences for DPTTs and provided preliminary data for an SEIR (Susceptible–Exposed–Infectious–Recovered) epidemiological model. This was developed to evaluate the impact of DDEIS on COVID-19 spread dynamics, and results are presented together with an evaluation of potential drawbacks. Full article
(This article belongs to the Special Issue COVID-19: Defense Strategies and Technologies)
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18 pages, 8365 KiB  
Article
Pipeline for Advanced Contrast Enhancement (PACE) of Chest X-ray in Evaluating COVID-19 Patients by Combining Bidimensional Empirical Mode Decomposition and Contrast Limited Adaptive Histogram Equalization (CLAHE)
by Giulio Siracusano, Aurelio La Corte, Michele Gaeta, Giuseppe Cicero, Massimo Chiappini and Giovanni Finocchio
Sustainability 2020, 12(20), 8573; https://doi.org/10.3390/su12208573 - 16 Oct 2020
Cited by 20 | Viewed by 6717
Abstract
COVID-19 is a new pulmonary disease which is driving stress to the hospitals due to the large number of cases worldwide. Imaging of lungs can play a key role in the monitoring of health status. Non-contrast chest computed tomography (CT) has been used [...] Read more.
COVID-19 is a new pulmonary disease which is driving stress to the hospitals due to the large number of cases worldwide. Imaging of lungs can play a key role in the monitoring of health status. Non-contrast chest computed tomography (CT) has been used for this purpose, mainly in China, with significant success. However, this approach cannot be massively used, mainly for both high risk and cost, also in some countries, this tool is not extensively available. Alternatively, chest X-ray, although less sensitive than CT-scan, can provide important information about the evolution of pulmonary involvement during the disease; this aspect is very important to verify the response of a patient to treatments. Here, we show how to improve the sensitivity of chest X-ray via a nonlinear post-processing tool, named PACE (Pipeline for Advanced Contrast Enhancement), combining properly Fast and Adaptive Bidimensional Empirical Mode Decomposition (FABEMD) and Contrast Limited Adaptive Histogram Equalization (CLAHE). The results show an enhancement of the image contrast as confirmed by three widely used metrics: (i) contrast improvement index, (ii) entropy, and (iii) measure of enhancement. This improvement gives rise to a detectability of more lung lesions as identified by two radiologists, who evaluated the images separately, and confirmed by CT-scans. The results show this method is a flexible and an effective approach for medical image enhancement and can be used as a post-processing tool for medical image understanding and analysis. Full article
(This article belongs to the Special Issue COVID-19: Defense Strategies and Technologies)
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Review

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21 pages, 1060 KiB  
Review
Selected Respiratory Protective Devices: Respirators and Significance of Some Markings
by Pavel Otrisal, Constantin Bungau, Vladimír Obsel, Zdeněk Melicharik and Gabriela Tont
Sustainability 2021, 13(9), 4988; https://doi.org/10.3390/su13094988 - 29 Apr 2021
Cited by 18 | Viewed by 2989
Abstract
Currently, setting the obligation to use respiratory protective equipment with a level of protection of at least FFP2 in public transport and commercial and shopping centers are considered within the European Union. Many new products appeared on the European market within these specifications, [...] Read more.
Currently, setting the obligation to use respiratory protective equipment with a level of protection of at least FFP2 in public transport and commercial and shopping centers are considered within the European Union. Many new products appeared on the European market within these specifications, and many symbols have been used. The paper deals with the meaning of selected respiratory protection based on respirators symbols and markings (which appeared massively, especially after the pandemic situation in the spring of 2020), these symbols not being uniformly understood and well communicated. We also mention and discuss some of the problems related to setting the conditions of public procurement, which affect respirators. Thus, this review is an “informative guide” in facilitating the understanding and use of full knowledge of the most appropriate respiratory protective devices in various situations. Full article
(This article belongs to the Special Issue COVID-19: Defense Strategies and Technologies)
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