Transmission Scenarios Research Articles

Effect of General Cross-Immunity Protection and Antibody-Dependent Enhancement in Dengue Dynamics

A mathematical model to describe the dynamic of a multiserotype infectious disease at the population level is studied. Applied to dengue fever epidemiology, we analyse a mathematical model with time delay to describe the cross-immunity protection period, including a key parameter for the antibody-dependent enhancement (ADE) effect, the well-known features of dengue fever infection. Numerical experiments are performed to show the stability of the coexistence equilibrium, which is completely determined by the basic reproduction number and by the invasion reproduction number, as well as the bifurcation structures for different scenarios of dengue fever transmission in a population. The model shows a rich dynamical behavior, from fixed points and periodic oscillations up to chaotic behaviour with complex attractors.

Reopen schools safely: simulating COVID-19 transmission on campus with a contact network agent-based model

ABSTRACT As the COVID-19 vaccination has been quickly rolling out around the globe, the evaluation of the effects of vaccinating populations for the safe reopening of schools has become a focal point for educators, decision-makers, and the general public. Within this context, we develop a contact network agent-based model (CN-ABM) to simulate on-campus disease transmission scenarios. The CN-ABM establishes contact networks for agents based on their daily activity patterns, evaluates the agents’ health status change in different activity environments, and then simulates the epidemic curve. By applying the model to a real-world campus environment, we identify how different community risk levels, teaching modalities, and vaccination rates would shape the epidemic curve. The results show that without vaccination, retaining under 50% of on-campus students can largely flatten the curve, and having 25% on-campus students can achieve the best result (peak value < 1%). With vaccination, having a maximum of 75% on-campus students and at least a 45% vaccination rate can suppress the curve, and a 65% vaccination rate can achieve the best result. The developed CN-ABM can be employed to assist local government and school officials with developing proactive intervention strategies to safely reopen schools.

Epidemiological differences between sexes affect management efficacy in simulated chronic wasting disease systems

Abstract Sex‐based differences in physiology, behaviour and demography commonly result in differences in disease prevalence. However, sex differences in prevalence may reflect exposure rather than transmission, which could affect disease control programmes. One potential example is chronic wasting disease (CWD), which has been observed at greater prevalence among male than female deer. We used an age‐ and sex‐structured simulation model to explore harvest‐based management of CWD under three different transmission scenarios that all generate higher male prevalence: (1) increased male susceptibility, (2) high male‐to‐male transmission or (3) high female‐to‐male transmission. Both female and male harvests were required to limit CWD epidemics across all transmission scenarios (approximated by R0), though invasion was more likely under high female‐to‐male transmission. In simulations, heavily male‐biased harvests controlled CWD epidemics and maintained large host populations under high male‐to‐male transmission and increased male susceptibility scenarios. However, male‐biased harvests were ineffective under high female‐to‐male transmission. Instead, female‐biased harvests were able to limit disease transmission under high female‐to‐male transmission but incurred a trade‐off with smaller population sizes. Synthesis and applications. Higher disease prevalence in a sex or age group may be due to higher exposure or susceptibility but does not necessarily indicate if that group is responsible for more disease transmission. We showed that multiple processes can result in the pattern of higher male prevalence, but that population‐level management interventions must focus on the sex responsible for disease transmission, not just those that are most exposed.

SARS-CoV-2 transmission in opposition-controlled Northwest Syria: modeling pandemic responses during political conflict

IntroductionTen years of conflict has displaced more than half of Northwest Syria's (NWS) population and decimated the health system, water and sanitation, and public health infrastructure vital for infectious disease control. The first NWS COVID-19 case was declared on July 9, 2020, but impact estimations in this region are minimal. With the rollout of vaccination and emergence of the B.1.617.2 (Delta) variant, we aimed to estimate the COVID-19 trajectory in NWS and the potential effects of vaccine coverage and hospital occupancy.MethodsWe conducted a mixed-method study, primarily including modeling projections of COVID-19 transmission scenarios with vaccination strategies using an age-structured, compartmental susceptible-exposed-infectious-recovered (SEIR) model, supported by data from 20 semi-structured interviews with frontline health workers to help contextualize interpretation of modeling results.ResultsModeling suggested that existing low stringency non-pharmaceutical interventions (NPIs) minimally affected COVID-19 transmission. Maintaining existing NPIs after the Delta variant introduction is predicted to result in a second COVID-19 wave, overwhelming hospital capacity and resulting in a fourfold increased death toll. Simulations with up to 60% vaccination coverage by June 2022 predict that a second wave is not preventable with current NPIs. However, 60% vaccination coverage by June 2022 combined with 50% coverage of mask-wearing and handwashing should reduce the number of hospital beds and ventilators needed below current capacity levels. In the worst-case scenario of a more transmissible and lethal variant emerging by January 2022, the third wave is predicted.ConclusionTotal COVID-19 attributable deaths are expected to remain relatively low owing largely to a young population. Given the negative socioeconomic consequences of restrictive NPIs, such as border or school closures for an already deeply challenged population and their relative ineffectiveness in this context, policymakers and international partners should instead focus on increasing COVID-19 vaccination coverage as rapidly as possible and encouraging mask-wearing.

Power Grid Field Violation Recognition Algorithm Based on Enhanced YOLOv5

Aiming at the problem that Yolov5 is difficult to accurately detect backlighting and small samples in national grid power transmission and distribution operations, studies the illegal behavior technology of “two wear and one wear” in power grid operation, and proposes a violation recognition algorithm based on the enhanced YOLOv5. First, add a new detection layer and use the BiFPN (bi-directional feature pyramid network) layer for feature fusion, so that feature layers of different scales can better learn the weight distribution and enhance the fusion ability. Secondly, add CBAM (Convolutional Block Attention Module) module before the output detection layer feature map to make full use of channel and spatial information to achieve better model accuracy and recall. The experimental results on the six self-made data sets show that the mAP of this method is 91.0%, which is 5.6% higher than the original algorithm, indicating that the model has stronger predictive ability and robustness for the identification of personnel and safety tools in transmission and distribution scenarios.

1.71 Tb/s Single-Channel and 56.51 Tb/s DWDM Transmission Over 96.5 km Field-Deployed SSMF

We report an industry leading optical dense wavelength division multiplexing (DWDM) field trial with line rates per channel <inline-formula> <tex-math notation="LaTeX">$\ge 1.66$ </tex-math></inline-formula> Tb/s using 130 GBaud dual-polarization probabilistic constellation shaping 256-ary quadrature amplitude modulation (DP-PCS256QAM) in a high capacity data center interconnect (DCI) scenario. This research trial was performed on 96.5 km of field-deployed standard single mode G.652 fiber infrastructure of Deutsche Telekom in Germany employing Erbium-doped fiber amplifier (EDFA)-only amplification. A total of 34 channels were transmitted with 150 GHz spacing for a total fiber capacity of 56.51 Tb/s and a spectral efficiency higher than 11bit/s/Hz. In the single-channel transmission scenario 1.71 Tb/s was achieved over the same link. In addition, we successfully demonstrate record net bitrates of 1.88 Tb/s in back-to-back (B2B) using 130 GBaud DP-PCS400QAM.

Cost-effective proactive testing strategies during COVID-19 mass vaccination: A modelling study

BackgroundAs SARS-CoV-2 vaccines are administered worldwide, the COVID-19 pandemic continues to exact significant human and economic costs. Mass testing of unvaccinated individuals followed by isolation of positive cases can substantially mitigate risks and be tailored to local epidemiological conditions to ensure cost effectiveness.MethodsUsing a multi-scale model that incorporates population-level SARS-CoV-2 transmission and individual-level viral load kinetics, we identify the optimal frequency of proactive SARS-CoV-2 testing, depending on the local transmission rate and proportion immunized.FindingsAssuming a willingness-to-pay of US$100,000 per averted year of life lost (YLL) and a price of $10 per test, the optimal strategy under a rapid transmission scenario (Re ∼ 2.5) is daily testing until one third of the population is immunized and then weekly testing until half the population is immunized, combined with a 10-day isolation period of positive cases and their households. Under a low transmission scenario (Re ∼ 1.2), the optimal sequence is weekly testing until the population reaches 10% partial immunity, followed by monthly testing until 20% partial immunity, and no testing thereafter.InterpretationMass proactive testing and case isolation is a cost effective strategy for mitigating the COVID-19 pandemic in the initial stages of the global SARS-CoV-2 vaccination campaign and in response to resurgences of vaccine-evasive variants.FundingUS National Institutes of Health, US Centers for Disease Control and Prevention, HK Innovation and Technology Commission, China National Natural Science Foundation, European Research Council, and EPSRC Impact Acceleration Grant.

Online Teaching Wireless Video Stream Resource Dynamic Allocation Method considering Node Ability

At present, wireless network technology is advancing rapidly, and intelligent equipment is gradually popularized, which rapidly developed the mobile streaming media business. All kinds of mobile video applications have enriched people’s lives by carrying huge traffic randomly. Wireless networks (WNs) are facing an unprecedented burden, which allocates very important wireless video resources. Similarly, in WNs, the network status is dynamic and the terminal is heterogeneous, which causes the traditional video transmission system to fail to meet the needs of users. Hence, Scalable Video Coding (SVC) has been introduced in the video transmission system to achieve bit rate adaptation. However, in a strictly hierarchical traditional computer network, the wireless resource allocation strategy usually takes throughput as the only way to optimize the target, and it is terrible to make more optimizations for scalable video transmission. This article proposed a cross-layer design to enable information to be transmitted between the wireless base station and the video server to achieve joint optimization. To improve users’ satisfaction with video services, the wireless resource allocation problem and the video stream scheduling problem are jointly considered, which keep the optimization space larger. Based on the proposed architecture, we further study the design of wireless resource allocation algorithms and rate-adaptive algorithms for the scenario of multiuser transmission of scalable video in the Long-Term Evolution (LTE) downlink. Experimental outcomes have shown substantial performance enhancement of the proposed work.

Detecting the Presence of Electronic Devices in Smart Homes Using Harmonic Radar Technology

Data about users is collected constantly by phones, cameras, Internet websites, and others. The advent of so-called ‘Smart Things’ now enable ever-more sensitive data to be collected inside that most private of spaces: the home. The first step in helping users regain control of their information (inside their home) is to alert them to the presence of potentially unwanted electronics. In this paper, we present a system that could help homeowners (or home dwellers) find electronic devices in their living space. Specifically, we demonstrate the use of harmonic radars (sometimes called nonlinear junction detectors), which have also been used in applications ranging from explosives detection to insect tracking. We adapt this radar technology to detect consumer electronics in a home setting and show that we can indeed accurately detect the presence of even ‘simple’ electronic devices like a smart lightbulb. We evaluate the performance of our radar in both wired and over-the-air transmission scenarios.

Linear Encryption Against Eavesdropping on Remote State Estimation

This article considers the problem of eavesdropping on remote state estimation. Linear encryption strategies are used to protect the transmitted data. Two types of data transmission are considered: raw measurements generated by traditional sensors as well as innovations generated by smart sensors. For these two transmission scenarios, the encryption coefficients are obtained by formulating different optimization problems, with the target of maximizing the eavesdropper's estimation error covariance. For stable systems, the designed encryption strategies can effectively impair the eavesdropper's estimation performance. For unstable systems, the encryption can be designed to make the eavesdropper's estimation error covariance divergent. The encryption performance is evaluated through numerical simulations on both stable and unstable systems.

QUIC vs TCP: A Performance Evaluation over LTE with NS-3

In the vast majority of mobile applications, the Transmission Control Protocol (TCP) is still leveraged at the transport layer of the Internet’s protocol stack. But, in many cases, the performance of TCP over mobile networks has been proven sub-optimal in practice, thus causing substantial bottlenecks. Quick UDP Internet Connections (QUIC) is a new protocol, currently being standardized by the Internet Engineering Task Force (IETF), that aims at solving some of the inherent problems of TCP. The purpose of this paper is to provide a comprehensive overview of QUIC and compare the performance of QUIC and TCP in wireless networks. To compare QUIC with TCP under various transmission scenarios over LTE networks, the ns-3 network simulator has been employed. The simulations performed showed that 1) under good or average transmission conditions, QUIC is characterized by a better steady state throughput at the same time achieving quite lower file download times; and 2) under poor transmission conditions, the two protocols exhibit a similar performance.

Rate-Splitting Multiple Access: Fundamentals, Survey, and Future Research Trends

Rate-splitting multiple access (RSMA) has emerged as a novel, general, and powerful framework for the design and optimization of non-orthogonal transmission, multiple access (MA), and interference management strategies for future wireless networks. Through information and communication theoretic analysis, RSMA has been shown to be optimal (from a Degrees-of-Freedom region perspective) in several transmission scenarios. Compared to the conventional MA strategies used in 5G, RSMA enables spectral efficiency (SE), energy efficiency (EE), coverage, user fairness, reliability, and quality of service (QoS) enhancements for a wide range of network loads (including both underloaded and overloaded regimes) and user channel conditions. Furthermore, it enjoys a higher robustness against imperfect channel state information at the transmitter (CSIT) and entails lower feedback overhead and complexity. Despite its great potential to fundamentally change the physical (PHY) layer and media access control (MAC) layer of wireless communication networks, RSMA is still confronted with many challenges on the road towards standardization. In this paper, we present the first comprehensive overview on RSMA by providing a survey of the pertinent state-of-the-art research, detailing its architecture, taxonomy, and various appealing applications, as well as comparing with existing MA schemes in terms of their overall frameworks, performance, and complexities. An in-depth discussion of future RSMA research challenges is also provided to inspire future research on RSMA-aided wireless communication for beyond 5G systems.

Travel-related Importation and Exportation Risks of SARS-CoV-2 Omicron Variant in 367 Prefectures (Cities) - China, 2022.

IntroductionMinimizing the importation and exportation risks of coronavirus disease 2019 (COVID-19) is a primary concern for sustaining the “Dynamic COVID-zero” strategy in China. Risk estimation is essential for cities to conduct before relaxing border control measures.MethodsInformed by the daily number of passengers traveling between 367 prefectures (cities) in China, this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation risks.ResultsUnder the transmission scenario (R0=5.49), this study estimated the cumulative case incidence of Changchun City, Jilin Province as 3,233 (95% confidence interval: 1,480, 4,986) before a lockdown on March 14, 2022, which is close to the 3,168 cases reported in real life by March 16, 2022. In a total of 367 prefectures (cities), 127 (35%) had high exportation risks according to the simulation and could transmit the disease to 50% of all other regions within a period from 17 to 94 days. The average time until a new infection arrives in a location in 1 of the 367 prefectures (cities) ranged from 26 to 101 days.ConclusionsEstimating COVID-19 importation and exportation risks is necessary for preparedness, prevention, and control measures of COVID-19 — especially when new variants emerge.

Measurement and Simulation-Based Exposure Assessment at a Far-Field for a Multitechnology Cellular Site up to 5G NR

5G is expected to be the dominant technology for mobile networks in the coming years, but there is concern about the increase in the total electromagnetic field radiation levels due to the deployment of the 5G technology. This paper presents an exposure assessment of electromagnetic field radiation on humans from single base station of a mobile network serving in dense, urban, suburban, and rural area scenarios for single-site transmission with multi-technology, including 2G, 3G, 4G, IoT, and 5G which have recently been deployed. This assessment is performed using simulation to predict the received signal levels and to calculate the related power densities for a typical single site under operating field configurations and settings for each technology. Field measurements were performed using a drive test tool to validate and calibrate the simulation results. The results show the total exposure ratio was very low compared to the international standard exposure limits, and the results show the contribution from each technology for these spesfic sites used in this study.

Fronthaul Optical Links Using Sub-Nyquist Sampling Rate ADC for B5G/6G Sub-THz Ma-MIMO Beamforming

This paper details fronthaul optical links using sub-Nyquist sampling rate analog-to-digital converters (ADCs) for Beyond fifth generation (B5G) and 6G sub-THz massive multiple-input multiple-output (Ma-MIMO) beamforming. Unlike Common Public Radio Interface (CPRI) using high speed ADCs in current fronthaul link, the proposed scheme involves ADCs operating at sub-Nyquist sampling rate for each antenna element. Based on pre-allocated relative time delays, pre-processed orthogonal frequency-division multiplexing (OFDM) signals sent from a baseband unit (BBU) can be deaggregated to different Ma-MIMO OFDM signals by sub-Nyquist sampling rate ADCs. In experiments, we assume that each remote radio unit (RRU) is equipped with 32/64 antenna elements and 32/64 ADCs operating at 1/32 and 1/64 of the Nyquist sampling rate. Furthermore, the received Ma-MIMO OFDM signal is then up-converted to 100-GHz for wireless transmission and defined as Ma-MIMO RF OFDM signal. We simulate the 32/64 antenna elements transmission scenario by individually transmit and demodulate each Ma-MIMO RF OFDM signal with 32/64 times of point-to-point antenna transmission. The error vector magnitude (EVM) and signal-to-noise ratio (SNR) of each received Ma-MIMO RF OFDM signal are less than 8&#x0025; and 26 dB, respectively. And the total received 64 Ma-MIMO RF OFDM signals will require line rate as high as 393.6374 Gb/s according to CPRI option-7. Notably, the proposed scheme reduces the requirement of sampling rate and enables all the Ma-MIMO OFDM signals at baseband without the insertion of guard band. Thus, the proposed scheme can reduce the complexity of signal deaggregation and power consumption in the demodulation process, leading to an improvement in cost efficiency.

Latency versus Reliability in LEO Mega-Constellations: Terrestrial, Aerial, or Space Relay

Large low earth orbit (LEO) mega-constellation systems have been designed and deployed as a global backbone to provide ubiquitous connectivity across the world. However, due to the high traffic load/congestion arisen from the required numerous information relay and forwarding, it is a challenge for LEO mega-constellation systems to set up long-distance connections between two remote terrestrial users for real-time communications, which requires strict low latency. Other than inter-LEO satellite links (ILSL), introducing third-party relays, such as terrestrial, aerial, and satellite relays, is an alternative way to improve the latency performance for wide-area deliveries of real-time traffic. However, the reliability of the transmitted signal will unavoidably degrade, because of the increased path-loss attributed to long-distance relaying transmissions. Then, to reveal the principle that the third-party relays affect the latency and reliability, in this work, an LEO satellite-terrestrial communication scenario is considered, in which two remote terrestrial users communicate with each other via an LEO mega-constellation system. Analysis models are built up to investigate the end-to-end time delay and outage performance while considering different ILSL, terrestrial, aerial, and satellite relay assisted transmission scenarios. More specifically, by applying geometrical probability theory, exact/approximated closed-form analytical expressions have been derived for average time delay

Simulation modeling of multi-stream data transmission in the AnyLogic environment

The paper considers a simulation model of multi-path data transmission built in the AnyLogic environment. The use of a multi-path data transmission scenario is extremely relevant today since user devices have more than one communication interface, and the amount of traffic is growing. We analyzed the QoS characteristics for a scenario with two sub-paths. It has been shown that a policy of allocation data into subpaths according to the amount of free resources can lead to the problem of incorrect packet order on the receiving side. In addition, it is obvious that the AnyLogic environment can be used to model telecommunication systems at a high level of abstraction.

Projecting the Combined Health Care Burden of Seasonal Influenza and COVID-19 in the 2020-2021 Season.

Background. In mid-2020, there was significant concern that the overlapping 2020–2021 influenza season and COVID-19 pandemic would overwhelm already stressed health care systems in the Northern Hemisphere, particularly if influenza immunization rates were low. Methods. Using a mathematical susceptible-exposed-infected-recovered (SEIR) compartmental model incorporating the age-specific viral transmission rates and disease severity of Austin, Texas, a large metropolitan region, we projected the incidence and health care burden for both COVID-19 and influenza across observed levels of SARS-CoV-2 transmission and influenza immunization rates for the 2020–2021 season. We then retrospectively compared scenario projections made in August 2020 with observed trends through June 2021. Results. Across all scenarios, we projected that the COVID-19 burden would dwarf that of influenza. In all but our lowest transmission scenarios, intensive care units were overwhelmed by COVID-19 patients, with the levels of influenza immunization having little impact on health care capacity needs. Consistent with our projections, sustained nonpharmaceutical interventions (NPIs) in Austin prevented COVID-19 from overwhelming health care systems and almost completely suppressed influenza during the 2020–2021 respiratory virus season. Limitations. The model assumed no cross-immunity between SARS-CoV-2 and influenza, which might reduce the burden or slow the transmission of 1 or both viruses. Conclusion. Before the widespread rollout of the SARS-CoV-2 vaccine, COVID-19 was projected to cause an order of magnitude more hospitalizations than seasonal influenza because of its higher transmissibility and severity. Consistent with predictions assuming strong NPIs, COVID-19 strained but did not overwhelm local health care systems in Austin, while the influenza burden was negligible. Implications. Nonspecific NPI efforts can dramatically reduce seasonal influenza burden and preserve health care capacity during respiratory virus season.HighlightsAs the COVID-19 pandemic threatened lives worldwide, the Northern Hemisphere braced for a potential “twindemic” of seasonal influenza and COVID-19.Using a validated mathematical model of influenza and SARS-CoV-2 co-circulation in a large US city, we projected the impact of COVID-19–driven nonpharmaceutical interventions combined with influenza vaccination on health care capacity during the 2020–2021 respiratory virus season.We describe analyses conducted during summer 2020 to help US cities prepare for the 2020–2021 influenza season and provide a retrospective evaluation of the initial projections.

A Robust Reversible Data Hiding Framework for Video Steganography Applications

Reversible Data Hiding (RDH) is a special form of data hiding approach for data integrity and confidentiality protection where the secret image bits (SI) are embedded into Cover Media (CM) by altering its intrinsic pixel attributes. However, in RDH the CM along with the secret message is recovered at the end of computing phase. However, despite of its potential use-cases for enhancing the embedding performance, when it comes to security for various network standards, the traditional RDH mechanisms cannot fully comply with the standards for different set of attacks during the bit-stream transmission scenarios. Therefore, the proposed study contributes towards a computational framework of a robust RDH framework for Video Steganography (VS) which is modeled and simulated under various attack effects and the observation outcome are produced in before and after attack situations to justify the improvement over Embedding Capacity (EC) and Peak Signal-to-Noise Ratio (PSNR) performance for both CM and secret message unlike traditional difference expansion-based methods (DE). The outcome of the study shows that the formulated RDH method not only achieves better reversibility at lower cost of computing but also ensures effective PSNR and imperceptibility outcome for both CM and secret image.

Update of the Phlebotominae Fauna with New Records for Argentina and Observations on Leishmaniasis Transmission Scenarios at a Regional Scale

Phlebotominae are small insects distributed in the Americas from Canada to Argentina and Uruguay, counting with more than 500 neotropical species. Some of them have a vectorial role in the transmission of Leishmania Ross, the causative agent of leishmaniases, a group of worldwide distributed diseases with different clinical manifestations and transmission cycles. Our aim was to update the Phlebotominae fauna of Argentina and to make observations on the American Cutaneous (ACL) and Visceral Leishmaniasis (AVL) transmission scenarios, according to the distribution of proven or suspected Leishmania vector species and recent changes in land use. Primary data (entomological captures) and secondary data (review of 65 scientific publications with Phlebotominae records) were used. With 9 new records, 46 Phlebotominae species are now recorded through the area comprising 14 political jurisdictions and 6 phytogeographic provinces. Distribution maps were constructed for the 5 proven or incriminated Leishmania vector species, and the evidence supporting the vectorial incrimination of these species is discussed. Three main ACL transmission scenarios are described in the phytogeographic provinces of the Yungas, Chaco, and Paranaense, associated with deforestation processes, while the transmission scenarios of AVL are urban outbreaks and scattered cases in rural areas. We update the available knowledge on the Phlebotominae fauna present in Argentina, emphasizing its epidemiological relevance in the current context of the increasing frequency of ACL outbreaks and geographic spread of AVL.