Another Look at Privacy-Preserving Automated Contact Tracing

In the current COVID-19 pandemic, manual contact tracing has been proven to be very helpful to reach close contacts of infected users and slow down spread of the virus. To improve its scalability, a number of automated contact tracing (ACT) solutions have been proposed, and some of them have been deployed. Despite the dedicated efforts, security and privacy issues of these solutions are still open and under intensive debate. In this article, we examine the ACT concept from a broader perspective, by focusing on not only security and privacy issues but also functional issues such as interface, usability, and coverage. We first elaborate on these issues and particularly point out the inevitable privacy leakages in existing Bluetooth Low Energy based ACT solutions, including centralized and decentralized ones. In addition, we examine the existing venue-based ACT solutions and identify their privacy and security concerns. Then, we propose a generic venue-based ACT solution and a concrete instantiation based on Bluetooth Low Energy technology. Our solution monitors users’ contacting history only in virus-spreading-prone venues and offers higher-level protection for both security and privacy than its predecessors. Finally, we evaluate our solution from security, privacy, and efficiency perspectives, and also highlight how to reduce false positives in some specific indoor environments.

The emergence of two distinct SARS-CoV-2 Gamma related variants during the second wave of COVID-19 in Santa Catarina, Southern Brazil and the rapid spread of P.1-like-II SARS-CoV-2 variant transmission and a regionalization in the Western region

COVID-19 has assumed significant and lasting proportions worldwide. Following initial cases in the Western mesoregion, the State of Santa Catarina (SC), southern Brazil, was heavily affected as a whole by the pandemic in early 2021. This study aimed to evaluate the dynamics of the SARS-CoV-2 virus spreading patterns in the SC state through March 2020 to April 2021 using genomic surveillance. During this period, 23 distinct variants, including two VOCs (Beta and Gamma) were identified, among which, the Gamma and related lineages were predominant in the second pandemic wave within SC. However, a regionalization of P.1-like-II in the Western region was observed, concomitant to the increase in cases, mortality, and case fatality rate (CFR) index. This is the first evidence of the regionalization of the SARS-CoV-2 transmission in the and highlight the importance of tracking variants, dispersion and their impact of SARS-CoV-2 on the public health system in Brazilian states.

i9MASKS Project

Engineering education is a challenging topic that has been deeply explored in order to provide better educational experiences to engineering students, and the learning by doing approach has been appraised. Amidst a global pandemic, an engineering summer program denominated i9Masks emerged and aimed to create transparent facial masks for preventing the virus spreading. This project had the participation of 21 students from different engineering areas, as well as professors and monitors whose guidance and commitment were of great importance for its success. Aiming to understand the importance of this engineering hands-on project for students' training, two inquiries were applied, being one for students and the other for professors and monitors/researchers. Students described this initiative as an amazing and innovative experience that they would like to repeat and considered useful for their careers. Regarding the impact perceived by the teaching staff, the results proved that they enjoyed participating in the i9MASKS project and sharing knowledge with students in a practical way.

The Emerging Clinical Utility of Neurosonology During COVID-19 Pandemic

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 infection. Over the last 2 years the virus has spread worldwide with enormous implications on the healthcare systems. COVID-19 patients suffer from mild upper-airway manifestations to pneumonia and severe acute respiratory distress syndrome and their hospitalizations are often prolonged. Neurological manifestations of the disease are common. Neurosonology (transcranial Doppler & cervical duplex ultrasound) is an easily repeatable diagnostic imaging modality that can be simply applied at the bedside of COVID-19 patients with cerebrovascular diseases or in critically ill patients in the intensive care unit. Neurosonology may provide hemodynamic assessment of cerebral circulation, quantitative evaluation of increased intracranial pressure and detection of micro-embolic signals in real-time. Consequently, it may assist substantially in the diagnosis, risk stratification and therapeutic approach of COVID-19 patients with or without cerebrovascular complications. In the present narrative review, we discuss the emerging clinical utility of neurosonology during COVID-19 pandemic and highlight the upgraded role of neurosonology resulting from the combination of the established applications coupled with the reduced risk of virus spreading during ultrasound evaluation compared to other imaging modalities including computed tomography and magnetic resonance imaging.

The importance of superspreaders on the spread of the global COVID-19 pandemic

The dynamics of pandemics is most often analyzed using a variation of the SIR (Susceptible-Infected-Recovered) model1, the key parameter of which is the basic reproduction number R0. Some evidences suggest that the contagion-spreading networks are scale-free, with the biggest nodes corresponding to superspreaders2,3. However, current understanding of the scale-free topology of these networks, and of the implications of such topology for the dynamics of pandemics is incomplete. Here we show that the world-wide spreading rate of COVID-19 gives an indirect evidence that the underlying virus-spreading network is scale-free, with the degree distribution exponent close to 2. Furthermore, our results show that the spreading rate of a virus is predominantly controlled by superspreaders who typically get infected and acquire immunity during the initial outbreak stage of the pandemic. Thereby the biggest nodes get immune and hence, removed from the network, resulting in a rapid decrease of the effective reproduction number. These findings are important for understanding the dynamics of pandemics, and for designing optimal virus control strategies. In particular, screening a population for the number of antibodies of a set of viruses can reveal potential superspreaders, the vaccination or isolation of whom can impede a pandemic at its early stage.

Internet Rumors During the COVID-19 Pandemic: Dynamics of Topics and Public Psychologies

The capturing of social opinions, especially rumors, is a crucial issue in digital public health. With the outbreak of the COVID-19 pandemic, the discussions of related topics have increased exponentially in social media, with a large number of rumors on the Internet, which highly impede the harmony and sustainable development of society. As human health has never suffered a threat of this magnitude since the Internet era, past studies have lacked in-depth analysis of rumors regarding such a globally sweeping pandemic. This text-based analysis explores the dynamic features of Internet rumors during the COVID-19 pandemic considering the progress of the pandemic as time-series. Specifically, a Latent Dirichlet Allocation (LDA) model is used to extract rumor topics that spread widely during the pandemic, and the extracted six rumor topics, i.e., “Human Immunity,” “Technology R&D,” “Virus Protection,” “People's Livelihood,” “Virus Spreading,” and “Psychosomatic Health” are found to show a certain degree of concentrated distribution at different stages of the pandemic. Linguistic Inquiry and Word Count (LIWC) is used to statistically test the psychosocial dynamics reflected in the rumor texts, and the results show differences in psychosocial characteristics of rumors at different stages of the pandemic progression. There are also differences in the indicators of psychosocial characteristics between truth and disinformation. Our results reveal which topics of rumors and which psychosocial characteristics are more likely to spread at each stage of progress of the pandemic. The findings contribute to a comprehensive understanding of the changing public opinions and psychological dynamics during the pandemic, and also provide reference for public opinion responses to major public health emergencies that may arise in the future.

Controlling Virus Spread Using an Intermittent Quarantine Strategy on Multiplex Networks

Virus spreading on the Internet will negatively affect cybersecurity. An intermittent quarantine immunization strategy to control virus spreading when containing information diffusion is proposed herein. In this model, information and virus spread on different subnetworks and interact with each other. We further develop a heterogeneous mean-field approach with time delays to investigate this model and use Monte Carlo simulations to systematically investigate the spreading dynamics. For a relatively short intermittent period, the optimal information transmission probability of the virus will be significantly suppressed. However, when the intermittent period is extremely long; increasing the probability of information transmission can control the virus spreading as well as suppress the increase in the intermittent period. Finally, it is shown that the average degree of the two subnetworks does not qualitatively affect the spreading dynamics.

Correlated Stochastic Epidemic Model for the Dynamics of SARS-CoV-2 with Vaccination

We formulate a mathematical model has been proposed to describe the stochastic influence of SARS-CoV-2 virus with various sources of randomness and vaccination. We assume the various sources of ran-domness in each population groups by different Brownian motion. We develop the correlated stochastic model by taking into account the various sources of randomness by different Brownian motions and distributed the total human population in three groups of susceptible, infected and recovered with reservoir class. Because reservoir play a significant role in the transmission of SARS-CoV-2 virus spreading. Moreover, the vaccination of susceptible are also accorded. Once we formulate the correlated stochastic model, the existence and uniqueness of positive solution will be discussed to show the problem feasibility. The SARS-CoV-2 extinction as well as persistency will be also discussed and we will obtain the sufficient conditions for it. At the last all the theoretical results will be supported via numerical/graphical findings.

Cassava starch-chitosan-sorghum micro-fibrillated cellulose biocomposite wrapping film to prevent COVID-19 outspread

To prevent virus spreading, the corpse or the coffin of COVID-19 patients need to be wrapped in plastic. Low-density polyethylene (LDPE), a crude oil-based wrapping plastic, is difficult to decompose in nature after use. In this study, biocomposite wrapping film was developed from cassava starch and chitosan, with the addition of sorghum Micro-Fibrillated Cellulose (MFC) by levels of 1%, 2%, 3%, 4% and 5%. Cassava starch (raw starch) was modified by acetic anhydride to produce acetylated cassava starch (acetylated starch) which is less hydrophilic thus enhance the compounding ability with LDPE. The sorghum MFC was obtained from sorghum fibers after following processes: soda pulping, bleaching and fibrillation with a super grinder. The addition of 1% sorghum MFC into raw starch-chitosan increased the tensile strength and modulus of elasticity by 33% and 17%, respectively. On the other hand, the addition of 2% sorghum MFC into acetylated starch-chitosan increased the elongation by 38%. Wrapping film needs to have good elongation ability so that it can be stretched during application. Based on elongation characteristic, acetylated cassava starch-chitosan with addition of 2% sorghum MFC can be developed to be a candidate for biocomposite wrapping film to prevent COVID-19 outspread.