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The COVID-19 pandemic has had profound impact, necessitating a deeper understanding of factors influencing virus transmission. The negative impacts have weakened the economy and changed billions of lives around the world. COVID-19 is a new virus, and a lot of studies have tried to investigate its effect on, for example, the economy or environment. This research reveals new approaches to recognizing and stopping the spread of this virus with its connection to weather conditions and relevant parameters. By analyzing how temperature and humidity affect COVID-19 spread, alongside evaluating the effectiveness of initial public policies, this study addresses the critical gap in research by investigating the interplay between climate conditions and government regulations during the early stages of the pandemic in South Korea. This dual approach provides a comprehensive framework for understanding how environmental and policy factors jointly influence pandemic dynamics, offering valuable lessons for future global health crises. Although it focuses only on the first phase of South Korea COVID-19 regulations, outcomes show that these regulations were notably effective against the COVID-19 pandemic. The outcomes prove that higher temperature and higher relative humidity lead to lower transmission. Hence, based on the results during winter, the number of infections would be expected to speed up again. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had profound impact, necessitating a deeper understanding of factors influencing virus transmission. The negative impacts have weakened the economy and changed billions of lives around the world. COVID-19 is a new virus, and a lot of studies have tried to investigate its effect on, for example, the economy or environment. This research reveals new approaches to recognizing and stopping the spread of this virus with its connection to weather conditions and relevant parameters. By analyzing how temperature and humidity affect COVID-19 spread, alongside evaluating the effectiveness of initial public policies, this study addresses the critical gap in research by investigating the interplay between climate conditions and government regulations during the early stages of the pandemic in South Korea. This dual approach provides a comprehensive framework for understanding how environmental and policy factors jointly influence pandemic dynamics, offering valuable lessons for future global health crises. Although it focuses only on the first phase of South Korea COVID-19 regulations, outcomes show that these regulations were notably effective against the COVID-19 pandemic. The outcomes prove that higher temperature and higher relative humidity lead to lower transmission. Hence, based on the results during winter, the number of infections would be expected to speed up again.

Currently, the analyses of and prediction using COVID-19-related data extracted from patient information repositories compiled by hospitals and health organizations are of paramount importance. These efforts significantly contribute to vaccine development and the formulation of contingency techniques, providing essential tools to prevent resurgence and to effectively manage the spread of the disease. In this context, the present research focuses on analyzing the biological information of the SARS-CoV-2 viral gene sequences and the clinical data of COVID-19-affected patients using publicly accessible data from Ecuador. This involves considering variables such as age, gender, and geographical location to understand the evolution of mutations and their distributions across Ecuadorian provinces. The Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology is applied for data analysis. Various data preprocessing and statistical analysis techniques are employed, including Pearson correlation, the chi-square test, and analysis of variance (ANOVA). Statistical diagrams and charts are used to facilitate a better visualization of the results. The results illuminate the genetic diversity of the virus and its correlation with clinical variables, offering a comprehensive understanding of the dynamics of COVID-19 spread in Ecuador. Critical variables influencing population vulnerability are highlighted, and the findings underscore the significance of mutation monitoring and indicate a need for global expansion of the research area. [ABSTRACT FROM AUTHOR]

Despite the undeniable effect of vaccination against COVID-19 in reducing disease severity, there is still a need to monitor and limit SARS-CoV-2 circulation and transmission. Thus, this study evaluated the presence of the SARS-CoV-2 genome on the surfaces of highly touched objects manipulated in the biological sample collection point and at the reception unit of the diagnostic laboratory. Surfaces were sampled once a week, for 6 weeks, between September 18th and October 23rd, 2020. RT-qPCR was used for SARS-CoV-2 detection. The coolers for biological sample transportation and the envelope containing the patient form were the objects with the highest occurrence of viral genome detection, although it was detected in each object in only two of the 6 evaluations. And the SARS-CoV-2 genome was detected just once on the vehicle steering wheel, computer keyboard, bathroom door handle and disinfection bench. The virus genome was not detected in any object on three of the six evaluations. And eight was the largest number of surfaces contaminated by the virus genome on one occasion. The reduced incidence of object contamination by the SARS-CoV-2 genome can be explained by the exposure of the objects to environmental conditions and the adoption of virus-spread containment measures. It can also reflect the low incidence of SARS-CoV-2 during the study's development period. Despite the low frequency of SARS-CoV-2 genome detection, our findings show that the virus was present in the environment at some point. This highlights the importance of adopting personal preventive measures to reduce respiratory virus spread, especially during epidemics and outbreaks. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a profound impact on various aspects of our lives, affecting personal, occupational, economic, and social spheres. Much has been learned since the early 2020s, which will be very useful when the next pandemic emerges. In general, mobility and virus spread are strongly related. However, most studies analyze the impact of COVID-19 on mobility, but not much research has focused on analyzing the impact of mobility on virus transmission, especially from the point of view of monitoring virus incidence, which is extremely important for making sound decisions to control any epidemiological threat to public health. As a result of a thorough analysis of COVID-19 and mobility data, this work introduces a novel measure, the Infection Ratio (IR), which is not sensitive to underestimation of positive cases and is very effective in monitoring the pandemic's upward or downward evolution when it appears to be more stable, thus anticipating possible risk situations. For a bounded spatial context, we can infer that there is a significant threshold in the restriction of mobility that determines a change of trend in the number of infections that, if maintained for a minimum period, would notably increase the chances of keeping the spread of disease under control. Results show that IR is a reliable indicator of the intensity of infection, and an effective measure for early monitoring and decision making in smart cities. [ABSTRACT FROM AUTHOR]

Tunneling nanotubes (TNTs) are actin-rich intercellular conduits that mediate distant cell-to-cell communication and enable the transfer of various cargos, including proteins, organelles, and virions. They play vital roles in both physiological and pathological processes. In this review, we focus on TNTs in different types of viruses, including retroviruses such as HIV, HTLV, influenza A, herpesvirus, paramyxovirus, alphavirus and SARS-CoV-2. We summarize the viral proteins responsible for inducing TNT formation and explore how these virusinduced TNTs facilitate intercellular communication, thereby promoting viral spread. Furthermore, we highlight other virus infections that can induce TNTlike structures, facilitating the dissemination of viruses. Moreover, TNTs promote intercellular spread of certain viruses even in the presence of neutralizing antibodies and antiviral drugs, posing significant challenges in combating viral infections. Understanding the mechanisms underlying viral spread via TNTs provides valuable insights into potential drug targets and contributes to the development of effective therapies for viral infections. [ABSTRACT FROM AUTHOR]

Background: This paper aims to present open-source computer simulation programs developed to simulate, track, and estimate the COVID-19 outbreak. Methods: The programs included two separate parts, one set of programs built in Simulink with a block diagram display, and another one coded as a script in MATLAB R2020b. The mathematical model used in this package was the suspectable-infected-removed (SIR), suspectable-exposed-infected-removed (SEIR), and susceptible-exposed-infected-recovereddeceased (SEIRD) models represented by a set of differential-algebraic equations. It can be easily modified to develop new models for the problem. A generalized method was adopted to simulate worldwide outbreaks in an efficient, fast, and simple way. Results: To get a good tracking of the virus spread, a sum of sigmoid functions was proposed to capture any dynamic changes in the data. The parameters used for the input (infection and recovery rate functions) were computed using the parameter estimation tool in MATLAB. Several statistical methods were applied for the rate function, including linear, Mean±SD and root mean square (RMS). In addition, an adaptive neuro-fuzzy inference system (ANFIS) was employed and proposed to train the model and predict its output. Conclusion: This procedure is presented in such a way that it can be generalized and applied in other parts and applications of estimating the scenarios of an event, including the potential of several models, including suspectable-infected-removed (SIR), which is sensitive to pollution, etc. This program can be used as an educational tool or for research studies and this article promises some lasting contributions in the field of COVID-19. [ABSTRACT FROM AUTHOR]

Chronic hepatitis B is a global public health problem, and coinfection with hepatitis delta virus (HDV) worsens disease outcome. Here, we describe a hepatitis B virus (HBV) surface antigen (HBsAg)-targeting monoclonal antibody (mAb) with the potential to treat chronic hepatitis B and chronic hepatitis D. HBsAg-specific mAbs were isolated from memory B cells of HBV vaccinated individuals. In vitro neutralization was determined against HBV and HDV enveloped with HBsAg representing eight HBV genotypes. Human liver-chimeric mice were treated twice weekly with a candidate mAb starting 3 weeks post HBV inoculation (spreading phase) or during stable HBV or HBV/HDV coinfection (chronic phase). From a panel of human anti-HBs mAbs, VIR-3434 was selected and engineered for pre-clinical development. VIR-3434 targets a conserved, conformational epitope within the antigenic loop of HBsAg and neutralized HBV and HDV infection with higher potency than hepatitis B immunoglobulins in vitro. Neutralization was pan-genotypic against strains representative of HBV genotypes A-H. In the spreading phase of HBV infection in human liver-chimeric mice, a parental mAb of VIR-3434 (HBC34) prevented HBV dissemination and the increase in intrahepatic HBV RNA and covalently closed circular DNA. In the chronic phase of HBV infection or co-infection with HDV, HBC34 treatment decreased circulating HBsAg by >1 log and HDV RNA by >2 logs. The potently neutralizing anti-HBs mAb VIR-3434 reduces circulating HBsAg and HBV/HDV viremia in human liver-chimeric mice. VIR-3434 is currently in clinical development for treatment of patients with chronic hepatitis B or D. Chronic infection with hepatitis B virus and co-infection with hepatitis D virus place approximately 290 million individuals worldwide at risk of severe liver disease and cancer. Available treatments result in low rates of functional cure or require lifelong therapy that does not eliminate the risk of liver disease. We isolated and characterized a potent human antibody that neutralizes hepatitis B and D viruses and reduces infection in a mouse model. This antibody could provide a new treatment for patients with chronic hepatitis B and D. [Display omitted] • Identification of a human mAb VIR-3434 that potently neutralizes HBV and HDV. • VIR-3434 targets a conserved, conformational epitope of the HBsAg antigenic loop. • VIR-3434 treatment blocks intrahepatic HBV spread in human liver-chimeric mice. • VIR-3434 treatment reduces circulating HBsAg and HDV RNA in co-infected mice. • Data have enabled clinical development of VIR-3434 against chronic hepatitis B/D. [ABSTRACT FROM AUTHOR]

Currently, the analyses of and prediction using COVID-19-related data extracted from patient information repositories compiled by hospitals and health organizations are of paramount importance. These efforts significantly contribute to vaccine development and the formulation of contingency techniques, providing essential tools to prevent resurgence and to effectively manage the spread of the disease. In this context, the present research focuses on analyzing the biological information of the SARS-CoV-2 viral gene sequences and the clinical data of COVID-19-affected patients using publicly accessible data from Ecuador. This involves considering variables such as age, gender, and geographical location to understand the evolution of mutations and their distributions across Ecuadorian provinces. The Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology is applied for data analysis. Various data preprocessing and statistical analysis techniques are employed, including Pearson correlation, the chi-square test, and analysis of variance (ANOVA). Statistical diagrams and charts are used to facilitate a better visualization of the results. The results illuminate the genetic diversity of the virus and its correlation with clinical variables, offering a comprehensive understanding of the dynamics of COVID-19 spread in Ecuador. Critical variables influencing population vulnerability are highlighted, and the findings underscore the significance of mutation monitoring and indicate a need for global expansion of the research area.

A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R0) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) over time (m) are deduced and shown to be in good agreement with experimental data. This model effectively addresses three key issues: (1) inferring the conditions under which virus infections die out for a specific strain given R0; (2) explaining the occurrence of second waves of infection and developing preventive measures; and (3) understanding the competitive spread of two viruses within a region and devising control strategies. The findings highlight the potential of this simple mathematical framework in comprehensively addressing these challenges. The theoretical insights derived from this model can guide the evaluation of infection wave severity and the formulation of effective strategies for controlling and mitigating epidemic outbreaks. [ABSTRACT FROM AUTHOR]

This paper presents a spatial analysis of the incidence rate of COVID-19 cases in the state of Paraná, Brazil, from June to December 2020, and a study of the incidence rate of COVID-19 cases associated with socioeconomic variables, such as the Gini index, Theil-L index, and municipal human development index (MHDI). The data were provided from the Paraná State Health Department and Paraná Institute for Economic and Social Development. For the study of spatial autocorrelation, the univariate global Moran index (I), local univariate Moran (LISA), global Geary (c), and univariate local Geary (ci) were calculated. For the analysis of the spatial correlation, the global bivariate Moran index (Ixy), the local multivariate Geary indices (CiM), and the bivariate Lee index (Lxy) were calculated. There is significant positive spatial autocorrelation between the incidence rate of COVID-19 cases and correlations between the incidence rate of COVID-19 cases and the Gini index, Theil-L index, and MHDI in the regions under study. The highest risk areas were concentrated in the macro-regions: east and west. Understanding the spatial distribution of COVID-19, combined with economic and social factors, can contribute to greater efficiency in preventive actions and the control of new viral epidemics.

IgA nephropathy (IgAN) is an autoimmune disease in which poorly galactosylated IgA1 is the antigen recognized by naturally occurring anti-glycan antibodies, leading to formation of nephritogenic circulating immune complexes. Incidence of IgAN displays geographical and racial disparity: common in Europe, North America, Australia, and east Asia, uncommon in African Americans, many Asian and South American countries, Australian Aborigines, and rare in central Africa. In analyses of sera and cells from White IgAN patients, healthy controls, and African Americans, IgAN patients exhibited substantial enrichment for IgA-expressing B cells infected with Epstein-Barr virus (EBV), leading to enhanced production of poorly galactosylated IgA1. Disparities in incidence of IgAN may reflect a previously disregarded difference in the maturation of the IgA system as related to the timing of EBV infection. Compared with populations with higher incidences of IgAN, African Americans, African Blacks, and Australian Aborigines are more frequently infected with EBV during the first 1-2 years of life at the time of naturally occurring IgA deficiency when IgA cells are less numerous than in late childhood or adolescence. Therefore, in very young children EBV enters "non-IgA" cells. Ensuing immune responses prevent infection of IgA B cells during later exposure to EBV at older ages. Our data implicate EBV-infected cells as the source of poorly galactosylated IgA1 in circulating immune complexes and glomerular deposits in patients with IgAN. Thus, temporal differences in EBV primo-infection as related to naturally delayed maturation of the IgA system may contribute to geographic and racial variations in incidence of IgAN. [ABSTRACT FROM AUTHOR]

The global crisis produced by SARS-CoV-2 affected health, economics, social activities, and the environment. In the SARS-CoV-2 outbreak worldwide, air pollutants could significantly contribute to the spread of the virus. The paper studies the relationship between air pollutants (PM2.5, PM10) concentrations and AQI variation and SARS-CoV-2 outbreak (average of cases per million inhabitants) in the case of Romania's counties. The methodology of the study is based on public open-source data concerning the emissions of air pollutants registered in the cities of Romania and the average of COVID-19 cases per million inhabitants. The findings of the study demonstrate that the highest numbers of COVID-19 cases were reported in the most polluted regions. A significant correlation between the levels of air pollution and the numbers of virus cases can be observed in most Romanian counties. The most affected counties by COVID-19 are also some of the most polluted counties in Romania. The study certifies the need for sustainable environmental policies that should be adopted fast in order to diminish the pollution's consequences on people's health. The findings show that new environmental, health and social strategies are needed. These refer to designing smart cities, with lower levels of air pollution; the development of new medical technologies and treatments; increasing social support and formulating coherent institutional policies for managing similar health crises. [ABSTRACT FROM AUTHOR]

In this paper, we explore two modeling approaches to understanding the dynamics of infectious diseases in the population: equation-based modeling (EBM) and agent-based modeling (ABM). To achieve this, a comparative study of these approaches was conducted and we highlighted their advantages and disadvantages. Two case studies on the spread of the COVID-19 pandemic were carried out using both approaches. The results obtained show that differential equation-based models are faster but still simplistic, while agent-based models require more machine capabilities but are more realistic and very close to biology. Based on these outputs, it seems that the coupling of both approaches could be an interesting compromise. [ABSTRACT FROM AUTHOR]

IgA nephropathy (IgAN) is an autoimmune disease in which poorly galactosylated IgA1 is the antigen recognized by naturally occurring anti-glycan antibodies, leading to formation of nephritogenic circulating immune complexes. Incidence of IgAN displays geographical and racial disparity: common in Europe, North America, Australia, and east Asia, uncommon in African Americans, many Asian and South American countries, Australian Aborigines, and rare in central Africa. In analyses of sera and cells from White IgAN patients, healthy controls, and African Americans, IgAN patients exhibited substantial enrichment for IgA-expressing B cells infected with Epstein-Barr virus (EBV), leading to enhanced production of poorly galactosylated IgA1. Disparities in incidence of IgAN may reflect a previously disregarded difference in the maturation of the IgA system as related to the timing of EBV infection. Compared with populations with higher incidences of IgAN, African Americans, African Blacks, and Australian Aborigines are more frequently infected with EBV during the first 1-2 years of life at the time of naturally occurring IgA deficiency when IgA cells are less numerous than in late childhood or adolescence. Therefore, in very young children EBV enters “non-IgA” cells. Ensuing immune responses prevent infection of IgA B cells during later exposure to EBV at older ages. Our data implicate EBV-infected cells as the source of poorly galactosylated IgA1 in circulating immune complexes and glomerular deposits in patients with IgAN. Thus, temporal differences in EBV primo-infection as related to naturally delayed maturation of the IgA system may contribute to geographic and racial variations in incidence of IgAN.

This paper presents a spatial analysis of the incidence rate of COVID-19 cases in the state of Paraná, Brazil, from June to December 2020, and a study of the incidence rate of COVID-19 cases associated with socioeconomic variables, such as the Gini index, Theil-L index, and municipal human development index (MHDI). The data were provided from the Paraná State Health Department and Paraná Institute for Economic and Social Development. For the study of spatial autocorrelation, the univariate global Moran index (I), local univariate Moran (LISA), global Geary (c), and univariate local Geary ( c i ) were calculated. For the analysis of the spatial correlation, the global bivariate Moran index (I x y) , the local multivariate Geary indices (C i M) , and the bivariate Lee index (L x y) were calculated. There is significant positive spatial autocorrelation between the incidence rate of COVID-19 cases and correlations between the incidence rate of COVID-19 cases and the Gini index, Theil-L index, and MHDI in the regions under study. The highest risk areas were concentrated in the macro-regions: east and west. Understanding the spatial distribution of COVID-19, combined with economic and social factors, can contribute to greater efficiency in preventive actions and the control of new viral epidemics. [ABSTRACT FROM AUTHOR]

A mathematical model is proposed to analyze the spreading dynamics of COVID-19. By using the parameters of the model, namely the basic reproduction number (R0) and the attenuation constant (k), the daily number of infections (DNI) and the cumulative number of infections (CNI) over time (m) are deduced and shown to be in good agreement with experimental data. This model effectively addresses three key issues: (1) inferring the conditions under which virus infections die out for a specific strain given R0; (2) explaining the occurrence of second waves of infection and developing preventive measures; and (3) understanding the competitive spread of two viruses within a region and devising control strategies. The findings highlight the potential of this simple mathematical framework in comprehensively addressing these challenges. The theoretical insights derived from this model can guide the evaluation of infection wave severity and the formulation of effective strategies for controlling and mitigating epidemic outbreaks.

Cytomegaloviruses (CMVs) are controlled by innate and adaptive immune responses in an immunocompetent host while causing multiple organ diseases in an immunocompromised host. A risk group of high clinical relevance comprises transiently immunocompromised recipients of hematopoietic cell transplantation (HCT) in the "window of risk" between eradicative therapy of hematopoietic malignancies and complete reconstitution of the immune system. Cellular immunotherapy by adoptive transfer of CMV-specific CD8 T cells is an option to prevent CMV disease by controlling a primary or reactivated infection. While experimental models have revealed a viral epitope-specific antiviral function of cognate CD8 T cells, the site at which control is exerted remained unidentified. The observation that remarkably few transferred cells protect all organs may indicate an early blockade of virus dissemination from a primary site of productive infection to various target organs. Alternatively, it could indicate clonal expansion of a few transferred CD8 T cells for preventing intra-tissue virus spread after successful initial organ colonization. Our data in the mouse model of murine CMV infection provide evidence in support of the second hypothesis. We show that transferred cells vigorously proliferate to prevent virus spread, and thus viral histopathology, by confining and eventually resolving tissue infection within nodular inflammatory foci. [ABSTRACT FROM AUTHOR]

The wide spread of the novel COVID-19 virus all over the world has caused major economical and social damages combined with the death of more than two million people so far around the globe. Therefore, the design of a model that can predict the persons that are most likely to be infected is a necessity to control the spread of this infectious disease as well as any other future novel pandemic. In this paper, an Internet of Things (IoT) sensing network is designed to anonymously track the movement of individuals in crowded zones through collecting the beacons of WiFi and Bluetooth devices from mobile phones to triangulate and estimate the locations of individuals inside buildings without violating their privacy. A mathematical model is presented to compute the expected time of exposure between users. Furthermore, a virus spread mathematical model as well as iterative spread tracking algorithms are proposed to predict the probability of individuals being infected even with limited data.

Summary: Stem pitting is a common virus‐induced disease phenotype that tremendously impacts growth of perennial woody plants. How stem pitting develops in the infected trees remains unclear.Here, we assessed the development of stem pits upon infection of citrus by Citrus tristeza virus (CTV), which has been regarded as 'phloem‐limited'. By taking advantage of a highly susceptible virus host – Citrus macrophylla – and a CTV isolate lacking a viral effector – the p33 protein, the development pattern of stem pitting was revealed via time‐course observations and histological analyses.The stem pits result from the virus‐colonized nonlignified 'gumming' malformations which are initiated by virus invasion into multiple spatially separated tissue layers – protophloem, metaphloem, and, unexpectedly, metaxylem. Notably, invasion of CTV into the unspecialized metaxylem cells interrupted the differentiation of the xylem tracheary elements. With the radial spread of CTV into the adjacent cells towards the stem periphery, the clusters of virus‐colonized immature metaxylem cells extended in size, merging, at a certain stage, with virus‐bearing cells in the protophloem and metaphloem layers.Collectively, our data provide a new insight into the process of the stem pitting development and the role of the xylem tissue in the virus pathogenicity. [ABSTRACT FROM AUTHOR]

Potato virus Y (PVY) is a non-persistent virus that is transmitted by many aphid species and causes significant damage to potato production. We constructed a spatially-explicit model simulating PVY spread in a potato field and used it to investigate possible effects of transmission efficiency, initial inoculum levels, vector behavior, vector abundance, and timing of peak vector activity on PVY incidence at the end of a simulated growing season. Lower PVY incidence in planted seed resulted in lower virus infection at the end of the season. However, when populations of efficient PVY vectors were high, significant PVY spread occurred even when initial virus inoculum was low. Non-colonizing aphids were more important for PVY spread compared to colonizing aphids, particularly at high densities. An early-season peak in the numbers of noncolonizing aphids resulted in the highest number of infected plants in the end of the season, while mid- and late-season peaks caused relatively little virus spread. Our results highlight the importance of integrating different techniques to prevent the number of PVY-infected plants from exceeding economically acceptable levels instead of trying to control aphids within potato fields. Such management plans should be implemented very early in a growing season.

Mathematical and epidemiological simulation plays a pivotal role in predicting, anticipating, and controlling present and future epidemics. To better understand and model the dynamics of a specific infection, researchers need to consider the influence of many variables ranging from micro-host–pathogen interactions to host-to-host encounters, and the prevailing cultural, social, economic, and local customs worldwide. As reported by the WHO, a novel corona virus (COVID-19) is identified as the etiological virus through Wuhan pneumonia for unknown etiology with Chinese administration on Jan 7, 2020. This virus is designated as an unsympathetic SARS-Cov-2 by International Commission for Taxonomy of Viruses on Feb 11, 2020. The main aim is to enlarge a phase based mathematical modelling to specify the transferability of this disease. It is developed Reservoir-individuals spreading set of connections modelling for imitating the prospective broadcast as of the infectivity foundation in the direction of the person infectivity. In view of the fact that, the Reservoir has set of connections to rigid to see the sights obviously as well as communal anxieties are concentrating on top of the spreading starting reservoir to individuals. The subsequent generation matrix methodology is endorsed towards compute the fundamental reproduction number (R0) through the RP modelling to measure the transferability by the COVID-19. The values of R0 are estimated from reservoir to human being as well as starting individual to individual, that is to say, the accepted quantity of less important diseases this consequence from presenting a solitary contaminated personality addicted to differently susceptible inhabitants. The present model demonstrated that the spreading of COVID-19 is superior to the Middle-East pulmonary infirmity during the Middle-East nationals, analogous to harsh sensitive pulmonary infirmity, but inferior than Middle-East pulmonary infirmity within the Republic of Korea. It can also extend this study to some other countries, including Saudi Arabia, Italy, and Germany etc. The COVID-19 pandemic has become the leading societal concern. The pandemic has shown that the public health concern is not only a medical problem, but also affects society as a whole; so, it has also become the leading scientific concern.

In this paper, we explore two modeling approaches to understanding the dynamics of infectious diseases in the population: equation-based modeling (EBM) and agent-based modeling (ABM). To achieve this, a comparative study of these approaches was conducted and we highlighted their advantages and disadvantages. Two case studies on the spread of the COVID-19 pandemic were carried out using both approaches. The results obtained show that differential equation-based models are faster but still simplistic, while agent-based models require more machine capabilities but are more realistic and very close to biology. Based on these outputs, it seems that the coupling of both approaches could be an interesting compromise.

The SARS‐CoV‐2 pandemic has created a great demand for a better understanding of the spread of viruses in indoor environments. A novel measurement system consisting of one portable aerosol‐emitting mannequin (emitter) and a number of portable aerosol‐absorbing mannequins (recipients) was developed that can measure the spread of aerosols and droplets that potentially contain infectious viruses. The emission of the virus from a human is simulated by using tracer particles solved in water. The recipients inhale the aerosols and droplets and quantify the level of solved tracer particles in their artificial lungs simultaneously over time. The mobile system can be arranged in a large variety of spreading scenarios in indoor environments and allows for quantification of the infection probability due to airborne virus spreading. This study shows the accuracy of the new measurement system and its ability to compare aerosol reduction measures such as regular ventilation or the use of a room air purifier. [ABSTRACT FROM AUTHOR]

During the pandemic outbreak of COVID-19, the important role of plastic becomes evident since vital equipment such as respirators have plastic parts, as well as personal protective equipment (PPE), which avoids the transmission of the SARS-CoV-2 virus, is made of plastic. So, plastic during a pandemic is considered a life savior in the struggle against the virus. However, the same material that is a protector becomes a polluter when inadequately disposed of in the environment, generating or worsening socio-environmental problems, such as pollution of water bodies by plastic. This work proposes a reflection about the role and the importance of plastic in our society, bringing an overview of its main applications and consequences during the COVID-19 pandemic, correlating its use with aspects related to environmental problems and public health. Some questions revolving around the concerns caused by plastic pollution are posed, and some possible solutions to the problems are outlined. [ABSTRACT FROM AUTHOR]

Through virus-based reconnaissances, the attacker may compromise critical power substations and induce power outages. Meanwhile, the power system operator may conduct defensive measures to prevent virus-spreading. In this paper, a graphical evolutionary game model is developed to solve the equilibrium of competitions between virus propagations and countermeasures, which helps to evaluate the cyber-security risk of power systems under long-term virus-based intrusions. In the proposed game model, the virus is supposed to propagate itself in a cyber network connecting cyber nodes belonging to power substations. Each cyber node may play as an attacker or a defender according to its state. A death-birth rule is adopted to model probabilistic strategies and state transfers, which reflects the bounded rationality of the viruses. Then, an evolution dynamic equation is derived to obtain the portion of the infected substations when the equilibrium is reached, and simulation algorithm is also given to estimate the infection probability of each substation under the persistent virus-based intrusion. Assuming a virus may trip all breakers in the infected substation, the cyber-security risk is evaluated to identify system-level vulnerabilities. The IEEE 118-bus system with a layered cyber network is used for case studies. Test results validate the proposed model and provide further insights into the virus-based intrusion.

This article presents the COVID-19 situation and control measures taken by the Government of Pakistan. Two waves of pandemic are faced globally and similar in the study area. We have investigated the risk management decision in two phases. Primarily, strict lockdown was observed from March 2020 to July 2020 and smart lockdown was enforced from August 2020 to December 2020. It has been studied that during strict lockdown, COVID cases reduced gradually but reopening of institutes and smart lockdown strategy resulted gradual increase in confirmed cases and death rates. During first wave of COVID-19 in Pakistan, a total confirmed number of patients of COVID-19 were 263,496 till 18th of July 2020 with total deaths of 5,568 people and 204,276 recoveries, while total number of COVID-19 patients reached 555,511 till 9th of February 2021 with total deaths of 12,026 people. Province of Sindh was affected badly with total number of 251,434 COVID-19 cases followed by Punjab Province with total number of 161,347 COVID-19 till 9th of February 2020. [ABSTRACT FROM AUTHOR]

Knowledge on the mechanisms of viral spread, of time‐related changes, and age‐specific factors of severe acute respiratory syndrome coronavirus 2 infections is important to develop recommendations aimed at controlling the pandemic. In this context, longitudinal data on proportions of positive results in different age groups are rare. Data on total positive counts and on shares of positive counts deriving from a private (MVZ) and a University (RWTH) laboratory were analyzed retrospectively and compared with public data on total positive counts of the Robert Koch Institute (RKI). Data were covered for Weeks 9–24 of the year 2020 and all patient ages. Total positive counts were lower in children compared to adults. Proportions of children and adults tested positive were 3%–5% and 5%–7%, respectively. RKI and MVZ data showed similar time‐related patterns. Patients of 20–60 years of age did account for the initial virus spread (maximum infection rates at Weeks 9–11). Thereafter, infection rates decreased in older patients whereas children did not show a comparable time‐related decrease. Pediatric data generated in outpatient settings and hospitals differed markedly which should be considered in further studies. In summary, compared with adults children are less affected by severe acute respiratory syndrome coronavirus 2 infections and are unlikely to account for the initial viral spread. However, children show sustained viral activity and may serve as a viral reservoir. Highlights: Adolescents and adults seem to account for initial spreading of SARS‐CoV‐2.SARS‐CoV‐2 positivity rates are lower in children compared to adults.Children may show a retarded decline of SARS‐CoV‐2 positivity rates.Reservoir exploration studies of SARS‐CoV‐2 should investigate if children serve as a viral reservoir. [ABSTRACT FROM AUTHOR]

The ascomycete Cryphonectria parasitica causes destructive chestnut blight. Biological control of the fungus by virus infection (hypovirulence) has been shown to be an effective control strategy against chestnut blight in Europe. To provide biocontrol effects, viruses must be able to induce hypovirulence and spread efficiently in chestnut trees. Field studies using living trees to date have focused on a selected family of viruses called hypoviruses, especially prototypic hypovirus CHV1, but there are now known to be many other viruses that infect C. parasitica. Here, we tested seven different viruses for their hypovirulence induction, biocontrol potential, and transmission properties between two vegetatively compatible but molecularly distinguishable fungal strains in trees. The test included cytosolically and mitochondrially replicating viruses with positive-sense single-stranded RNA or double-stranded RNA genomes. The seven viruses showed different in planta behaviors and were classified into four groups. Group I, including CHV1, had great biocontrol potential and could protect trees by efficiently spreading and converting virulent to hypovirulent cankers in the trees. Group II could induce high levels of hypovirulence but showed much smaller biocontrol potential, likely because of inefficient virus transmission. Group III showed poor performance in hypovirulence induction and biocontrol, while efficiently being transmitted in the infected trees. Group IV could induce hypovirulence and spread efficiently but showed poor biocontrol potential. Nuclear and mitochondrial genotyping of fungal isolates obtained from the treated cankers confirmed virus transmission between the two fungal strains in most isolates. These results are discussed in view of dynamic interactions in the tripartite pathosystem. [ABSTRACT FROM AUTHOR]

Background: In the context of the current coronavirus pandemic, we propose an inexpensive, innovative overhead transparent plastic barrier with powered suction (OTPBPS) technique using materials that are ubiquitous in the hospital, easy to set up in minutes and well tolerated by the patients. As presented in this case report, it is an effective method to reduce viral spread from patients with positive or suspected yet unconfirmed coronavirus disease 2019 status. Case Description: A 49-year-old male was admitted to the hospital with a diagnosis of cervical stenosis and a C6-C7 disc herniation with spinal cord compression. The OTPBPS technique was set up to create a negative pressure environment around the patient's head, using a Mayo stand, a transparent plastic bag, and powered wall canister suction. The neurosurgeon successfully performed an anterior cervical discectomy and instrumented fusion under OTPBPS. The patient was satisfied with the intubation and anesthetic management and reported excellent feedback. Conclusion: The OTPBPS technique helps control the spread of an aerosolized viral load from the patient's mouth or airway during awake fiber-optic intubation. This technique will help anesthesiologists and other frontline health-care providers manage copious endotracheal secretions and droplet particles, which have an immense infectious potential. [ABSTRACT FROM AUTHOR]

Since the beginning of the first cases of the new coronavirus, opinions and laws on the use of plastic materials have been questioned around the world. Their importance in the manufacture of hospital devices and personal protective equipment (PPE) is unquestionable, as they contribute largely to the reduction of the virus spread, helping health systems from all edges of the world and, most importantly, saving lives. However, the same material that is a protector, becomes a polluter when inadequately disposed of in the environment, generating or worsening socio-environmental problems, such as pollution of water bodies by plastic. A critical overview of the role of plastic during the COVID-19 pandemic is provided in this paper. A future panorama is attempted to be outlined. The real possibility of the virus spread from the use of plastic is discussed, as well as the recycling of plastic during the pandemic, correlating its use with problems that it may cause. [ABSTRACT FROM AUTHOR]

Aim/hypothesis: Human enteroviral infections are suggested to be associated with type 1 diabetes. However, the mechanism by which enteroviruses can trigger disease remains unknown. The present study aims to investigate the impact of enterovirus on autophagy, a cellular process that regulates beta cell homeostasis, using the clonal beta cell line INS(832/13) and human islet cells as in vitro models. Methods: INS(832/13) cells and human islet cells were infected with a strain of echovirus 16 (E16), originally isolated from the stool of a child who developed type 1 diabetes-associated autoantibodies. Virus production and release was determined by 50% cell culture infectious dose (CCID50) assay and FACS analysis. The occurrence of autophagy, autophagosomes, lysosomes and autolysosomes was detected by western blot, baculoviral-mediated expression of microtubule-associated protein light chain 3 (LC3)II-GFP and LysoTracker Red, and quantified by Cellomics ArrayScan. Autophagy was also monitored with a Cyto-ID detection kit. Nutrient deprivation (low glucose [2.8 mmol/l]), amino acid starvation (Earle's Balanced Salt Solution [EBSS]) and autophagy-modifying agents (rapamycin and chloroquine) were used in control experiments. Insulin secretion and the expression of autophagy-related (Atg) genes and genes involved in autophagosome–lysosome fusion were determined. Results: E16-infected INS(832/13) cells displayed an accumulation of autophagosomes, compared with non-treated (NT) cells (grown in complete RPMI1640 containing 11.1 mmol/l glucose) (32.1 ± 1.7 vs 21.0 ± 1.2 μm2/cell; p = 0.05). This was accompanied by increased LC3II ratio both in E16-infected cells grown in low glucose (LG) (2.8 mmol/l) (0.42 ± 0.03 vs 0.11 ± 0.04 (arbitrary units [a.u.]); p < 0.0001) and grown in media containing 11.1 mmol/l glucose (0.37 ± 0.016 vs 0.05 ± 0.02 (a.u.); p < 0.0001). Additionally, p62 accumulated in cells after E16 infection when grown in LG (1.23 ± 0.31 vs 0.36 ± 0.12 (a.u.); p = 0.012) and grown in media containing 11.1 mmol/l glucose (1.79 ± 0.39 vs 0.66 ± 0.15 (a.u.); p = 0.0078). mRNA levels of genes involved in autophagosome formation and autophagosome–lysosome fusion remained unchanged in E16-infected cells, except Atg7, which was significantly increased when autophagy was induced by E16 infection, in combination with LG (1.48 ± 0.08-fold; p = 0.02) and at 11.1 mmol/l glucose (1.26 ± 0.2-fold; p = 0.001), compared with NT controls. Moreover, autophagosomes accumulated in E16-infected cells to the same extent as when cells were treated with the lysosomal inhibitor, chloroquine, clearly indicating that autophagosome turnover was blocked. Upon infection, there was an increased viral titre in the cell culture supernatant and a marked reduction in glucose-stimulated insulin secretion (112.9 ± 24.4 vs 209.8 ± 24.4 ng [mg protein]–1 h–1; p = 0.006), compared with uninfected controls, but cellular viability remained unaffected. Importantly, and in agreement with the observations for INS(832/13) cells, E16 infection impaired autophagic flux in primary human islet cells (46.5 ± 1.6 vs 34.4 ± 2.1 μm2/cell; p = 0.01). Conclusions/interpretation: Enteroviruses disrupt beta cell autophagy by impairing the later stages of the autophagic pathway, without influencing expression of key genes involved in core autophagy machinery. This results in increased viral replication, non-lytic viral spread and accumulation of autophagic structures, all of which may contribute to beta cell demise and type 1 diabetes. [ABSTRACT FROM AUTHOR]

A virus is a small, infectious particle that lives inside a host. Today, viruses have an important role in our daily life. The reason for this is that viruses, including coronavirus (COVID-19), are affecting many people in the world. The most important measure that can be taken to stop the spread of the disease will be self-taken measures along with increased the awareness of individuals. Schools, and especially teachers, play a vital role in this. Sharing accurate information and science-based facts about viruses will help reduce students' fears and anxieties about the disease and support their ability to cope with its effects on their lives. The main purpose of this activity is to help students learn about viruses, how they spread and how to prevent them from spreading. The 5E (Engagement, Exploration, Explanation, Elaboration, and Evaluation) learning model is used. The organization of these activities leads to provide research and constructivist learning rather than a traditional laboratory activity series. Also, students have fun during these activities. [ABSTRACT FROM AUTHOR]

The liver is home to five known human hepatitis viruses (hepatitis A virus–hepatitis E virus). Despite being phylogenetically unrelated, these viruses replicate and spread in the liver without causing apparent cytopathic effects, and all have evolved strategies to counteract antibody-mediated inhibition of virus spread. In this review, we discuss the current understanding regarding the spread mechanisms for these viruses with an attempt to extract common principles and identify key questions for future studies. [ABSTRACT FROM AUTHOR]

The first case of the new coronavirus, COVID-19, was reported in China on 17 November 2019. By the end of March 2020, the rapid global spread of infection affected over 1 million people. Italy is one of the countries most impacted, with over 100,000 positive cases identified. The first detected cases were reported on 21 February 2020 in two Italian towns: Vo' Euganeo in the Province of Padua, Veneto region, and Codogno, in the Province of Lodi, Lombardy. In the next weeks the epidemic spread quickly across the country but mainly in the north of Italy. The two regions: Veneto and Lombardy, implemented different strategies to control the viral spread. In Veneto, health personnel tested both symptomatic and asymptomatic subjects, while in Lombardy only symptomatic cases were investigated. We analyzed the evolution of the epidemic in these regions and showed that testing both symptomatic and asymptomatic cases is a more effective strategy to mitigate the epidemic impact. We strongly recommend that decision-makers: ensure early isolation of symptomatic patients and rapid identification of their contacts; maximize testing rapidly, especially among people with multiple daily contacts with infected populations, high exposure to the public in essential services; rapidly increase diagnostic capacity by mobilizing trained personnel capable of performing rRT-PCR on respiratory samples; equip the population with protective masks. [ABSTRACT FROM AUTHOR]

The effect of non-pharmacological interventions to contain the spread of SARS-CoV-2 have caused negative impacts, especially in education. Re-opening schools and universities is regarded as a high risk scenario. This paper seeks to understand, with the help of mathematical modeling, possible mechanisms through which the virus could spread in an academic environment and to quantify contagions attributable to participating in academic activities. To simulate the dynamics of contagion at the University, an agent-based mathematical model that incorporated stochastic differential equations was built using academic data for the University's 2020-2 semester. The model suggests that hybrid-attendance combined with epidemiological surveillance can produce very safe operating conditions without significantly contributing towards more COVID infections in the city of Bogotá. [ABSTRACT FROM AUTHOR]

Peste des Petits Ruminants (PPR) is a viral disease affecting predominantly small ruminants. Due to its transboundary nature, regional coordination of control strategies will be key to the success of the on-going PPR eradication campaign. Here, we aimed at exploring the extent of transboundary movement of PPR in West Africa using phylogenetic analyses based on partial viral gene sequences. We collected samples and obtained partial nucleoprotein gene sequence from PPR-infected small ruminants across countries within West Africa. This new sequence data was combined with publically available data from the region to perform phylogenetic analyses. A total of fifty-five sequences were obtained in a region still poorly sampled. Phylogenetic analyses showed that the majority of virus sequences obtained in this study were placed within genetic clusters regrouping samples from multiple West African countries. Some of these clusters contained samples from countries sharing borders. In other cases, clusters grouped samples from very distant countries. Our results suggest extensive and recurrent transboundary movements of PPR within West Africa, supporting the need for a regional coordinated strategy for PPR surveillance and control in the region. Simple phylogenetic analyses based on readily available data can provide information on PPR transboundary dynamics and, therefore, could contribute to improve control strategies. On-going and future projects dedicated to PPR should include extensive genetic characterization and phylogenetic analyses of circulating viral strains in their effort to support the campaign for global eradication of the disease.

Tunneling nanotubes (TNTs) are actin-rich intercellular conduits that mediate distant cell-to-cell communication and enable the transfer of various cargos, including proteins, organelles, and virions. They play vital roles in both physiological and pathological processes. In this review, we focus on TNTs in different types of viruses, including retroviruses such as HIV, HTLV, influenza A, herpesvirus, paramyxovirus, alphavirus and SARS-CoV-2. We summarize the viral proteins responsible for inducing TNT formation and explore how these virus-induced TNTs facilitate intercellular communication, thereby promoting viral spread. Furthermore, we highlight other virus infections that can induce TNT-like structures, facilitating the dissemination of viruses. Moreover, TNTs promote intercellular spread of certain viruses even in the presence of neutralizing antibodies and antiviral drugs, posing significant challenges in combating viral infections. Understanding the mechanisms underlying viral spread via TNTs provides valuable insights into potential drug targets and contributes to the development of effective therapies for viral infections., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Lv, Li, Wang, He and Zhang.)