Search Results (52)

SARS-CoV and MERS-CoV are two coronaviruses that have received significant attention due to their high pathogenicity and mortality rates in human populations. In this study, we compared their evolutionary dynamics to provide a One Health perspective on their differences in terms of the results of disease control. The phylogenetic network of SARS-CoVs showed that human isolates gathered into a “super-spreader” cluster and were distinct from civet isolates. In contrast, dromedary camel- and human-isolated MERS-CoVs were clustered together. Thus, most clades of MERS-CoV can infect humans, and MERS-CoVs seem to more easily spill over the animal-to-human interface. Additionally, the civet can be easily controlled, while the intermediate host (dromedary camels) of MERS-CoV is an important livestock species, so it is impossible to eliminate all animals. This further leads to difficulties in disease control in MERS. Although MERS-CoVs are endemic to dromedary camels in both the Middle East and Africa, human infections are mainly linked to the Middle East. The nucleotide sequences of the MERS-CoV receptor gen (dipeptidyl peptidase 4 (DPP4)) from 30 Egyptians, 36 Sudanese, and 34 Saudi Arabians showed little difference. These findings suggest that the observed disparities in MERS prevalence between populations in the Middle East and Africa may be more strongly attributed to inadequate disease surveillance and the limited camel-to-human transmission of clade C MERS-CoV in Africa, rather than variations in DPP4 gene. Full article

With the rapid advancement of Internet of Things (IoT) technology, ultra-wideband flexible transparent antennas have garnered substantial attention for their potential applications in wireless communication devices. Poly(methyl methacrylate) (PMMA), renowned for its exceptional optical properties and favorable processing characteristics, has been extensively utilized as a transparent substrate material for antennas. However, the intrinsic brittleness of transparent PMMA substrates poses a significant limitation in applications such as flexible antennas. In this study, we introduce a superspreading strategy to address the complex trade-off among transparency, toughness, and dielectric properties in flexible electronics through molecular disorder engineering. The PMMA films fabricated via this superspreading strategy exhibit a visible transmittance of 85–95% at 400 nm, a toughness of 9 × 10⁵ J/m³ (representing an enhancement of 150–225% compared to conventional methods), and a frequency-stable permittivity (ε_r = 3.6 ± 0.05) within the 9–12 GHz range. These films also feature a precisely tunable thickness range of 5.5–60 μm. The PMMA-based flexible transparent antenna demonstrates a gain of 2–4 dBi and a relative bandwidth of 40%, thereby confirming its suitability for ultra-wideband applications. Collectively, this research presents a promising candidate for the development of ultra-wideband flexible transparent antennas. Full article

Reducing friction-induced squeal noise is a common issue in daily life and industrial production, particularly for elastomers. However, adjusting structure and wettability in wet environments to solve the friction-induced squeal noise remains a challenge. Here, inspired by rabbit corneas, a microchannel nanofiber array composite structure superhydrophilic elastomer material was prepared to achieve rapid liquid spreading and optimize liquid distribution. Researchers have found that when the depth of the groove microchannel is 400 μm and the length of the nanofiber is 5000 nm, water rapidly spreads on the surface in only 430 ms. This reduces self-excited vibration caused by friction, thereby reducing squealing noise by 20 decibels (dB). This article proposes a novel and direct biomimetic squealing noise reduction strategy, which has great potential in solving friction vibration noise problems in industry and daily life, such as automotive wiper blades, engines, oil lubricated bearings, etc. Full article

Continuous surveillance is critical for early intervention against emerging novel SARS-CoV-2 variants. Therefore, we investigated and compared the variant-specific evolutionary epidemiology of all the Delta and Omicron sequences collected between 2021 and 2023 in Kuwait. We used Bayesian phylodynamic models to reconstruct, trace, and compare the two variants’ demographics, phylogeographic, and host characteristics in shaping their evolutionary epidemiology. The Omicron had a higher evolutionary rate than the Delta. Both variants underwent periods of sequential growth and decline in their effective population sizes, likely linked to intervention measures and environmental and host characteristics. We found that the Delta strains were frequently introduced into Kuwait from East Asian countries between late 2020 and early 2021, while those of the Omicron strains were most likely from Africa and North America between late 2021 and early 2022. For both variants, our analyses revealed significant transmission routes from patients aged between 20 and 50 years on one side and other age groups, refuting the notion that children are superspreaders for the disease. In contrast, we found that sex has no significant role in the evolutionary history of both variants. We uncovered deeper variant-specific epidemiological insights using phylodynamic models and highlighted the need to integrate such models into current and future genomic surveillance programs. Full article

This study explores the critical challenges the livestock sector faces, particularly those related to biosecurity, animal welfare, and antibiotic use restrictions. It highlights the need to implement advanced information and communication technologies to enhance operational sustainability and decision-making. We introduce the Biorisk^® External platform, a cloud-based visit control system designed to optimize biosecurity management by accurately tracking visitor activity through QR codes and GPS geolocation. During a 6-month study period from July to December 2023, we analyzed visits to 142 different swine production sites and 30 vehicle movement patterns. The analysis revealed trends in visitation patterns and compliance with biosecurity SOPs. The software categorized visits as authorized (A), not authorized with access (NAWA), and not authorized without access (NAWOA), providing a framework to assess biosecurity risks. Additionally, network analysis identified interconnected farms, which were classified as ‘superspreaders’, highlighting their considerable risk of disease transmission. This study advocates for the integration of digital systems in livestock operations to improve biosecurity measures, facilitate real-time data input, and support informed decision-making. By enhancing biosecurity protocols through technology, the livestock industry can better safeguard animal health, increase operational efficiency, and reduce potential economic losses associated with disease outbreaks. Full article

In the midst of global efforts to curb the spread of infectious diseases, researchers worldwide are striving to unravel the intricate spatial and temporal patterns of disease transmission dynamics. Mathematical models are indispensable tools for understanding the dissemination of emerging pathogens and elucidating the evolution of epidemics. This paper introduces a novel approach by investigating city transmission networks as a framework for analyzing disease spread. In this network, major cities are depicted as nodes interconnected by edges representing disease transmission pathways. Subsequent network analysis employs various epidemiological and structural metrics to delineate the distinct roles played by cities in disease transmission. The primary objective is to identify superspreader cities. Illustratively, we apply this methodology to study COVID-19 transmission in Saudi Arabian cities, shedding light on the specific dynamics within this context. These insights offer valuable guidance for decision-making processes and the formulation of effective intervention strategies, carrying significant implications for managing public health crises. Full article

Modeling of airborne virus transmission and protection against it requires knowledge of the amount of biofluid emitted into the atmosphere and its viral load. Whereas viral concentrations in biofluids are readily measured by quantitative PCR, the total volume of fluids aerosolized during speaking, as measured by different researchers using various technologies, differs by several orders of magnitude. We compared collection methods in which the aerosols first enter into a low-humidity chamber either by direct injection or via commonly used funnel and tubing arrangements, followed by standard optical particle sizer measurement. This “collect first, measure later” approach sacrifices the recording of the temporal correlation between aerosol generation and sound types such as plosives and vowels. However, the direct-injection mode prevents inertia deposition associated with the funnel arrangements and reveals far more intermediate-size (5–20 μm in diameter) particles that can dominate the total mass of ejected respiratory aerosol. The larger aerosol mass observed with our method partially reconciles the large discrepancy between the SARS-CoV-2 infectious dose estimated from superspreader event analyses and that from human challenge data. Our results also impact measures to combat airborne virus transmission because they indicate that aerosols that settle faster than good room ventilation rates can dominate this process. Full article

The onset and early stages of dynamic wetting on different hydrophobic surfaces is investigated experimentally for aqueous solutions of two commercial trisiloxane surfacants of similar chemical structure, one of which exhibits superspreading behaviour, in order to investigate the spreading dynamics independently of the surface activity. Superspreading, or the ability of a surfactant solution to spread on a surface beyond the state determined by thermodynamic equilibrium, has been investigated for more than 30 years however its physical mechanism remains poorly understood to date despite its important applications in the formulation of agrochemicals. Surfactant solutions were prepared by dissolving S233 and S240 surfactants (Evonik Industries AG, Essen, Germany) into de-ionised water at a weight concentration of 0.1%. Drops of surfactant solutions and pure water were deposited on three horizontal substrates with different wettability (equilibrium contact angle of water ranging between ${55}^{\circ }$ and ${100}^{\circ }$), and observed from below with a high-frame rate camera to visualise the advancing contact line. The spreading ratio of drops as a function of time was extracted from high-speed videos by digital image processing. Results reveal that the superspreading solution exhibits an intermittent spreading rate, as well as peculiar features of the contact line, which are not observed for the non-superspreading solution, and confirm the superspreading effect becomes less significant when the surface energy of the substrate is decreased. Full article

Network epidemiology plays a fundamental role in understanding the relationship between network structure and epidemic dynamics, among which identifying influential spreaders is especially important. Most previous studies aim to propose a centrality measure based on network topology to reflect the influence of spreaders, which manifest limited universality. Machine learning enhances the identification of influential spreaders by combining multiple centralities. However, several centrality measures utilized in machine learning methods, such as closeness centrality, exhibit high computational complexity when confronted with large network sizes. Here, we propose a two-phase feature selection method for identifying influential spreaders with a reduced feature dimension. Depending on the definition of influential spreaders, we obtain the optimal feature combination for different synthetic networks. Our results demonstrate that when the datasets are mildly or moderately imbalanced, for Barabasi–Albert (BA) scale-free networks, the centralities’ combination with the two-hop neighborhood is fundamental, and for Erdős–Rényi (ER) random graphs, the centralities’ combination with the degree centrality is essential. Meanwhile, for Watts–Strogatz (WS) small world networks, feature selection is unnecessary. We also conduct experiments on real-world networks, and the features selected display a high similarity with synthetic networks. Our method provides a new path for identifying superspreaders for the control of epidemics. Full article

In this study, we analyze the transmission of the COVID-19 model by using a piecewise operator in the classical Caputo sense. The existence along with the uniqueness of the solution of the COVID-19 model under a piecewise derivative is presented. The numerical scheme with Newton polynomials is used to obtain a numerical solution to the model under consideration. The graphical illustrations for the suggested model are demonstrated with various fractional orders. The crossover behavior of the considered system is observed in the graphical analysis. Furthermore, the comparison of simulations with real data for three different countries is presented, where best-fitted dynamics are observed. Full article

The Omicron variant of SARS-CoV-2 rapidly spread worldwide in late 2021–early 2022, displacing the previously prevalent Delta variant. Before 16 December 2021, community transmission had already been observed in tens of countries globally. However, in Russia, the majority of reported cases at that time had been sporadic and associated with travel. Here, we report an Omicron outbreak at a student dormitory in Saint Petersburg between 16–29 December 2021, which was the earliest known instance of a large-scale community transmission in Russia. Out of the 465 sampled residents of the dormitory, 180 (38.7%) tested PCR-positive. Among the 118 residents for whom the variant had been tested by whole-genome sequencing, 111 (94.1%) were found to carry the Omicron variant. Among these 111 residents, 60 (54.1%) were vaccinated or had reported a previous infection of COVID-19. Phylogenetic analysis confirmed that the outbreak was caused by a single introduction of the BA.1.1 sub-lineage of the Omicron variant. The dormitory-derived clade constituted a significant proportion of BA.1.1 samples in Saint Petersburg and has spread to other regions of Russia and even to other countries. The rapid spread of the Omicron variant in a population with preexisting immunity to previous variants underlines its propensity for immune evasion. Full article

The wetting behavior of droplets of aqueous surfactant solutions over hydrophobic thin PVDF porous membrane and non-porous hydrophobic PVDF film is investigated for small (~10 μL) droplets of aqueous trisiloxane surfactant solutions: superspreader S 240. The time dependencies of contact angle, droplet radius, wetted area and volume were monitored as well as penetration into the porous substrate. It is shown that the fast spreading of droplets of trisiloxane solutions takes place both in the case of porous and non-porous substrates at a concentration above some critical concentration. It was found that the trisiloxane droplets penetrate into the hydrophobic porous substrates and disappear much faster than on a corresponding hydrophobic non-porous substrate, which was not observed before. This phenomenon is referred to as “superpenetration”. Full article

The Software-Defined Network (SDN) is a next-generation network that uses OpenFlow to decouple the control plane from the data plane of forwarding devices. Other protocols for southbound interfaces include ForCES and POF. However, some security issues might be in action on the SDN, so that attackers can take control of the SDN control plane. Since live video calling, QoS control, high bandwidth needs, and resource management are inevitable in any SDN/Software-Defined Cellular Network (SDCN), traffic monitoring is an integral approach for safeguarding against DDoS, heavy hitters, and superspreaders. In such a scenario, SDN traffic measurement comes into action. Thus, we survey SDN traffic measurement solutions to assess how these solutions can make a secure, efficient, and robust SDN/SDCN architecture. This research classifies SDN traffic measurement solutions according to network application behavior and compares several ML approaches. Furthermore, we find out the challenges related to SDN/SDCN traffic measurement and the future scope of research, which will guide the design and development of more advanced traffic measurement solutions for a scalable, heterogeneous, hierarchical, and widely deployed SDN/SDCN architecture. In more detail, we list different kinds of practical machine learning (ML) approaches to analyze how we can improve traffic measurement performances. We conclude that using ML in SDN traffic measurement solutions will help secure SDNs/SDCNs in complementary ways. Full article

White-tailed deer (Odocoileus virginianus, WTD) spread communicable diseases such the zoonotic coronavirus SARS-CoV-2, which is a major public health concern, and chronic wasting disease (CWD), a fatal, highly contagious prion disease occurring in cervids. Currently, it is not well understood how WTD are spreading these diseases. In this paper, we speculate that “super-spreaders” mediate disease transmission via direct social interactions and indirectly via body fluids exchanged at scrape sites. Super-spreaders are infected individuals that infect more contacts than other infectious individuals within a population. In this study, we used network analysis from scrape visitation data to identify potential super-spreaders among multiple communities of a rural WTD herd. We combined local network communities to form a large region-wide social network consisting of 96 male WTD. Analysis of WTD bachelor groups and random network modeling demonstrated that scraping networks depict real social networks, allowing detection of direct and indirect contacts, which could spread diseases. Using this regional network, we model three major types of potential super-spreaders of communicable disease: in-degree, out-degree, and betweenness potential super-spreaders. We found out-degree and betweenness potential super-spreaders to be critical for disease transmission across multiple communities. Analysis of age structure revealed that potential super-spreaders were mostly young males, less than 2.5 years of age. We also used social network analysis to measure the outbreak potential across the landscape using a new technique to locate disease transmission hotspots. To model indirect transmission risk, we developed the first scrape-to-scrape network model demonstrating connectivity of scrape sites. Comparing scrape betweenness scores allowed us to locate high-risk transmission crossroads between communities. We also monitored predator activity, hunting activity, and hunter harvests to better understand how predation influences social networks and potential disease transmission. We found that predator activity significantly influenced the age structure of scraping communities. We assessed disease-management strategies by social-network modeling using hunter harvests or removal of potential super-spreaders, which fragmented WTD social networks reducing the potential spread of disease. Overall, this study demonstrates a model capable of predicting potential super-spreaders of diseases, outlines methods to locate transmission hotspots and community crossroads, and provides new insight for disease management and outbreak prevention strategies. Full article

During a pandemic, public discussion and decision-making may be required in face of limited evidence. Data-grounded analysis can support decision-makers in such contexts, contributing to inform public policies. We present an empirical analysis method based on regression modelling and hypotheses testing to assess events for the possibility of occurrence of superspreading contagion with geographically heterogeneous impacts. We demonstrate the method by evaluating the case of the May 1st, 2020 Demonstration in Lisbon, Portugal, on regional growth patterns of COVID-19 cases. The methodology enabled concluding that the counties associated with the change in the growth pattern were those where likely means of travel to the demonstration were chartered buses or private cars, rather than subway or trains. Consequently, superspreading was likely due to travelling to/from the event, not from participating in it. The method is straightforward, prescribing systematic steps. Its application to events subject to media controversy enables extracting well founded conclusions, contributing to informed public discussion and decision-making, within a short time frame of the event occurring. Full article