Mechanisms Of Virus Transmission Research Articles

Reliable Augmentation and Precise Identification of EPG Waveforms Based on Multi-Criteria DCGAN

The electrical penetration graph (EPG) technique is of great significance in elucidating the mechanisms of virus transmission by piercing-sucking insects and crop resistance to these insects. The traditional method of manually processing EPG signals encounters the drawbacks of inefficiency and subjectivity. This study investigated the data augmentation and automatic identification of various EPG signals, including A, B, C, PD, E1, E2, and G, which correspond to distinct behaviors exhibited by the Asian citrus psyllid. Specifically, a data augmentation method based on an improved deep convolutional generative adversarial network (DCGAN) was proposed to address the challenge of insufficient E1 waveforms. A multi-criteria evaluation framework was constructed, leveraging maximum mean discrepancy (MMD) to evaluate the similarity between the generated and real data, and singular value decomposition (SVD) was incorporated to optimize the training iterations of DCGAN and ensure data diversity. Four models, convolutional neural network (CNN), K-nearest neighbors (KNN), decision tree (DT), and support vector machine (SVM), were established based on DCGAN to classify the EPG waveforms. The results showed that the parameter-optimized DCGAN strategy significantly improved the model accuracies by 5.8%, 6.9%, 7.1%, and 7.9% for DT, SVM, KNN, and CNN, respectively. Notably, DCGAN-CNN effectively addressed the skewed distribution of EPG waveforms, achieving an optimal classification accuracy of 94.13%. The multi-criteria optimized DCGAN-CNN model proposed in this study enables reliable augmentation and precise automatic identification of EPG waveforms, holding significant practical implications for understanding psyllid behavior and controlling citrus huanglongbing.

Highly pathogenic avian influenza A(H5N1) virus infections on fur farms connected to mass mortalities of black-headed gulls, Finland, July to October 2023.

Highly pathogenic avian influenza (HPAI) has caused widespread mortality in both wild and domestic birds in Europe 2020-2023. In July 2023, HPAI A(H5N1) was detected on 27 fur farms in Finland. In total, infections in silver and blue foxes, American minks and raccoon dogs were confirmed by RT-PCR. The pathological findings in the animals include widespread inflammatory lesions in the lungs, brain and liver, indicating efficient systemic dissemination of the virus. Phylogenetic analysis of Finnish A(H5N1) strains from fur animals and wild birds has identified three clusters (Finland I-III), and molecular analyses revealed emergence of mutations known to facilitate viral adaptation to mammals in the PB2 and NA proteins. Findings of avian influenza in fur animals were spatially and temporally connected with mass mortalities in wild birds. The mechanisms of virus transmission within and between farms have not been conclusively identified, but several different routes relating to limited biosecurity on the farms are implicated. The outbreak was managed in close collaboration between animal and human health authorities to mitigate and monitor the impact for both animal and human health.

Deciphering the Role of Virus Receptors in Plant–Virus–Vector Interactions

Insect-transmitted plant viruses are a major threat to global agricultural crop production. Receptors play a prominent role in the interplay between host-pathogen and vector interaction. The virus–vector relationship involves both viral and vector receptors. Receptors-like kinases (RLKs) and receptor-like proteins play a crucial role in plant immunity, which acts as a basal defense. Pathogens can evade or block host recognition by their effector proteins to inhibit pathogen recognition receptor (PRR)-mediated signaling. Intriguingly, RLKs are also known to interact with viral proteins and impact plant susceptibility against viruses, while the endocytic receptors in vectors assist in the binding of the virus to the vectors. Unlike other receptors of fungi and bacteria which have three different domains located from extracellular or intracellular to perceive a multitude of molecular patterns, the characterization of viral receptors is quite complex and limited since the virus is directly injected into plant cells by insect vectors. Little is known about these receptors. Unraveling the receptors involved in virus entry and transmission within the vector will provide vital information in virus–vector interactions. This review focuses on efforts undertaken in the identification and characterization of receptors of plant viruses within the host and vector. This will lead to a better understanding of the cellular mechanism of virus transmission and spread, and further suggests new alternative tools for researchers to develop an integrated approach for the management of viral diseases and associated vectors.

Identification of a novel HIV-1 third-generation circulating recombinant form (CRF126_0755) in Guangdong, China

The genetic recombination patterns and genetic distribution of HIV-1 are valuable for elucidating the epidemic and genetic diversity of HIV. Numerous HIV-1 circulating recombinant forms (CRFs) have recently emerged and disseminated rapidly. In China, at least 32 CRFs have been reported to account for more than 80% of all HIV infections. However, CRFs derived from the CRF07_BC and CRF55_01B lineages have never been recorded. Here, a novel third-generation CRF involving HIV-1 was identified in four HIV-1-infected patients in Guangdong, China, who had no epidemiological association with each other. Phylogenetic and recombinant analyses confirmed that these strains shared highly similar recombination patterns, with the CRF07_BC backbone substituted by a CRF55_01B segment; therefore, these strains were classified as CRF126_0755. This is the first study of a CRF derived from CRF07_BC and CRF55_01B. Bayesian phylogenetic inference suggested that CRF126_0755 originated in approximately 2005-2007. The present findings reveal that the genotype composition of HIV-1 has become more complex than that of other viruses and highlight the urgent need for continuous molecular screening and epidemic surveillance within HIV-1-infected populations to advance our understanding of viral transmission mechanisms.

Virus detection light diffraction fingerprints for biological applications.

The transmission of viral diseases is highly unstable and highly contagious. As the carrier of virus transmission, cell is an important factor to explore the mechanism of virus transmission and disease. However, there is still a lack of effective means to continuously monitor the process of viral infection in cells, and there is no rapid, high-throughput method to assess the status of viral infection. On the basis of the virus light diffraction fingerprint of cells, we applied the gray co-occurrence matrix, set the two parameters effectively to distinguish the virus status and infection time of cells, and visualized the virus infection process of cells in high throughput. We provide an efficient and nondestructive testing method for the selection of excellent livestock and poultry breeds at the cellular level. Meanwhile, our work provides detection methods for the recessive transmission of human-to-human, animal-to-animal, and zoonotic diseases and to inhibit and block their further development.

Reduction of acute respiratory infections in day-care by non-pharmaceutical interventions: a narrative review.

Children who start in day-care have 2-4 times as many respiratory infections compared to children who are cared for at home, and day-care staff are among the employees with the highest absenteeism. The extensive new knowledge that has been generated in the COVID-19 era should be used in the prevention measures we prioritize. The purpose of this narrative review is to answer the questions: Which respiratory viruses are the most significant in day-care centers and similar indoor environments? What do we know about the transmission route of these viruses? What evidence is there for the effectiveness of different non-pharmaceutical prevention measures? Literature searches with different terms related to respiratory infections in humans, mitigation strategies, viral transmission mechanisms, and with special focus on day-care, kindergarten or child nurseries, were conducted in PubMed database and Web of Science. Searches with each of the main viruses in combination with transmission, infectivity, and infectious spread were conducted separately supplemented through the references of articles that were retrieved. Five viruses were found to be responsible for ≈95% of respiratory infections: rhinovirus, (RV), influenza virus (IV), respiratory syncytial virus (RSV), coronavirus (CoV), and adenovirus (AdV). Novel research, emerged during the COVID-19 pandemic, suggests that most respiratory viruses are primarily transmitted in an airborne manner carried by aerosols (microdroplets). Since airborne transmission is dominant for the most common respiratory viruses, the most important preventive measures consist of better indoor air quality that reduces viral concentrations and viability by appropriate ventilation strategies. Furthermore, control of the relative humidity and temperature, which ensures optimal respiratory functionality and, together with low resident density (or mask use) and increased time outdoors, can reduce the occurrence of respiratory infections.

Using Agent-Based Modeling to Examine Risk for COVID-19 Infection in Custodial Settings.

Research on pandemics in institutional settings often assumes that all human interactions within a jail pose similar viral transmission risks. We developed an agent-based model (ABM) called Simulation Applications for Forecasting Effective Responses in Corrections (SAFER-C™) to simulate nine scenarios of possible interactions and virus transmission among incarcerated individuals and jail staff and tested this assumption. We found that resumption of high-contact activities has a greater impact on the number of infections, while out-of-cell group sizes and initial vaccination rates had lower impact. This work emphasizes the importance of understanding and modeling human interactions in confinement facilities, as well as understanding, responding to, and limiting the mechanism of viral transmission in jails. Insights from ABMs provide correctional administrators with realistic options for managing responses.

Global Mapping and Visualization Analysis of One Health Knowledge in the COVID-19 Context.

Globally, the COVID-19 pandemic had a significant impact on the health, social, and economic systems, triggering lasting damage and exposing the complexity of the problem beyond just being a health emergency. This crisis has highlighted the need for a comprehensive and collaborative strategy to successfully counter infectious diseases and other global challenges. With the COVID-19 pandemic pushing One Health to the forefront of global health and sustainable development agendas, this concept has emerged as a potential approach for addressing these challenges. In the context of COVID-19, this study investigates global knowledge about One Health by examining its state, significant contributions, and future directions. It seeks to offer an integrated framework of insights guiding the development of well-informed decisions. A comprehensive search using the Scopus database was conducted, employing specific terms related to One Health and COVID-19. VOSviewer 1.6.19 software was used to generate network visualization maps. Countries' research output was adjusted based on their gross domestic product (GDP) and population size. The study identified a total of 527 publications. The United States led with 134 documents (25.4%), but India topped the adjusted ranking. One Health journal stood as the most common outlet for disseminating knowledge (49 documents; 9.3%), while Centers for Disease Control and Prevention (CDC), the United States emerged as the most prolific institution (13 documents; 2.5%). Key topics were related to the virus transmission mechanisms, climate change impacts, antimicrobial resistance, ecosystem health, preparedness, collaboration, community engagement, and developing of efficient surveillance systems. The study emphasizes how critical it is to capitalize on the present momentum of COVID-19 to advance One Health concepts. Integrating social and environmental sciences, and a variety of professions for better interaction and collaboration is crucial. Additionally, increased funding for developing countries, and legislative empowerment are vital to advance One Health and boost disease prevention.

Probability of transmission of SARS-CoV-2 virus pathogens in long-distance passenger transport

This paper presents a description of the methodology developed for estimation of pathogen transmission in transport and the results of the case study application for long-distance passenger transport. The primary objective is to report the method developed and the application for case studies in various passenger transport services. The most important findings and achievements of the presented study are the original universal methodology to estimate the probability of pathogen transmission with full mathematical disclosure and an open process formula, to make it possible to take other specific mechanisms of virus transmission when providing transport services. The results presented conducted an analysis on the mechanisms of transmission of SARS-CoV-2 virus pathogens during the transport process, to examine the chain of events as a result of which passengers may be infected. The author proposed a new method to estimate the probability of transmission of viral pathogens using the probability theory of the sum of elementary events. This is a new approach in this area, the advantage of which is a fully explicit mathematical formula that allows the method to be applied to various cases. The findings of this study can facilitate the management of epidemic risk in passenger transport operators and government administration. It should be clearly emphasised that the developed method and estimated values are the probabilities of pathogen transmission. Estimating the probability of transmission of the SARS-CoV-2 virus pathogen is not the same as the probability of viral infection, and more so the probability of contracting COVID-19. Viral infection strongly depends on viral mechanisms, exposure doses, and contact frequency. The probability of contracting COVID-19 and its complications depends on the individual characteristics of the immune system, even with confirmed viral infection. However, it is undoubtedly that the probability of transmission of the SARS-CoV-2 virus pathogen is the most reliable measure of infection risk, which can be estimated according to the objective determinants of pathogen transmission.

A Coxsackievirus B1-mediated nonlytic Extracellular Vesicle-to-cell mechanism of virus transmission and its possible control through modulation of EV release.

Like most non-enveloped viruses, CVB1 mainly uses cell lysis to spread. Details of a nonlytic virus transmission remain unclear. Extracellular Vesicles (EVs) transfer biomolecules between cells. We show that CVB1 entry into HeLa cells results in apoptosis and release of CVB1-induced 'medium-sized' EVs (CVB1i-mEVs). These mEVs (100-300 nm) harbour CVB1 as shown by immunoblotting with anti-CVB1-antibody; viral capsids were detected by transmission electron microscopy and RT-PCR revealed CVB1 RNA. The percentage of mEVs released from CVB1-infected HeLa cells harbouring virus was estimated from TEM at 34 %. Inhibition of CVB1i-mEV production, with calpeptin or siRNA knockdown of CAPNS1 in HeLa cells limited spread of CVB1 suggesting these vesicles disseminate CVB1 virions to new host cells by a nonlytic EV-to-cell mechanism. This was confirmed by detecting CVB1 virions inside HeLa cells after co-culture with CVB1i-mEVs; EV release may also prevent apoptosis of infected cells whilst spreading apoptosis to secondary sites of infection.

Investigation of airborne spread of COVID-19 using a hybrid agent-based model: a case study of the UK.

Agent-based models have been proven to be quite useful in understanding and predicting the SARS-CoV-2 virus-originated COVID-19 infection. Person-to-person contact was considered as the main mechanism of viral transmission in these models. However, recent understanding has confirmed that airborne transmission is the main route to infection spread of COVID-19. We have developed a computationally efficient agent-based hybrid model to study the aerial propagation of the virus and subsequent spread of infection. We considered virus, a continuous variable, spreads diffusively in air and members of populations as discrete agents possessing one of the eight different states at a particular time. The transition from one state to another is probabilistic and age linked. Recognizing that population movement is a key aspect of infection spread, the model allows unbiased movement of agents. We benchmarked the model to recapture the temporal stochastic infection count data of the UK. The model investigates various key factors such as movement, infection susceptibility, new variants, recovery rate and duration, incubation period and vaccination on the infection propagation over time. Furthermore, the model was applied to capture the infection spread in Italy and France.

Analysis of the spread of SARS-CoV-2 in a hospital isolation room using CFD and Lagrangian Coherent Structures

This research paper presents an analysis of the propagation of the SARS-CoV-2, or other similar pathogens, in a hospital isolation room using computational fluid dynamics (CFD) and Lagrangian Coherent Structures (LCS). The study investigates the airflow dispersion and droplets in the room under air conditioning vent and sanitizer conditions. The CFD simulation results show that both the air conditioner and sanitizer systems significantly influence the dispersion of the virus in the room. The use of LCS enables acquiring a deep understanding of the dispersion of suspended particles, providing insights into the mechanisms of virus transmission. The findings of this study could help in developing strategies for improving the design and operation of isolation rooms to minimize the likelihood of virus dissemination within hospitals.

An Application of the DHI Methodology for a Comparison of SARS-CoV-2 Epidemic Hazards in Customer Delivery Services of Smart Cities

Current awareness of epidemic threats and critical experiences of the COVID-19 pandemic require extension of the management model in the smart city, especially in the field of mobility and transport services, with monitoring of epidemic hazards. This paper addresses the issue of epidemic hazards, a new challenge in smart cities, and customer delivery services. The novel DHI methodology for epidemic hazards assessment is presented and applied to compare customer delivery services in aspects of SARS-CoV-2 epidemic hazards. The case studies presented a detailed analysis of epidemic hazards on the basis of process algorithms and dedicated quantitative scales to assess factors influencing the mechanisms of virus transmission. The developed DHI methodology and the results obtained for transport services constitute important cognitive knowledge for the administrative personnel in smart city.

Neural-SEIR: A flexible data-driven framework for precise prediction of epidemic disease.

Accurately modeling and predicting epidemic diseases is crucial to prevent disease transmission and reduce mortality. Due to various unpredictable factors, including population migration, vaccination, control efforts, and seasonal fluctuations, traditional epidemic models that rely on prior knowledge of virus transmission mechanisms may not be sufficient to forecast complex epidemics like coronavirus disease 2019(COVID-19). The application of traditional epidemiological models such as susceptible-exposed-infectious-recovered (SEIR) may face difficulties in accurately predicting such complex epidemics. Data-driven prediction approaches lack the ability to generalize and exhibit low accuracy on small datasets due to their reliance on large amounts of data without incorporating prior knowledge. To overcome this limitation, we introduce a flexible ensemble data-driven framework (Neural-SEIR) that "neuralizes" the SEIR model by approximating the core parameters through neural networks while preserving the propagation structure of SEIR. Neural-SEIR employs long short-term memory (LSTM) neural network to capture complex correlation features, exponential smoothing (ES) to model seasonal information, and prior knowledge from SEIR. By incorporating SEIR parameters into the neural network structure, Neural-SEIR leverages prior knowledge while updating parameters with real-world data. Our experimental results demonstrate that Neural-SEIR outperforms traditional machine learning and epidemiological models, achieving high prediction accuracy and efficiency in forecasting epidemic diseases.

SOCIAL AND LEGAL SUPPORT OF WOMEN LIVING WITH HIV IN UKRAINE

The aim of the article is to analyze the social and legal support of women in Ukraine living with HIV, and to identify features that need to be taken into account when working with this category of people. To achieve this goal, the article uses research methods such as analysis, synthesis, monitoring, statistical processing of information, and analysis of literature, legal documents.Results: The article highlights the relevance of the problem of HIV / AIDS nowadays, as the final real statistics do not exist due to the fact that many carriers of the virus and patients are not tested. It is important to solve this problem to conduct informational and educational campaigns to promote voluntary testing, counseling on treatment, social support at the legislative level and prevention of infection.The article also considers the mechanisms of virus transmission (sexual, parenteral and vertical). The individual approach to the prevention, detection and treatment of HIV / AIDS is described, as well as the impact of urban processes on the spread of this problem and increase new cases of infection among men compared to women. Parenteral transmission of infection predominates among men, and sexual transmission predominates among women. Discrimination against women compared to men in terms of receiving the necessary assistance and realizing the full potential of HIV / AIDS is noted. This confirms the existence of social stereotypes that shape the overall picture of gender relations in Ukraine, although the level of legislation guarantees the availability and quality of all types of assistance to both men and women equally.The facts concerning HIV-infected women have been identified, namely: numerous discrimination and violations of the rights of women with HIV-positive status; receiving ARV therapy by women with HIV-positive status; access of women living with HIV to assisted reproductive technologies; social services for women with HIV-positive status. All of them must be reflected in Ukrainian legislation.A review of regulations and other documents on the rights and opportunities of HIV-positive women in Ukraine was conducted. National and international documents are analyzed and systematized. The information was summarized and grouped by different positions, which allowed to identify certain features that need to be taken into account when working with HIV-positive women, as well as to conclude that there is insufficient experience in implementing a gender-based approach in developing and approving Ukrainian legislation.

Monkeypox outbreak in a piercing and tattoo establishment in Spain

Monkeypox outbreak in a piercing and tattoo establishment in Spain

The Atmospheric Environment Effects of the COVID-19 Pandemic: A Metrological Study.

Since the COVID-19 outbreak, the scientific community has been trying to clarify various problems, such as the mechanism of virus transmission, environmental impact, and socio-economic impact. The spread of COVID-19 in the atmospheric environment is variable and uncertain, potentially resulting in differences in air pollution. Many scholars are striving to explore the relationship between air quality, meteorological indicators, and COVID-19 to understand the interaction between COVID-19 and the atmospheric environment. In this study, we try to summarize COVID-19 studies related to the atmospheric environment by reviewing publications since January 2020. We used metrological methods to analyze many publications in Web of Science Core Collection. To clarify the current situation, hotspots, and development trends in the field. According to the study, COVID-19 research based on the atmospheric environment has attracted global attention. COVID-19 and air quality, meteorological factors affecting the spread of COVID-19, air pollution, and human health are the main topics. Environmental variables have a certain impact on the spread of SARS-CoV-2, and the prevalence of COVID-19 has improved the atmospheric environment to some extent. The findings of this study will aid scholars to understand the current situation in this field and provide guidance for future research.

Analysis of airborne sputum droplets flow dynamic behaviors under different ambient conditions and aerosol size effects

The coronavirus (COVID-19) is becoming more threatening with the emergence of new mutations. New virus transmission and infection processes remain challenging and re-examinations of proper protection methods are urgently needed. From fluid dynamic viewpoint, the transmission of virus-carrying droplets and aerosols is one key to understanding the virus-transmission mechanisms. This study shows virus transmission by incorporating flow-evaporation model into the Navier-Stokes equation to describe the group of airborne sputum droplets exhaled under Rosin-Rammler distribution. Solid components and humidity field evolution are incorporated in describing droplet and ambient conditions. The numerical model is solved by an inhouse code using advection-diffusion equation for the temperature field and the humidity field, discretized by applying the total-variation diminishing Runge-Kutta method. The results of this study are presented in detail to show the different trends under various ambient conditions and to reveal the major viral-transmission routes as a function of droplet size.

Risk Assessment and Prevention Strategy of Virus Infection in the Context of University Resumption

The risk assessment system of virus infection probability and the prevention measures for virus transmission are keys to controlling epidemics. In the context of university resumption, this study identifies the risk elements in terms of the mechanism of virus transmission. The effect of two recognized effective measures, i.e., occupancy constraints and ventilation intervention, on the infection risk are quantified and compared using the improved Wells–Riley model. Considering the priority of these two measures, the controlling quantity are determined, and the optimal schemes are proposed based on the targeted infection risk. The results show that the effect of reducing infection risk by constraining occupancy within 25% of all public campus buildings is better than that achieved by increasing the ventilation rate alone. If the ventilation system of the building type is operated by occupiers, it is a priority to prevent the risk of virus infection by restricting occupancy and ensuring the distance between occupants, while if the ventilation system of the building type is centrally controlled, it is a priority to increase the ventilation rate and then limit the occupancy rate during peak periods to 75%.

Numerical Investigation on the Droplet Dispersion inside a Bus and the Infection Risk Prediction

COVID-19 can be easily transmitted to passengers by inhaling exhaled droplets from the infected person in a bus. Therefore, studying droplet dispersion would provide further insight into the mechanism of virus transmission and predict the risk of infection among passengers on a bus. In this research, a bus equipped with air-conditioning was employed as the research object. To determine the dispersion path, concentration distribution, and escape time of the droplets, computational fluid dynamic (CFD) was applied to simulate the flow field and the droplets’ dispersion. The effect of the air supply rate, the location of vents, and the location of infected persons on the dispersion were discussed. Based on the distribution of droplets in the cabin calculated by CFD, a superposition method was used to determine the number of virus particles inhaled by every individual passenger over a four-hour journey. Then, infection risk was assessed by the Wells-Riley equation for all the passengers in the cabin after the whole journey. The results show that the distribution of droplets in the cabin is greatly influenced by the location of the infected person, and the airflow pattern is highly associated with the air supply rate and the location of vents. The infection risk of passengers located at the droplet dispersion path and the distance from the infected persons less than 2.2 m is over 10%. The increase in the air supply rate could speed up the spread of the droplets but at the same time, it could reduce the infection risk.