Airborne diseases, such as highly pathogenic avian influenza, are among the deadliest threats to the egg industry and can easily cause devastating losses of poultry when severe outbreak events occur. During the ongoing transition to cage-free production, uncertainty regarding ventilation designs for cage-free facilities also exposes vulnerability with respect to disease control within facilities. To address ventilation system design and the capability of restraining internal airborne disease spread, this study was conducted to model and compare indoor airborne virus dispersal for a commercial cage-free hen house within four different ventilation schemes. A one-eighth length, full-scale, floor-raised hen house with commercial bird density was modeled to simulate the environmental conditions and disease spread under steady-state conditions inside the barn during cold weather. Analyses of the dispersion of virus particles coupled with airflow patterns were performed by visualizing contours of virus particles and air velocities at critical locations. In addition, the virus mass fraction at bird level was of particular interest when comparing and evaluating the performance of various ventilation schemes. The simulation results demonstrated that the internal dispersion of airborne virus particles was determined by indoor airflow patterns and implied the role of ventilation configuration in reducing disease spread in a poultry barn. Furthermore, valuable insights are provided for further investigations of ventilation options for cage-free hen housing.The current ventilation designs of poultry barns have been present deficiencies with respect to the capacity to protect against disease exposure, especially during epidemic events. An evolution of ventilation options is needed in the egg industry to keep pace with the advancing transition to cage-free production. In this study, we analyzed the performances of four ventilation schemes for constraining airborne disease spread in a commercial cage-free hen house using computational fluid dynamics (CFD) modeling. In total, four three-dimensional models were developed to compare a standard ventilation configuration  with three alternative designs, all with mid-wall inlet and a central vertical exhaust. A one-eighth scale commercial floor-raised hen house with 2365 hens served as the model. Each ventilation configuration simulated airflow and surrogate airborne virus particle spread, assuming the initial virus was introduced from upwind inlets. Simulation outputs predicted the MICE and MIAE models maintained a reduced average bird level at 47% and 24%, respectively, of the standard TISE model, although the MIRE model predicted comparable virus mass fraction levels with TISE. These numerical differences unveiled the critical role of centrally located vertical exhaust in removing contaminated, virus-laden air from the birds housing environment. Moreover, the auxiliary attic space in the MIAE model was beneficial for keeping virus particles above the bird-occupied floor area. The shift to cage-free egg production is the most significant evolution in poultry facilities that has been faced in decades . Aviary Moreover, the capacity of ventilation systems to constrain airborne disease spread is paramount during epidemic outbreaks. Airborne or aerosol transmission is a typical route of infectious disease, which occurs when birds inhale fine particles or aerosols that contain contagious pathogens. Airborne transmission can take place at greater distances because diseases can be dispersed through airstreams from outdoor to indoor environments and from bird to bird. Such transmission can be worse if the pathogen-laden air is easily transported through most bird-occupied areas prior to being exhausted, as conventional ventilation schemes are designed to maintain indoor animal comfort and may neglect the importance of disease control. During the spring of 2022, an ongoing outbreak of highly pathogenic avian influenza (HPAI) was reported throughout the United States, leading to the loss of millions of birds to date at, representing the worst loss since 2015 ,9. The HEvaluating ventilation performance to constrain airborne disease dispersal in a commercial hen house is challenging and laborious, with the infeasibility of exposing birds to pathogenic contaminants. Instead, a mathematical simulation methodology is preferred as an alternative approach to field measurements . ComputaThe need to address problems associated with airborne disease dispersion in poultry houses has encouraged researchers to use CFD simulations to assess ventilation designs. In a previous study, we modeled the mass flux profile of virus particles in two different hen housing ventilation schemes that featured opposite airflow directions in two dimensions . In anotAn existing commercial cage-free hen house was modeled at full-scale in three dimension, and four ventilation configurations were simulated using CFD to evaluate ventilation system performance with respect to reducing indoor virus particle transmission at the bird level. Three-dimensional CFD models were developed for a barn with a standard ventilation configuration with realistic hen numbers compared to three alternative designs. Numerical simulations of airflows, along with the dispersion of virus particles during cold weather, were conducted to characterize the dispersal patterns of viruses by calculating their mass fraction profiles. The goal was to compare the performance of each ventilation design in controlling airborne disease spread in typical cage-free hen housings with an emphasis on analyzing the influence at the bird level in order to provide practical recommendations for future refinement of cage-free ventilation options.Three-dimensional models and pertinent simulations were conducted by deploying commercial CFD code FLUENT  . Computaunctions ,24 was aunctions ,26.A floor-raised hen house in Lititz, Pennsylvania, was selected as the commercial house for CFD modeling. The house is 162.15 m 532 ft) long and 13.72 m 45 ft) wide, with a capacity of almost 20,000 birds. Details of the study hen house can be found in our previous publications [2 ft long5 ft wideA total of four ventilation schemes were modeled, including the standard ventilation system currently in use, as well as three alternative designs . The curThree alternative ventilation systems, namely, MICE , MIRE , and MIAE  had identical inlets positioned 1.5 m (59 in.) above the ground that worked with opening baffles and wall plates at the top, yet with different exhaust placement and ceiling features . The midOne-eighth of the study hen house was modeled to take advantage of construction symmetry and save computational resources. The modeled hen house was assumed to have complete insulation, which was not realistic but simplified the primary heat loss during cold weather conditions from exhausting of warm indoor air via the convection ventilation system. Ten inlets with an identical opening size of 3.81 cm (1.5 in.) were modeled for the hen house and preconditioned to provide adequate airflow at a pertinent static pressure difference . Only thThe computational domain of each model involved the barn and ambient air for the sake of analyzing indoor and outdoor airflows. A uniform domain size of 128.2 m × 20.3 m × 24.4 m (420.6 ft × 66.5 ft × 80 ft) was established for each of the four models. To reduce the end-wall effects, only a central section representing one-eighth of the study hen house was modeled with realistic dimensions and representative ventilation features. The designated extra downwind space in the domain was designated to minimize the reverse flows at the boundaries during numerical simulation [2 (1.18 ft2) to stand for an average body weight of 1.59 kg (3.5 lb.) [To approach realistic simulations and assess disease spread at the hen level, 2365 individual hens were modeled to represent approximately one-eighth of the whole flock size. An individual hen model was created using a simplified torso–head–tail shape with a surface area of 0.11 m3.5 lb.) . A unifo3.5 lb.) .The CFD simulations adopted six types of boundary conditions or cell zones. The “wall” boundary conditions included the ground, the top surface of the computational domain, hen model surfaces, and all the components of the hen house, such as ceiling, roof, nesting area, etc., which were all set as non-slip walls, except for the top surface of the domain, which was defined as a zero-shear stress wall ,3,4,19. To simulate the spread of airborne disease, gaseous ammonia was selected as a surrogate contaminant species, as the dispersal behavior of virus particles can be analogous to the diffusion of a tracer gas . The difANSYS meshing was deployed to discretize the computational domain . SkewnesA pressure-based solver was used to conduct all simulations. Governing equations were discretized using a second-order scheme, and a first-order scheme was adopted to calculate turbulent kinetic energy and turbulent dissipation rate.The convergence criteria were not met until both the monitoring variable at selected points and the residual values were stabilized, satisfying the scale threshold. For all simulations, 2500 iterations were applied to ensure all the meshing files were generated with a similar size.Three parallel cross-sectional reference planes were created to characterize simulation outputs, which represented locations in a barn with inlets (CP-I), no ventilation features (CP-N), and an exhaust fan (CP-F), respectively . A row oIn addition, a transversal reference plane TP-I was created to visualize the incoming air and viruses, which was parallel to the ground through the middle of individual inlets in each model. The TP-I was set to 2.6 m (8.53 ft) above the floor in the TISE model, whereas the TP-I in the MICE, MIRE, and MIAE models was set to a height of 1.6 m (5.25 ft).Five bird-occupied zones were created to capture the simulation data at the bird level. Each zone represented conditions at different locations within a cross-sectional reference plane covering all the floor area ,3,4. EacSimulation results of environmental parameters of interest were previously analyzed by creating contours of airflow vectors, temperature distribution, and static pressure difference ,4,29,30.In addition to characterizing the virus spread from a perspective of the entire barn, point-to-point data were exported from five bird-occupied zones to compare and evaluate the potential threat at the bird level with the aid of statistical analysis. To quantitatively analyze the performance of different ventilation schemes in controlling the spread of airborne disease, environmental parameters and mass fraction data of ammonia were exported from each cross-sectional reference plane. All the simulation data points were treated as repeated measurements that were fit to a mixed-effects model to verify whether altering ventilation schemes and locations (zones) had statistically significant effects on the results of interest. Analysis of variance (ANOVA) and Tukey tests were employed to test pertinent hypotheses and perform multiple comparisons using R v4.1.2 ,38.3/s (4174 ft3/min), 1.93 m3/s (4089 ft3/min), 1.96 m3/s (4153 ft3/min), and 1.91 m3/s (4047 ft3/min) based on the simulation output of the TISE, MICE, MIAE, and MIAE models. In addition, the internal volume of the barn varied among the four models, namely 639.42 m3 , 639.36 m3 , 1058.25 m3 , and 1052.67 m3  for the TISE, MICE, MIRE, and MIAE models, respectively. The TISE and MICE barns had an identical internal volume with a flat ceiling, whereas the MIRE and MIAE barns had greater interior volume either without a ceiling or with an attic space . Air velocity contours at three cross-sectional reference planes are presented as geometric illustrations of the hen house with four ventilation schemes to visualize the indoor air patterns in each case  regions. However, slight yellowish and green areas were observed in the upper central portion of the barn in the MIAE model, indicating moderate accumulations of virus in the attic area.Transversal planes (TP-I) of virus particles within each model  showed sIncoming streams of simulated virus particles resulted in distinct color sections of contamination in all four models, with boundaries in the middle of the plane, especially in the MIRE model. Due to longer trajectories of incoming air jets in the TISE model, streams containing high concentrations of viruses were also longer than those of the other three models. Concentrations of virus particles tended to be higher from the inlets that were close to the exhaust fan in the MICE model, in contrasted to observations in the MIRE model. The largest orange-reddish area in the MIRE model was observed near the inlet at the end farthest away from the exhaust fan. Incoming streams of viruses in the MIAE model were relatively uniform, with a short length of orange-reddish trajectories, whereas a yellow region was formed in the central part, indicating moderate accumulations of virus particles near the attic entrance.The dispersal behavior of virus particles differed at three cross-sectional reference planes and was influenced by the ventilation features of inlet and fan location. The contours of mass fraction to visualize the distribution of virus concentrations are shown in a steady state in At CP-I, the influence of the inlets suggested significant effects on the internal air circulation, as well as virus spread . The disDifferences in virus mass fractions were observed at CP-N between the left and right sides of the barn in all models, although no ventilation features are part of this plane . AverageThe mass fraction contours at the CP-F plane in the TISE model showed more uniformity compared to the other three models . No visiVirus mass fraction data at bird level were captured and exported for quantitative analysis to compare the internal airborne disease within each ventilation scheme. Simulation data from the five bird-occupied zones were analyzed separately at CP-I, CP-N, and CP-F reference planes to compare virus levels from each ventilation model.The effects of key factors and their interactions were statistically significant in terms of mass fractions of virus based on the outputs of ANOVA analyses at three separate reference planes . The numSubsequent Tukey’s tests were performed to test the statistical significance of pair-wise differences of the means of mass fraction data from each plane. The results of statistical analyses demonstrated that most of the differences between pairwise comparisons were statistically significant due to the large scale of data points from a single zone , althougBar graphs were created for simulation results of mass fractions from five bird-occupied zones in the same plane with annotated statistical significance . Due to Mass fraction data from five zones at CP-N b suggestScenarios at CP-F c presentThe large error bars in the MICE, MIRE, and MIAE models in Zone-3 indicate dynamic virus concentrations at the bird level close to the nest-box region. However, the variation of mass fractions was not obvious in Zone-3 within the standard ventilation system of the TISE model compared to the three ventilation alternatives, implying a relatively steady air movement in that region.Previous studies have demonstrated that the performances of these three alternative ventilation schemes represented by the MICE, MIRE, and MIAE models are capable of providing indoor environmental conditions  comparable with those of the industry-standard TISE ventilation scheme ,29,30,31Because viruses were initially injected through the upwind (left-side) inlets, all four models showed a consistent general tendency wherein the left portion of the barn had higher mass fractions of virus than the right portion. Analyses of virus mass fractions at three cross-sectional references planes revealed similar or even lower virus levels, on average, within the three alternative models compared with the standard TISE model. The MICE model had an indoor volume identical to that of the TISE model, although the average virus levels at the bird level were 47% and 19% lower in the CP-I and CP-N planes, respectively, and were only 3.4% higher in the CP-F plane. The average virus level in the MIAE model was just 1.4% higher than that in the TISE model at CP-N yet was 24% and 17% lower than the TISE model in the CP-I and CP-F planes, respectively, at the bird level. According to the analyses of simulation results from five bird-occupied zones in each reference plane, the MICE and MIAE models exhibited more competitive performances with respect to maintaining low concentrations of viruses relative to the standard TISE model, whereas the virus level in the MIRE model was slightly higher than that in the TISE model at the bird level .Hence, the MICE and MIAE models have advantages in terms of internal air circulation over the TISE model from the perspective of maintaining lower levels of airborne particles under the same simulation conditions. In fact, the MICE model represents a ventilation configuration that is widely used in Europe, forming an overall bottom-to-top airflow path inside the barn, which might be a more efficient design to exhaust the airborne contaminants that were absorbed from the upwind atmosphere ,41. By vIn contrast, such internal air circulations may not be as efficient as in the MIRE and MIAE models due to the different ventilation configurations. However, the partial ceiling of in the MIAE model played a critical role in containing the virus-laden air inside the attic by blocking vertical air movements in the process of internal air circulation. As a result, the average virus level in the MIAE model was the second lowest at the bird level at CP-I and CP-N and was the lowest at CP-F among all models, as a majority of viruses were trapped in the recirculating zone in the attic space. This evidence warrants further exploration of the use of an attic area for pretreatment of exhaust air. Without any ceiling, vertical air movement took place frequently in the case of the MIRE model, which enabled viruses to be transmitted thoroughly in the left portion of the barn . Due to Herein, indoor dispersal of virus particles spread was investigated, assuming the virus was initially introduced through upwind inlets with preconditions of constant wind (speed and direction). The evaluation was conducted during cold weather, when a minimum amount of fresh air exchange challenges the provision of high-quality air in the hen house. Future studies should be conducted on scenarios in which the virus is introduced from within the barn to simulate the indoor dispersal of virus particles either in a transient or steady state. In this study, virus particles were simplified as gaseous contaminants; therefore, no phase changes were considered during the numerical simulations. Although airborne or aerosolized virus particles are mostly infinitesimal and can be treated as gaseous contaminants, their transmission behavior may be expressed in a more complicated manner, such as by binding to respiratory droplets or dust particles before falling to the ground, which is worthy of further investigation. Furthermore, the broad computational domain used in this study can be employed to investigate the influence on neighboring barns and ambient environments during an outbreak event of the study hen house.Numerical simulation results demonstrated that the dispersion of airborne virus particles inside a floor-raised hen house is highly dependent on internal air movements. Although all four tested models had similar ventilation rates and static pressure differences, the patterns of indoor air circulations varied with ventilation configurations, as well as the volume of indoor spaces. Simulation results of mass fractions of virus particles from bird-occupied zones at three cross-sectional reference planes suggested that the alternative ventilation designs MICE and MIAE were able to maintain up to 47% and 24% lower virus levels, respectively, on average, compared with the TISE model. The driving forces from the ceiling exhaust fan played a critical role in creating strong internal air circulations that prompted expulsion of contaminated air. In addition, the partially open attic space of the MIAE model proved beneficial to containing the spread virus particles based on the MIAE simulation results. Although the MIRE model presented virus mass fractions similar to those of the TISE model due to vigorous internal air mixing, the simulation data can be used to refine current designs.In summary, CFD modeling is a powerful tool to investigate airborne disease spread in animal housing, allowing researchers to obtain deep insights about the relationship between ventilation configurations and disease control. The CFD models developed in this study can be further refined to evaluate other ventilation options for various types of cage-free hen houses with specific aims.


Specific clones were enriched after 5 rounds of bio-panning and four identical genes were classified after the sequence analysis. Moreover, the higher mutation rates were revealed in the CDR regions, especially in the CDR3. IgY showed specific binding activities to both EV71-infected and Coxsackievirus 16-infected cell lysates and high infectivity inhibitory activity of EV71. However, while IgY detected a 37 kDa protein, the selected scFv seemingly detected higher size proteins which could be cell protein instead of EV71 proteins. Despite the highly effective chicken antibody generation, the purity of virus particles prepared by size exclusion is the limitation of this study, and further characterization should be carried out rigorously.Enterovirus 71 (EV71) is the major etiological agent contributing to the development of hand-foot-mouth disease (HFMD). There are not any global available vaccines or antibody drugs against EV71 released yet. In this study, we perform the virus immunization in a cost-effective and convenient approach by preparing virus particles from size exclusion and immunization of chicken. Polyclonal yolk-immunoglobulin (IgY) was simply purified from egg yolk and monoclonal single-chain variable fragments (scFv) were selected via phage display technology with two scFv libraries containing 6.0 × 10 Picornaviridae family, is one of the major serotypes of human enterovirus type A  × (H − L) + L], where Y represents half of the mean optical density at 570 nm (OD570) of the cell control without the antibody, B represents the mean OD570 of wells with the antibody dilution nearest to and below Y, A represents the mean OD570 of wells with the antibody dilution nearest to and above Y, and L and H are the antibody concentrations at B and A, respectively.The neutralization assay was used for measuring the ability of the antibody to inhibit the cytopathic effects induced by viruses. Briefly, 96-well tissue culture plates were seeded with 3 × 10 for 1 h . The RD t tests. A p value of < 0.05 was considered statistically significant.GraphPad Prism (version 6.0 software) was used for data analysis. The ELISA results were all performed duplicated, were analyzed and expressed as means plus or minus standard errors via multiple In conclusion, we carried out the immunization of EV71 virus with a cost-effective and convenient approach by simple virus purification using size exclusion and chicken immunization. The polyclonal IgY antibodies showed specific to EV71 virus and effectively inhibited the EV71 infection to RD cells. Additionally, we constructed scFv libraries and selected specific monoclonal antibody with phage display technology, which is more efficient in terms of cost and time for antibody generation. Unfortunately, the monoclonal antibody had no specific to EV71 virus. However, it still shows an inhibitory effect on EV71 virus infection, which led us to postulate that EV71S1 has the potential to recognize host cell proteins. Finally, reviewing the entire experimental design, we still believe that cost-effective and convenient approach is feasible, although no specific monoclonal antibody has been selected, but the polyclonal IgY antibodies results still have great potential for future development of diagnostic agents or treatments for EV71 infection. At the same time, scientists should also reflect about the purity of the virus when using animal post-immunization methods to generate antibodies to be more efficient.


Respiratory viruses including Respiratory Syncytial Virus, influenza virus and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause serious and sometimes fatal disease in thousands of people annually. Understanding virus propagation dynamics within the respiratory system is critical because new insights will increase our understanding of virus pathogenesis and enable infection patterns to be more predictable in vivo, which will enhance our ability to target vaccine and drug delivery. This study presents a computational model of virus propagation within the respiratory tract network. The model includes the generation network branch structure of the respiratory tract, biophysical and infectivity properties of the virus, as well as air flow models that aid the circulation of the virus particles. As a proof of principle, the model was applied to SARS-CoV-2 by integrating data about its replication-cycle, as well as the density of Angiotensin Converting Enzyme expressing cells along the respiratory tract network. Using real-world physiological data associated with factors such as the respiratory rate, the immune response and virus load that is inhaled, the model can improve our understanding of the concentration and spatiotemporal dynamics of the virus. We collected experimental data from a number of studies and integrated them with the model in order to show in silico how the virus load propagates along the respiratory network branches. According to the American Center for Disease Control (CDC), influenza has killed between 12,000 and 61,000 people annually and caused approximately 460,000 hospitalizations per year in the United States. Respiratory Syncytial Virus (RSV) is estimated to cause close to 33 million cases of respiratory disease each year globally, with approximately 3 million hospitalizations2. The bifurcation geometry of the airway network as well as the distribution of cell surface receptors that the virus can bind to also changes the virus dispersion along the respiratory network branches. For example, in the case of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus is known to use the Angiotensin Converting Enzyme (ACE2) receptor to bind to and enter cells3. Since cells expressing high ACE2 are not spread evenly throughout the respiratory system, some areas are more vulnerable to SARS-CoV-2 infection, thus creating a heterogeneous concentration distribution across the respiratory airway network system. Different variants can also have more or less affinity for ACE2 as well as a secondary receptor that SARS-CoV-2 uses, TMPRSS24.Once a respiratory virus enters the nose or mouth, it can move down the throat towards the lungs but much of the virus will deposit on the walls of the upper respiratory tract and then infect cells along the way, leading to amplification of the initial virus load. In this study, we are interested in virus spread from the upper to the lower respiratory tract. We thus consider that an infection has been controlled if it remained restricted to the upper respiratory tract. The dispersion of virus particles throughout the respiratory airway network system  is influenced by multiple factors including respiratory pattern , the concentration of virus particles in the inhaled air, also known as exposure level, the distance that the virus particles can travel through the respiratory airway network and importantly the strength of the immune responseThe temporal dynamics of the infection and the spreading pattern along the respiratory airway branches can be characterized and predicted effectively if the viral concentration dynamics  can be characterized using modeling and simulations along with critical parameters that influence the system. From a personalization perspective, by being able to predict how the virus will impact a patient based on known criteria, medical staff will be able to make timely, informed and accurate decisions to prevent development of severe conditions. In the pharmaceutical industry, such model can benefit the development of drugs by allowing the in silico screening and characterization of inhibitory drugs prior to costly in vivo trials.Development of a temporal viral concentration model that can be used to analyze changes in virus dynamics as virus particles propagate along the branches of the airway in the respiratory system. This is achieved by accounting for the generation branching geometry of the respiratory airway network, and integrating models of the air flow that affects viral deposition and replication, and its impact on the virus spread distribution along the airway generations.Modelling the spatial and temporal dynamics of the virus particle within the respiratory tract, by considering parameters such as the breathing rate and dynamic viral pleomorphic size change with respect to the changes from the inhaled dosage.Sensitivity analysis of the viral propagation along the airway generation branches considering factors such as the exposure level, cellular receptor availability and immune response and then characterizing the temporal dynamics in virus load with respect to different patient parameters such as age, gender, and lifestyles.In the literature, we can find information about the temporal dynamics of virus infections over time, but not about the changes in viral dynamics along the respiratory airway branches. The main aim of this study was to develop a generic computational model for characterizing the dynamics of virus infection of the respiratory tract. The study uses SARS-CoV-2 as a case study to present how the derived model could be used to characterize the virus propagation dynamics in humans. The main contributions of this study are as follows: The main steps in the process of deriving the computational model for the virus propagation dynamics along the respiratory airway generations are illustrated in Fig. 5. When virus particles enter through the mouth or nose, they flow through the respiratory tract. To determine the amount of virus particles that enters a particular airway generation, the air flow velocity u through that branch is required. To compute airflow velocity in each airway generation, this study takes into account the bifurcation transformation between the large airways that separates into smaller branches with reduced lengths and diameters as illustrated in Fig. To determine airflow dynamics, the respiratory generation model in this study is taken from literatureQ is the flow rate, P is the pressure, l) and right (r) branches, and the numbers along with l and r refers to the airway generation number. In addition, the subscript in and out stands respectively for the inlet and outlet of the branch. When air flows down the airway, there is a drop in pressure as well as resistance against the air flow (termed as impedance). We adapt these properties and model the flow using transmission line circuit theory, where its equivalence is voltage drop in response to changes in the current flow6. Hence, following the concepts from transmission line circuit theory, the impedance (Z) at the outlet of the parent airway  and diameter of the airway generations  can be determined using the advection-diffusion propertyThe advection mechanism is the dominant force that facilitates the propagation of particles and their deposition along the upper airways due to the high airflow velocity, which in turn, causes turbulence in the airflow. This differs from the lower branches within the respiratory track, which is dominated largely by pure diffusion. These factors are next taken into account to compute virus concentration in each airway generation.ith airway generation, ith airway generation . Given the initial inlet virus concentration that a person consumes through the mouth or nose is By taking these factors into account, this section presents how the advection-diffusion mechanism of the virus particle propagation can be utilized to compute the concentration over an airway generation mentclass2pt{minima, the virus concentration at the steady state is expressed in Eq. (In order to simplify virus concentration dynamics expression given in Eq.  by removthat Eq.  can be sd in Eq.  (see SI k) and followed by the virus reproduction rate (p), which are required for determining the virus concentration using Eq. (Next subsection describes the methods for computing virus deposition rate (sing Eq. .k) mainly takes place under three main mechanisms, impaction , cytotocxic T-cells (CTL) and antibodies (Abs), and has two main phases: the innate and the adaptive immune response13. It is of course challenging to measure the immediate response to a SARS-CoV-2 infection but correlative studies indicate that IFNs play an important role in protecting against severe disease. Impaired IFN response appears to correlate with worse outcomes14 while genome wide studies have shown particular genotypes in key IFN pathway related genes correlate with more severe outcomes16. Alongside this, the limited T-cell response, an early responder to infection in its own right, is also associated with more severe disease suggesting that a more robust response may help to control the infection before it gets out of control. Because of the complexities of the immune response, the variations within it and the lack of absolute clarity, it is challenging to account for each pathway in the overall response, but this is a complexity that can be added in layers as the process becomes more refined. For now, we will focus on the T-cell response as the in vivo data is clearer.Virus concentration will vary across the respiratory tract as infection progresses Fig. a. The SAC) and immune response dynamics by assuming T-cell (T) proliferation by viral infection follows a Michaelis Mention growth and the relationship which explains the activation of T-cell proliferation by virus infection is log-sigmoidal form, along with the susceptible cell (A) infection and infected cell (I) generation. However, this model has originally been developed for characterizing the dynamics in influenza virus and the width of the log-sigmoidal function was considered as 1  and r is the T-cell proliferation rate (see3 for more information about this model).The model Eqs. –10 reprehere).The computational outcomes presented below are generated by using the parameter values listed in Table Q and the velocity u in each airway generation by using real physiological parameters such as the length and diameter of the airway generations5. Dimensions will change in younger children and this can be added to the model if focusing on children23. Figure Q and u over the 23 generations when air enters through the nose or mouth at a rate of 30 lminThe term airway generations is used to describe what part of the respiratory tract the virus is in. The higher the generation the deeper into the respiratory system it is. Generation numbers go from 0 (top of trachea/mouth/nose) to 23 . To model how a virus particle moves through the respiratory system, based solely on air movement, we used the derived model in Eq. 18. In terms of velocity and deposition, Fig. −1. It can be observed that the temporal dynamics in the virus deposition rate over the first 15 airway generations is considerably higher. In addition, the impact of increasing inlet airflow rate −1 presented in Fig. The virus shape is pleomorphic  but is predominantly elliptical or spherical. Also, as larger particles are mostly trapped in the upper airways, while smaller  particles propagate deep down the lungs. Therefore, we also analyzed the impact of the virus particle shape on its propagation through the respiratory system based on changes in its diameter 24 (or Infectiousparticles/ml) entering the respiratory tract , but with the same variance.To understand the virus concentration dynamics as it flows along the airways, our analysis assumes a virus concentration of 3. Figure 25, which justifies the need for self-isolation between 7 and 14 days post-infection as the virus concentration would be at its highest during this period, which increases the probability of onward transmission.Figure Virus concentration is impacted by apoptosis driven by infection Fig. a, ACE2 er is 0.5–10 K is Naturally, to identify major factors impacting virus distribution through the respiratory system it is important to remember that each factor does not act in isolation, however, our model is able to isolate each factor and project it’s influence on virus dynamics. The immune response clearly plays a role in this. As illustrated earlier, cell death is important but the cellular and antibody based immune responses are vital too. Although an antibody response may take a few days to optimally respond to an infection, the early cellular response is the front line of defense and plays a major role in limiting virus access to the lungs. Figure p and the immune response by T-cells r on the change in virus concentration over the respiratory tract for three cases: p is much larger compared to the immune response by T-cells and is more likely to reach high concentrations in the lung. The model also illustrates that the concentration in the lung can increase initially but an efficient immune response is vital to rapid reduction of virus, both in the lung and upper respiratory tract. Moreover, a rapid immune response clears virus by 10 days approximately as shown in Figs. To expand the previous results further, it is important to consider virus concentration throughout the respiratory system rather than just overall values. Figure r and the virus reproduction rate p and highlights that rapid immune response can effectively control the spread of the virus downward the respiratory tract. Moreover, Fig. r and decrease in the virus reproduction rate p, it greatly contributes to curb the virus load more effectively since the time taken to reduce the virus load decreases with higher r value. Interestingly, the airflow rate In addition, Fig. A major strength of our model is the ability to identify and understand risk factors that may contribute to poor outcomes.22. Figure I) depicts the change in virus concentration across the respiratory tract with respect to three different age groups, whilst Fig. II) shows the impact of gender. The model predicts that virus concentration increases on average as age increases, while women will have, on average, a lower virus concentration than men, because there is a gender difference in the average immune response to respiratory infections22. This does not mean that women are more likely to have a better outcome when infected as other factors can influence that too, but it does point to a potential area of concern for men. The model also predicts that the virus concentration increases in smokers and those that consume excessive amounts of alcohol, because of the impact these lifestyle habits can have on the immune response . This model also indicates that smoking may lead to a higher virus concentration than in those that consume alcohol excessively.For example, by incorporating real world data, Fig. nse Fig. III. This26 identified multiple drugs that were effective against SARS-CoV-2 and are now entering in vivo trials). This study reports the development of a model that maps the temporal virus concentration dynamics throughout the respiratory tract with respect to a range of parameters that affect the propagation of the virus and then explores how the model can provide deep insights into the temporal dynamics of an infectious virus along the respiratory tract. This model provides the opportunity to predict in silico, the ability of a respiratory virus to reach the lower parts of the lung and potentially cause disease, thus opening up opportunities to understand areas such as virus variants, virus-vaccine dynamics and antiviral drug efficacy and potential real world impact, without the requirement for in vivo data.In response to the global COVID-19 pandemic, there has been considerable research undertaken to understand the virus, screen current and novel compounds to identify drugs that might be effective against SARS-CoV-2 and to develop vaccines , because the model Figs.  and  8 s26. The main reason behind this is because the virus binds to ACE2 expressing cells. Figure 27. In our study, the virus replication was derived by numerically solving the systems of differential Eqs. , the probability of the virus propagation and deposition deep into the lungs is high due to their micrometer scale diameter. However, our study has found a number of factors that affects the propagation dynamics of the virus that fluctuate as the virus flows through the branch generations of the airways. It is well known that the initial viral infection occurs in the upper respiratory tract and then spreads further down into the lungg in Eq. . Figure ial Eqs.  with cli34 can lead to varying densities of ACE2-expressing cells and immune response levels, and these differences will have an impact on clinical outcome as well as how easily a person will transmit the virus to others. Our analytical model considers temporal dynamics in the density of ACE2-expressed cells along the branches of the airway tract, where there is greater ACE2-expressed cell density in the nose and mouth (airway generation 1–2) as well as in the alveoli region (airway generation 21–24). This complies with a recent study12 that suggested the oral mucosa has good expression of ACE2, while the study35 highlighted that the ACE2-expression seems predominantly greater in the AT2  cells that express high levels of ACE2 in the lung, while the upper airways have a broad distribution of ACE2. This is why the virus load is considerably higher in the top and lower sections of the respiratory track compared to branches in the middle airway generations, and this is shown in in Fig. 36.It is clear from this model that ACE2 expression is a key factor that determines virus infection, replication and distribution in the respiratory system. In fact, from our models, ACE2 expression distribution along with the immune response are key factors in determining infection outcome. It is known that a number of factors such as smoking, age, gender and raceI and II), then there is opportunity for the virus to overcome it. This indicates clearly that the likelihood of an infection overcoming the initial immune response and moving deeper into the respiratory tract is dependent, not only on the initial viral load but also on the robustness of the immune response, as our model shows  as well as in the adaptive immune response . This in turn facilitates the progression of virus and increase the virus load along the respiratory tract, as a result39. Also, the T-cell composition vary with sex depending on a number of factors such as environmental factors, nutrition status and the composition of the microbiome40. Moreover, differences in airway dimensions as well as the inlet air volume between adult and children23 could influence on the spread of viral infection dynamics. However, due to lack of airway dimensions with respect to age, we assumed the airway dimensions given in Table It is known that there are particular cohorts of people that are most at risk of suffering from severe COVID-19 and death. Age is clearly the major predictor of likely outcome with the likelihood of severe disease or death increasing with age, but other factors such as obesity, diabetes and smoking can also contribute to an increased risk of a poor outcomeBiological understanding of SARS-CoV-2 is vital; how it infects, how it causes disease etc. Alongside that however is the vital need to build a wall of knowledge that will help to limit the impact of it and other pandemic and endemic viruses in the future. Accurate, rapid in silico models that incorporate real world data and evolve with that data will allow rapid identification of threats, rapid identification of vulnerable people to disease and rapid identification of drugs that are targeted correctly and effectively. The model proposed here lays the foundations of this and creates a framework that can be evolved and iteratively improved. It is a model that can predict outcomes before the biology confirms them and can be refined to improve the predictability and the quantification of risk associated with known and unknown threats going forward.Supplementary Information.


Pseudorabies virus (PRV) has received widespread attention for its potential health effects on humans, wildlife, domestic animals, and livestock. In this review, we focus on PRV dynamics in wildlife, given the importance of wild-origin PRV transmission to domestic and farm animals. Wild boars, pigs, and raccoons can serve as reservoirs of PRV, with viral transmission to domestic livestock occurring via several routes, such as wild herd exposure, contaminated meat consumption, and insect vector transmission. Many endangered feline and canine species can be infected with PRV, with acute disease and death within 48 h. The first confirmed human case of PRV infection in mainland China was reported in 2017. Thus, PRV exhibits potentially dangerous cross-host transmission, which is likely associated with inappropriate vaccination, poor awareness, and insufficient biosecurity. Currently, no vaccine provides full protection against PRV in all animals. Here, we summarize the epidemiology and pathogenesis of PRV infection in wild, domestic, and farmed animals, which may facilitate the design of novel therapeutics and strategies for controlling PRV infection and improving wildlife protection in China.  Herpesviridae and subfamily Alphaherpesvirinae [Belonging to the family svirinae , the psesvirinae  based onsvirinae  and is aWild boars and pigs are the primary natural hosts of PRV and the only latent carriers . PRV-relIn this review, we provide a brief overview of the traceability, transmission, and vaccination of PRV infection in animals with the aim to strengthen PR control measures.At present, the epizootiology of PR disease is not completely understood. One hypothesis for herd-to-herd transmission is that wild animals  act as disease reservoir hosts and spread the virus from one farm to another . AlternaWild boars are reservoirs for various infectious diseases in livestock and humans, including classical (CSFV) and African swine fever viruses (ASFV), porcine circovirus 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSV), porcine parvovirus (PPV), hepatitis E virus (HEV), swine influenza virus (SIV), Japanese encephalitis virus (JEV), and torque teno virus (TTV) ,40.PRV infection is enzootic and widespread in Eurasian wild boars ,42, withAs wild boar populations expand their range, there is increased potential risk for disease transmission that may affect healthy of humans and domestic swine, and conservation of wildlife. Based on long-term serological field studies, PRV is considered endemic in wild boar populations in the USA, including in the southern and central states  [Ursus arctos) in Slovakia [Detection of antibodies to canine distemper virus (CDV), canine herpesvirus type 1 (CHV-1), canine parvovirus type 2 (CPV-2), canine parainfluenza virus type 2 (CPIV-2), canine coronavirus (CCV), West Nile virus (WNN), and PRV is positive in European brown bears ( arctos) . PreviouSlovakia  and PRV-Slovakia ,9,76,77.In most cases, PR disease is fatal in bears, with death occurring within 1–3 days of clinical symptoms. Upon consuming infected pig offal or pig heads, bears can show acute and asymptomatic infections. In Himalayan bears, however, only mild clinical signs are reported, with negative neutralizing antibody tests .Procyon lotor) are considered a natural reservoir of PRV [Raccoons  is an endangered feline species [+ and TK+ genotype [The Florida panther ( species . Similar species . Necropsgenotype .Lynx pardinus), one of the most endangered feline species in the world [Cytauxzoon sp. by using PCR assay [The Iberian lynx  based on the testing of brain tissue. Clinical symptoms include anorexia, abnormal vocalizations, and nervousness [PRV infection has been reported in coyotes  non-natural hosts may become infected via contact with immunized pigs ; (2) befPRV has a wide host range and can be transmitted across wild, domestic, and farm animals. The DIVA strategy  has been used in various European countries and the USA based on gE- or gI-deleted vaccines ,72. AttegB, gC, gD, and gE genes play central roles in receptor binding, pathogenicity, and induction of antibodies, with various residues shown to be under positive selection, including residues 43, 75, 848, and 922 in the gB protein, residues 59 and 194 in the gC protein, and residue 348 in gE protein [PRV was previously considered to be limited to host species only. However, there are three possible pathways that have allowed cross-host transmission from wild boars and pigs to non-natural hosts, namely, positive selection, adaptive evolution, and recombination. The  protein , thus su protein . Thus, t protein . Intracl protein . These r protein , and mayIn addition, the receptors of PRV have been identified, including 3-O-sulfonated-heparan sulfate (3-O-S-HS) , the herIn this review, we summarize the epidemiology and pathogenesis of PRV infection in wild, domestic, and farm animals. Recently, various field strains have shown virulence against non-natural hosts, such as bears, coyotes, and panthers, with some found to be epidemiologically associated with swine isolates, wild boar isolates, and vaccine strains. Thus, novel and safe vaccines should be developed for different animals, particularly endangered species, to control cross-host transmission of PRV.


Ophiovirus as a co-infection in a carrot sample from Australia; and a novel member of the genus Umbravirus recovered from a sample of herb parsley from Israel.The family Apiaceae comprises approximately 3700 species of herbaceous plants, including important crops, aromatic herbs and field weeds. Here we report a study of 10 preserved historical or recent virus samples of apiaceous plants collected in the United Kingdom (UK) import interceptions from the Mediterranean region  or during surveys of Australian apiaceous crops. Seven complete new genomic sequences and one partial sequence, of the apiaceous potyviruses apium virus Y (ApVY), carrot thin leaf virus (CaTLV), carrot virus Y (CarVY) and celery mosaic virus (CeMV) were obtained. When these 7 and 16 earlier complete non-recombinant apiaceous potyvirus sequences were subjected to phylogenetic analyses, they split into 2 separate lineages: 1 containing ApVY, CeMV, CarVY and panax virus Y and the other CaTLV, ashitabi mosaic virus and konjac virus Y. Preliminary dating analysis suggested the CarVY population first diverged from CeMV and ApVY in the 17th century and CeMV from ApVY in the 18th century. They also showed the “time to most recent common ancestor” of the sampled populations to be more recent: 1997 CE, 1983 CE and 1958 CE for CarVY, CeMV and ApVY, respectively. In addition, we found a new family record for beet western yellows virus in coriander from Cyprus; a new country record for carrot torradovirus-1 and a tentative novel member of genus  Apiaceae (synonym Umbelliferae) currently comprises 434 genera containing approximately 3700 species of herbaceous plants, characterised by hollow stems, taproots and flat topped flower heads with pedicels that radiate from a central point, called compound umbels [Actinotus sp.), are so contracted as to appear like single flower heads. The family contains many cultivated crop species, including carrot (Daucus carota), parsnip (Pastinaca sativa), celery (Apium graveolens) and arracacha (Arracacia xanthorrhiza); aromatic herbs such as coriander (Coriandrum sativum), parsley (Petroselinum crispum) and dill (Anethum graveolens); and noxious weeds such as giant hogweed (Heracleum mantegazzianum) and poison hemlock (Conium maculatum). Studies of the viruses infecting these species have only occurred sporadically, and this research has largely focused on crop species and their uncultivated relatives, which may play a role in the epidemiology of their viruses.The family d umbels  but whicApiaceae, the greatest focus has been on its viruses, with more than 30 described [Sequivirus), formerly Anthriscus strain of parsnip yellow fleck virus  [Polerovirus), carrot mottle virus  and the carrot red leaf virus-associated RNA (CtRLVaRNA) [Umbravirus carrot mottle mimic virus (CMMoV) was recognised as an alternative CMD component [Potyvirus) [As the carrot is the most important crop species in the escribed . Howeveruivirus) . In AustRLVaRNA) . In Austomponent ,7. Becautyvirus) ,9,10,11.Apiaceae other than carrot, CarVY and several potyviruses have been recorded either in single or mixed infections, and many of these have global distributions. In Australia, in addition to CarVY, apium virus Y (ApVY) and celery mosaic virus (CeMV), which occur in a range of apiaceous crops and alternative host species, have also been studied [Torilis arvensis) [Angelica spp in the NW USA [Cryptotaenia japonica in Japan and Angelica sinensis from China [Within species of the  studied ,10,12,13 studied . It also studied  and in E studied . CeMV ca studied , Latin A studied , Austral studied . In the  studied ,20. In Ervensis) ,21,22, brvensis) ,24. Othee NW USA , Japanesom China  and poisom China .Closterovirus) has been reported in hogweed (H. sphondylium) [Alfamovirus) [Chordovirus . This study also associated the root necrosis symptom with CYLV [Angelica keiskei; a hogweed-like Japanese herb) [Crinivirus) and lettuce chlorosis virus  were involved in single or mixed infections, but they were inconclusive [Reports of viruses isolated from other non-cultivated or minor apiaceous crop hosts have revealed potential cross over to other hosts. Carrot yellow leaf virus  , along wmovirus) ,18,29,30ith CYLV . Subsequse herb) ,34,35,36se herb)  was compnclusive .HTS has increasingly been used for studies of preserved historical virus samples. Sequencing plant virus isolates from historical virus isolate collections enables resolution of virus taxonomy and naming issues, and it aids dating studies. Extensive sequencing of old virus specimens avoids allocation of incorrect names to newly found viruses in metagenomic studies. With well-studied viruses, evolutionary and regional population change investigations require comparisons between old and recent isolate sequences. Historical virus collections also constitute a valuable resource enabling biosecurity investigations of virus introductions and pathways of entry and baseline surveillance. In addition, sequencing of viruses in archaeological and herbarium specimens of infected plants can also contribute to knowledge of virus evolution ,40. Apiaceae by sequencing both preserved historical and recent virus specimens from different parts of the world. A special focus of this research is on potyvirus diversity.The aim of this study was to obtain additional information about the viruses of the Potyvirus except those present in coriander sample 21506527 from Cyprus and Australian samples WA-1 and VIC-1 from celery and carrot, respectively. The additional metagenomes revealed in samples 21604167, WA-1 and VIC-1 had not been detected previously because the diagnostic tests used had been too specific to detect non-target viruses. All sequence data arising from the samples reported below are available in the NCBI short read archive BioProject PRJNA773642.The metagenomes recovered by HTS from samples of apiaceous plants are listed in −5–10−80 of the observed anomalies being random; the sequences closest to the recombinant were CaTLV sequences, MH170889 (nts 1–6199) and LT615233 . This sequence was removed from further analysis.First the alignments of the seven new genomic sequences, and 17 from the Genbank database related to them, were checked by RDP4 analysis . Only onML analysis of the ORFs from the 7 new sequences together with those of the 16 closely related potyviruses showed that they fell into two separate lineages a. Most b and addp = 0.425). By contrast, the ‘Relative Time Dated Tips (RTDT) relaxed clock algebraic method gave a sensible TMRCA of 1670 CE but with ‘two standard error’ dates of 1371 CE and 1824 CE and commensurate estimates for the principal nodes  of coriander (Coriandrum sativum) imported to the UK from Cyprus was found to contain a sequence for the potyvirus carrot thin leaf virus (accession number OM419175). However, it was also found to contain a 5654 nt contig of a Polerovirus with 94.01% similarity to beet western yellows virus isolate SDJN16 from Capsicum annum in China (accession number MK307779.1).Torradovirus). This is the first record of CaTV1 in Australia, and it represents the first record for this virus in the Southern Hemisphere. Phylogenetic trees of CaTV1 RNA 1 . The RNA 2 sequence contains an open reading frame encoding a putative 49 kDa protein with a 76% identity to the CP of MLBVV. The genome organisation shown in the RNA1,2,3 and 4 (OM419178–OM419181), the CP homology and the novel host (carrot) suggest that these sequences constitute a novel member of the genus Additionally, sample CarVY isolate VIC-1 contained RNA consisting of 2 contigs with an identity (67%/72% respectively for the two contigs) over part (34%/−49% respectively) of their length to the unclassified and undescribed red clover RNA virus 1 (accession MG596242). Translation of open reading frames of both these contigs produced putative proteins with an identity to different parts of the replicase proteins of red clover RNA virus 1  but also Dactylorhiza hatagirea beny-like virus  (accession DAF42465) and Arceuthobium sichuanense virus 3  (accession DAZ87284.1). This unclassified new RNA virus is tentatively called carrot associated RNA virus 1 and the sequences are available on GenBank for further study see .Sample 21604167, a parsley sample imported into the UK from Israel in 2016, contained sequences of a suspected novel virus. A 3086 nt contig was obtained with little nt similarity to anything available on Genbank. The sequence contained three open reading frames (OM419177). BLAST analysis of the putative proteins showed a homology to ORF1, ORF2/RdRP and ORF3 of various umbraviruses, including Teosinte-associated umbra-like virus (accession OK018180), with a 31%, 45% and 39% identity, respectively. This homology along with the inferred genome organisation and the absence of any CP-like sequences 3′ of the ORF3 suggest that this may well be the incomplete genome of a novel umbravirus tentatively called parsley umbravirus 1.Angelica lucida L. and A. genuflexa Nutt. Growing in British Colombia [Panax notoginseng, the herb ‘ginseng’, from China. All the hosts are species of the family Apiaceae, except for P. notoginseng, which is from the related family Araliaceae; together, they form the Apiales. The second largest lineage of potyvirus metagenomes we found are those of CaTLV, which forms a phylogenetic lineage with ashitabi mosaic virus (AshMV) found in ‘ashitabi’ (Angelica keiskei), a Japanese herb and a konjac virus Y (KonVY) from Chinese elephant yam . The two lineages are individually fully supported statistically but searches of the Genbank database found no virus sequences that linked them. Similar criteria indicated that poison hemlock virus Y (PHVY) isolated in Iran from Conium maculatum, another apiaceous weed, is a distinct potyvirus related most closely to lettuce mosaic virus. Thus, apiaceous plants are currently hosts to at least three distinct lineages of potyviruses, which, although originally derived from a common ancestral potyvirus, probably infected non-apiaceous plant species in an intermediate ‘life’.The metagenomes we have recovered by HTS from various samples of apiaceous plants add to knowledge of the ‘apiaceous virome’ in both breadth and depth. The largest lineage of these is of potyviruses related to CeMV, which has been described as a distinct clade . This liColombia , as wellPanax and Angelica have classic Pacific disjunct distributions that are much more ancient [Angelica lucida as “a signature plant which was central to their sealing ceremonies, and sought after as a treat” [The COs and CPs phylogenies of the CeMV lineage differ in detail, and they give no clear indication of its ‘centre of emergence’ (CoE) . The pre ancient , and the ancient  used Anga treat” ,49. ThesPolerovirus beet western yellows (BWYV) in coriander (Coriandrum sativum) and a new country record for carrot torradovirus-1 (CaTV1) in Australia recovered from a 20-year-old carrot sample. This study also reports putative novel members of the genera Umbravirus, Ophiovirus and a virus from a potentially novel genus in the family Benyviridae.Additionally, the samples tested here report a new host record for the Apiaceae [Although the host range of BWYV is broad, the detection of this virus from coriander imported into the UK from Cyprus is the first record of it in a species from the family Apiaceae ,50. DuriApiaceae  “beet weTorradovirus to be shown to be aphid transmitted, rather than whitefly transmitted [A. keiskei from Japan, although the Anglica isolate appears to be basal to this clade. Unfortunately, the complete RNA 1 sequence for the Japanese carrot isolate reported by Yoshida [Torillis isolate from Greece lineages with the two carrot isolates , and the RNA 2 of the Angelica isolate is basal to this clade rather than the German/non-carrot clade. Given there are still relatively few isolate sequences of CaTV1 available, surveillance work should be carried out to further investigate the diversity and the distribution of this emerging species. The reports highlighting the global distribution of recently described viruses, such as CaTV1, and the close relationship between minor phylogroups of these isolates  [Umbravirus petroselinum.The detection of a tentative novel member of the genus nfection b. Howeveviridae) . There aviridae) ,58,59 beviridae) . This coviridae) ,62, the viridae) , or possviridae) , as a reApiaceae virome to understand the pathological and the ecological relationships between its viruses and their respective hosts.Whilst reporting novel sequences to further elucidate the diversity of potyviruses infecting apiaceous species, this study also highlights the remaining knowledge gaps in the evolutionary history of this key group of viruses infecting such a globally important plant family, which includes crops and ecologically important uncultivated species, as mentioned in the introduction. Furthermore, the additional new host record (BWYV in Coriander), new country record  as well as three putative novel viruses further emphasises the need for a greater focus on the Preserved samples were from both historical and recent sample collections that lacked sequence data. These represented a range of apiaceous crop and herb species drawn from two sources, as detailed in Samples of fresh and previously freeze-dried infected leaf material  were subThe indexed libraries were sequenced along with others on a MiSeq (Illumina), using a 600 cycle V3 kit. The resulting paired end reads were 3′ trimmed to a quality score of 20 using Sickle in paired-end mode . ContigsTo calculate the read number and the coverage, raw reads were mapped back to the viral genomes identified using BWA-MEM2 . Subsequhttp://translatorx.co.uk (accessed on 3 March 2022)) [The Genbank nt database was searched, using its BLAST facility, for all sequences similar to those of the 7 new potyvirus genomic sequences reported in this paper  and 17 ah 2022)) , with ith 2022)) .http://tree.bio.ed.ac.uk/software/figtree/, accessed on 12 May 2018) and a commercial graphics package. The phylogenetic position of the partial GazVY CP gene sequence was determined by aligning it with the other CP gene sequences and using only the region found in all sequences for the ML analysis.The appropriate substitution model for evolutionary analysis of nt sequences was determined using MEGA-11 , and, asThe 15 COs for which collection dates were known were analysed for their ‘temporal signal’ by the linear regression method TempEst  and the


The prepared compounds were characterized with several analytical methods, including X-ray fluorescence (XRF) spectrometry, Fourier-transform infrared spectroscopy (FT-IR), electrospray ionization mass spectrometry (EIS), scanning electron microscope (SEM), X-ray diffraction (XRD), and thermogravimetric-differential thermal (TGA/DTG) analysis. The XRF technique evidenced the presence of Sb metal in the composite beads. FT-IR suggested that the interaction between pectin and the [Sb(TPP)Cl2] complex was assured by inter- and intramolecular C-H⋯O, C-H⋯Cl hydrogen bonds and weak C–H⋯Cg π interactions (Cg is the centroid of the pyrrole and phenyl rings). The morphological features of the prepared polymeric beads were affected by the addition of [Sb(TPP)Cl2] particles, and the surface became rough. The thermal residual mass for the composite beads (29%) was more important than that of plain beads (23%), which confirmed the presence of inorganic matter in the modified polymeric beads. At 20 °C, the highest adsorption amounts of methylene blue were 39 mg/g and 68 mg/g for unmodified pectin and pectin-[Sb(TPP)Cl2] beads, respectively. The adsorption mechanism correlated well with the kinetic equation of the second order and the isotherm of Freundlich. The prepared polymeric beads were characterized as moderate-to-good adsorbents. The calculated thermodynamic parameters demonstrated an exothermic and thermodynamically nonspontaneous mechanism.In this work, pectin biopolymers were functionalized with dichloride  antimony [Sb(TPP)Cl The elimination of synthetic dye molecules from contaminated water has become a global environmental worry because of the influences of contaminants on human health and ecosystems. The cationic methylene blue dye, which is water-soluble, has been stated as a main constituent of polluted water. This dye has been identified as carcinogenic and has massive toxic effects on marine organisms . To overThe proficiency of adsorption is dependent on the physicochemical properties of the used adsorbent and its reutilization ability. As a consequence, there is an important concern devoted to developing biomaterials derived from renewable sources, including cellulose, lignin, chitin, chitosan, pectin, carrageenan, etc. Indeed, the design of biopolymer-based adsorbents has attracted the attention of many researchers ,6,7. Pec2] mass, pH, time, concentration of dye, and bath temperature. The adsorption capacities were assessed and compared for plain and functionalized beads. Kinetic and isotherm studies were also carried out in an attempt to better understand the adsorption mechanism.Metallo-porphyrins are considered an interesting class of molecules, and they could be used for a wide variety of applications. They are characterized by their rigidity, great solubility in organic suspension, and photo-physical characteristics. They are also highly thermally stable. Owing to these interesting features, metallo-porphyrins have been used as catalysts in photocatalysis, opto-electronics, medicine, dye adsorption, etc. ,21,22,232) was used as a precipitant agent for the biopolymer. Methylene blue was purchased from Sigma Aldrich. The aqueous solutions were realized with distilled water.Pectin powders  were supplied by Sigma Aldrich. Calcium chloride (CaCl2] complex was prepared under an argon atmosphere following our previous work  is given in 2]: C44H28N4SbCl2 (805.1 g/mol). C, 45.32; H, 2.55; N, 4.80%. Found: C, 44.90; H, 2.65; N, 4.70%. UV/Vis : 428 (5.48), 557 (3.25), 598 (3.11). 1H-RMN : δ (ppm) = 9.66 , 8,34 ; 7,98 . MS : m/z = 805.1 [Sb(TPP)Cl2]+.The [Sb(TPP)Clous work . For thi2] particles were blended with the homogenous pectin solution, at different loading contents . Solution was vigorously stirred for 4 h. After complete homogenization, the resulting solution was pumped into droplets in a precipitation bath of CaCl2 (10% w/v) through a needle . Then, the formed beads were filtered and washed with distilled water many times. Finally, pectin-[Sb(TPP)Cl2] beads were dried under vacuum at 40 °C for 48 h. Additionally, the synthesized virgin pectin beads were used as control samples.First, 4 g of pectin polymer was dissolved in 100 mL of distilled water and stirred for 24 h at room temperature. Then, the prepared [Sb(TPP)Cl2]. An XRF spectrophotometry  was used to determine the relative abundance of metals and trace elements in the polymeric samples. An FT-IR System Perkin Elmer 2000 Model was used to identify the chemical groups present in such a sample structure. XRD patterns were carried out under the following conditions: X-ray Tube: Cu (1.54060 A) Voltage = 40.0 kV, current = 30.0 mA, scan range from 10 to 80 degrees, Thermogravimetric analysis (TGA/DTA) was carried out using a TGA 209F1D-0346-L . Experiments were realized under nitrogen flow from 25 °C to 800 °C (heating rate = 10 °C/min). The morphological features of the polymeric beads were analyzed using a Hitachi S800-1 microscope . The absorbance of methylene blue solution was measured in a quartz cell using a UV–visible spectrophotometer.MicrOTOF Q Bruker instrument  was employed to implement mass spectra of the prepared [Sb(TPP)Cl2] composite was considered using Equation (1):Adsorption experiments were carried out in conical flasks containing 0.01 g of dried polymeric beads and 20 mL of methylene blue. The dye solution was stirred continuously (125 rpm). At the completion of each experiment, each sample was filtered, and the absorbance value was recorded at the high wavelength of methylene blue dye (660 nm). The experimental parameters, including time, pH, color concentration, and temperature, were studied at different ranges. The adsorbed amount of the cationic color onto unmodified pectin beads and pectin- complex has been determined using EIS conducted in a solution of dichloromethane (C = 5 × 10−5 M) in the positive mode [2]+ moieties.The structure of  composite beads. For [Sb(TPP)Cl2] complex, the C–H stretching frequency of the TPP moiety is observed in the range 3100–2915 cm−1. The absorption band at 1594 cm−1 is assigned to the stretching ν (C=W C). Peaks located in the range 1475–1433 cm−1 belong to the C-H bending. The absorption band at 1231 cm−1 is assigned to C-N stretching. The bands ascribed to the deformation mode δ(CCH) are seen in the range 1112–910 cm−1. The absorption band located between 889 and 700 cm−1 is assigned to the ν (C–C) phenyl group [−1 that corresponds to hydroxyl stretching vibrations. The peaks at the region of 1741−1621 cm−1 are due to the vibration of COOCH3 and COO− groups. The band at 1420 cm−1 is attributed to the OH bending groups. The band in the region 1300–1000 cm−1 is attributed to the C-O-C stretching groups [2] complex assured by conventional and non-conventional interactions.yl group . The FT-g groups ,27,28. C2] composite beads at different magnifications (×100 and ×1000). As it is observed, the unmodified pectin beads display a homogenous and smooth surface. However, this surface appears rough after the addition of [Sb(TPP)Cl2] particles. Such change indicates the formation of the pectin-[Sb(TPP)Cl2] composite beads. It is also suggested that the addition of [Sb(TPP)Cl2] to pectin beads affects clearly the morphology characteristics of the beads.2] composite beads. As it is shown, the unmodified pectin beads reveal sharp peaks at 2θ that equal 13.6° θ, 20.3° θ, 30.1° θ, and 43° θ, which suggests the crystalline nature of pectin [2 particles.f pectin . However2] are presented in 2] composite beads, is equal to 71%. This weight loss is subdivided into many stages, as observed at 8%, 40%, 12%, and 11%. Indeed, compared to the unmodified beads, we notice a thermal shift for the first and second thermal events occurring at 203 °C and 524 °C, respectively. Such a difference in the thermal events proves the chemical modification of the pectin biopolymer. After thermal decomposition, the residual mass observed for the composite beads (29%) is more important than that of the unmodified beads (23%), indicating the presence of inorganic matter.The TGA/DTA curves of pectin beads and pectin-[Sb(TPP)Cl2] content, time, initial pH value, initial dye concentration, and bath temperature. 2] in the prepared polymeric beads and reaches its maximum when the content of [Sb(TPP)Cl2] reaches 1% . As a consequence, for further adsorption experiments, the removal of methylene blue will be evaluated and addressed for the unmodified pectin beads and pectin-[Sb(TPP)Cl2] (1%) composite beads. The pH of the solution can considerably influence the surface charge of both the solute and the solid studied adsorbent through either protonation or deprotonation events  (1%) composite beads.In this section, a thermodynamic study is carried out for the adsorption of methylene blue onto unmodified pectin beads and pectin-[Sb(TPP)ClThe free energy change (ΔG°) is calculated using Equations (2) and (3) :ΔG°= −−1·k−1) represents the gas constant and T (K) symbolizes the temperature.R :The slopes and intercepts of the linear plot of Ln Kd vs. (1/T) are used to deduce the values of ∆H° and ∆S° . The cal2] complex assured by conventional and nonconventional interaction. The surface features of the polymeric beads become rough after the addition of [Sb(TPP)Cl2] particles. After thermal decomposition, the residual mass observed for the composite beads (29%) is more important than that of the unmodified beads (23%), which proves the presence of inorganic matter in the modified polymeric beads. The maximum adsorption quantities of methylene blue were 39 mg/g and 68 mg/g for pectin beads and composite gel beads, respectively. The adsorption mechanism correlated well with the second-order equation (R2 ≥ 0.99), which suggests that the studied phenomenon was mainly chemical. The isotherm study revealed that multilayer adsorption might occur at heterogeneous interfaces. The prepared polymeric beads could be considered moderate-to-good adsorbents. The calculated thermodynamic parameters suggested that the adsorption of methylene blue on unmodified pectin beads and pectin-[Sb(TPP)Cl2] (1%) composite beads was nonspontaneous and exothermic. During the adsorption experiments, the disorder decreases at the interface between the solution and the adsorbent, causing a well-ordered spread of dye molecules at the active sites of adsorption.In this study, dichloride  antimony was successfully immobilized onto pectin gel beads. The prepared polymeric beads were characterized and used to remove methylene blue from an aqueous solution. The FT-IR result showed remarkable shifts observed within the main functional groups suggesting the interaction between pectin and [Sb(TPP)Cl


Varicosavirus is one of six genera of plant-infecting rhabdoviruses. Varicosaviruses have non-enveloped, flexuous, rod-shaped virions and a negative-sense, single-stranded RNA genome. A distinguishing feature of varicosaviruses, which is shared with dichorhaviruses, is a bi-segmented genome. Before 2017, a sole varicosavirus was known and characterized, and then two more varicosaviruses were identified through high-throughput sequencing in 2017 and 2018. More recently, the number of known varicosaviruses has substantially increased in concert with the extensive use of high-throughput sequencing platforms and data mining approaches. The novel varicosaviruses have revealed not only sequence diversity, but also plasticity in terms of genome architecture, including a virus with a tentatively unsegmented genome. Here, we report the discovery of 45 novel varicosavirus genomes which were identified in publicly available metatranscriptomic data. The identification, assembly, and curation of the raw Sequence Read Archive reads has resulted in 39 viral genome sequences with full-length coding regions and 6 with nearly complete coding regions. The highlights of the obtained sequences include eight varicosaviruses with unsegmented genomes, which are linked to a phylogenetic clade associated with gymnosperms. These findings have resulted in the most complete phylogeny of varicosaviruses to date and shed new light on the phylogenetic relationships and evolutionary landscape of this group of plant rhabdoviruses. Thus, the extensive use of sequence data mining for virus discovery has allowed us to unlock of the hidden genetic diversity of varicosaviruses, the largely neglected plant rhabdoviruses.The genus  A recently discovered huge number of diverse viruses has revealed the complexities of the evolutionary landscape of replicating entities and the challenges associated with their classification , leadingVaricosavirus is one of the six genera that are comprised of plant rhabdoviruses , and its members are thought to have a negative-sense, single-stranded, bi-segmented RNA genome  (accessed on 19 August 2022). The resulting viral sequence hits of each bioproject were visually explored. Tentative virus-like contigs were curated (extended or confirmed) by iteratively mapping each SRA library’s filtered reads. This strategy used BLAST/nhmmer to extract a subset of reads related to the query contig and used the retrieved reads to extend the contig and then repeated the process iteratively using the extended sequence as query. The extended and polished transcripts were reassembled using the Geneious v8.1.9  alignment tool with high sensitivity parameters. Bowtie2, available at http://bowtie-bio.sourceforge.net/bowtie2/index.shtml (accessed on 26 September 2022), was used with standard parameters for filtered read mapping to calculate the mean coverage of each assembled virus sequence.The nucleotide (nt) raw sequence reads from each SRA experiment, which are associated with different NCBI bioprojects , were dohttps://www.ncbi.nlm.nih.gov/orffinder/, accessed on 22 August 2022) and the functional domains and architectures of translated gene products were determined using InterPro  and the NCBI conserved domain database-CDD v3.19 . Further, HHPred and HHBlits, as implemented in https://toolkit.tuebingen.mpg.de/#/tools/ (accessed on 22 August 2022), were used to complement the annotation of divergent predicted proteins by hidden Markov models. Transmembrane domains were predicted using the TMHMM version 2.0 tool .ORFs were predicted with ORFfinder  sequence identities of the L protein of those varicosaviruses identified in this study, as well as those available in the NCBI database, were calculated using SDTv1.2 . Virus nhttps://mafft.cbrc.jp/alignment/software) (accessed on 25 August 2022) with multiple aa sequence alignments and using FFT-NS-i as the best-fit model. The aligned aa sequences were used as inputs to generate phylogenetic trees using the maximum-likelihood method (best-fit model = E-INS-i) with the FastTree 2.1.11 tool (available at http://www.microbesonline.org/fasttree/) (accessed on 25 August 2022). Local support values were calculated with the Shimodaira-Hasegawa test (SH) and 1000 trees were resampled. The L proteins of four selected cytorhabdoviruses were used as outgroups. To explore the potential phylogenetic co-divergence of varicosaviruses with their associated host plants, plant host cladograms were generated in phyloT v.2  based on NCBI Taxonomy. Connections were manually inferred between the viral and plant phylograms and cladograms and visually inspected.Phylogenetic analysis based on the predicted polymerase protein of all available varicosaviruses was completed using MAFFT 7.505  has an additional ORF 5’ to the L gene, supported by the identification of the conserved intergenic sequence (see below), encoding a 171 aa putative protein , which a5UUUUUGCUCU 5′ (5 instead of AU(N)5 (The consensus gene junction sequences of the bisegmented varicosaviruses were determined to be 3′ AU(N)GCUCU 5′ , while tf AU(N)5 . StrikinThere is a great dearth of data on the potential functions of putative proteins, other than N and L, encoded by varicosaviruses, and, intriguingly, there were no conserved domains identified in these proteins. We grasped some shared identities, primarily for the cognate P3  , though The pairwise aa sequence identities between the L proteins of all the reported varicosaviruses, including those identified in this study, showed great diversity and an overall low identity between the different varicosaviruses . RelativVaricosavirus genus, a taxonomic criterion which had previously not been fully defined [Varicosavirus species, which would increase the number of members of the genus by more than an order of magnitude.When we analyzed the diversity between the variants of viruses which are likely members of the same species, we found that proteins encoded by the Brassica virus 2, Spinach virus 1, and Sciadopitys virus 1 variants were very similar. On the other hand, proteins encoded by the Brassica virus 1, Lolium virus 1, and Melilotus virus 1 variants were quite diverse, but, nevertheless, they showed aa identities for the N and L proteins exceeding 80%. Thus, we tentatively propose an aa sequence identity of 80% across the L gene as the threshold for species demarcation in the  defined . This thPinus flexilis. In this study, we complemented that result by the discovery of eight additional unsegmented varicosaviruses which were exclusively associated with gymnosperms . Furthermore, unexpectedly, the best hit of the putative P5 protein encoded on ASaV2 RNA2 was a fragment of the PiFleV1 L protein, while the deduced L protein on ASaV2 RN1 was not a best hit with PiFleV1, but instead, with the non-gymnosperm-linked MelRoV1 hosted by the Orobanchaceae parasitic plant Melampyrum roseum. Thus, we suspected that ASaV2 was potentially misassembled from fragments belonging to two different viruses. Consequently, we re-analyzed the original SRA data used by Sidhartan et al. [Interestingly, in the BlastP analyses of N, P2, and P3 of the gymnosperm-associated viruses, most of them had, as a best hit to the cognate proteins encoded by the putative bisegmented ASaV2 , a virusn et al.  and wereThe phylogenetic analysis based on the deduced L protein aa sequences placed all unsegmented varicosaviruses, except TorV1, into a distinct clade. Interestingly, TorV1 was placed in a clade that was basal to all varicosaviruses . This diWe generated a tanglegram to compare the virus phylogram and plant host cladogram to further explore virus–host relationships . This anSeveral lines of evidence suggest that varicosaviruses may be vertically transmitted: (i) a close host–virus co-evolution in some clades may reflect species isolation and a lack of horizontal transmission, (ii) some viruses detected in this study were identified from seed transcriptomics databases, and (iii) an emerging characteristic of persistent, chronic infections of several plant viruses which are likely vertically transmitted are latent/asymptomatic infections, a characteristic which appears to be shared with varicosaviruses. Thus, further studies should be carried out to elucidate the transmission mode of varicosaviruses beyond the fungal-transmitted LBVaV . It is wWelwitschia mirabilis [Rhabdoviridae, subfamily Betarhabdovirinae, for which we suggest the name “Gymnorhavirus”.Before the era of data-driven virus discovery, few viruses had been identified in gymnosperms ,62,63,64irabilis . Eight uirabilis . Taken tIn summary, this study highlights the importance of the analysis of SRA public data as a valuable tool not only to accelerate the discovery of novel viruses, but also to gain insight into their evolution and to refine virus taxonomy. Using this approach, we looked for hidden varicosa-like virus sequences to unlock the veiled diversity of a largely neglected plant rhabdovirus genus, the varicosaviruses. Our findings, including an approximately 3.5-fold expansion of the current genomic diversity within the genus, resulted in the most complete phylogeny of varicosaviruses to date, and they shed new light on the genomic architecture, phylogenetic relationships, and evolutionary landscape of this unique group of plant rhabdoviruses. Future studies should assess many intriguing aspects of the biology and ecology of these viruses such as potential symptoms, vertical transmission, and putative vectors.


The economic impact after the outbreak of porcine reproductive and respiratory syndrome (PRRS) has been proven to be tremendous for pig production worldwide. However, the economic impact of the disease is not well understood in China. In our previous study, we acquired and analyzed the main production data  from the management system before and after the PRRS outbreaks occurring in November 2014, March 2015, December 2016, and February 2017. This study aimed to analyze and quantify the economic losses of the four PRRS outbreaks in Chinese herds. A straightforward approach was used to calculate additional costs and decreased revenues based on the PRRS-induced production deficiencies by average cost-of-production indices calculated from annual estimates of costs between 2014 and 2017. The results showed that economic losses varied between ¥668.14 and ¥1004.43 per sow in breeding herds from the outbreaks to regain the basic performance, with an average of ¥822.75 per sow, and the mean costs in the fattening herds (including nursery pigs) were ¥601.62 per sow, ranging from ¥318.64 to ¥937.14. Overall, the economic impact of PRRS on the whole herd was ¥1424.37 per sow. The majority of the losses were due to the reduction in the number of weaned piglets for breeding herds, and the increased feed cost (occupying 44.88%) was the primary source of loss for fattening herds. Our study fills the gap in knowledge of PRRS economics in China, enriches the data for veterinary economics, and re-stresses the necessity for producers and veterinarians to control PRRS effectively. Betaarterivirus of the family Arteriviridae in the order Nidovirales, consisting of two species, PRRSV 1 (European) and PRRSV 2 (North American) based on the identity at the nucleotide level  (Porcine reproductive and respiratory syndrome virus (PRRSV) is an enveloped positive-strand RNA virus and the causative agent of PRRS, which was first identified in Europe in 1991 and the United States in 1992  . The clis, ICTV) –6. In ads, ICTV) , 8. A los, ICTV) . At the s, ICTV) . A Dutchs, ICTV) . A Spanis, ICTV) .More than two decades have passed since the first PRRS report in the 1990s, accompanied by several epidemics due to the broad variation and rapid evolution of PRRSV in China , 13. Esphttp://www.boyar.cn/. Co-infection with bacteria can exacerbate PRRS-associated disease, but these data were difficult to accurately collect, and costs were difficult to apportion among multiple infectious agents, so the multiple secondary infectious diseases, such as Haemophilus parasuis and Streptococcus suis, that impacted production for the fattening herds were excluded from the study.The methodology of our analysis is a relatively simple and direct approach modified from the economic model used by Nieuwenhuis et al. , which wThree breeding farms  with the sale of piglets at weaning and one farrow-to-finish farm (D) from a large-scale swine company were selected to participate in this study, with the average number of sows of 5,000, 2,450, 3,800, and 1,750. The PRRS outbreak occurred in four breeding herds in November 2014, March 2015, December 2016, and February 2017, respectively, based on clinical signs discovered by veterinarians and diagnosis and confirmed by laboratory tests, with PCR negative results for classical swine fever virus (CSFV), pseudorabies virus (PRV), and porcine circovirus 2 (PCV2) in the detected samples. Four different PRRSV strains, SDwh1403 (a recombinant betweenNADC30-like and MLV), SDqd1501 (a recombinant between HP-PRRSV-like and QYYZ), SDwh1601 (a recombinant between JXA1-P80 (a MLV derived from HP-PRRSV and NADC30-like), and SDwh1701 (a strain evolved from JXA1-P80) were isolated . All fouThe main production data was acquired from the management system, 6 months before the PRRS outbreak to the basic production performance after the outbreak, to analyze the specific production parameters. Then, the calculation of economic losses was applied independently for breeding and fattening herds based on the specific comparative production metrics affected by PRRS. Representative costs derived from the average market prices reported during the period from 2014 to 2017 were generated to reflect typical historical costs in the industry. Variable cost standards in this study included ¥4,000/sow, ¥1,637/gilt, ¥380/weaned pig, ¥15.65/kg (marketed pigs), ¥3.217/kg of feed for sows, ¥2.928/kg of feed for gilts, ¥3.693/kg of feed for nursery pigs, and ¥2.752/kg of feed for grower-finisher pigs. The average cost of feed from wean to finish was ¥2.874/kg (about 35kg feed for nursery pigs and 235kg feed for finisher pigs) . The fixThe economic losses of breeding herds mainly consist of (1) the increased vaccine and medication costs (including pre-weaning piglets); (2) the decreased numbers of weaned piglets * ¥380/weaned pig; (3) the increased numbers of eliminated sows * ¥4,000/sow; and (4) the increased numbers of replaced gilts * ¥1,637/gilt. The water, electricity, and increased labor costs were assumed not to be affected by PRRS in breeding herds and were not calculated in this analysis. The costs due to the low quality of weaned piglets (positive for qRT-PCR) were analyzed in fattening herds.The economic losses of fattening herds mainly consisted of (1) increased vaccine and medication costs; (2) increased labor costs attributable to the delay to market ; (3) increased feed costs; (4) increased costs attributable to the increased mortality and cull rate [including labor costs (¥80/pig) and weaned-pig prices (¥380/pig)].The economic losses of fattening herds = the marketed pigs * + * ¥460.The four breeding herds took 20, 13, 18, and 17 weeks, respectively, to regain basic production performance, with a reduction in the number of weaned piglets and an increase in health costs. The average number of weaned piglets (per week) of herds A, B, C, and D in the 6 months before the PRRS outbreak was 2,166, 1,157, 1,815, and 868, and decreased to 1,933, 954, 1,487, and 723 after the outbreak, respectively. This represented a reduction of 4,660, 2,639, 5,904, and 2,465 pigs when they come back to the basic production performance, leading to 1.77, 1.00, 2.24, and 0.94 million losses based on the value of ¥380/weaned pig. For sows, it was estimated that 64, 39, 97, and 53 pigs were additionally culled than before, and an extra 158, 44, 159, and 92 gilts were introduced for replacement, which yielded losses of 0.52, 0.23, 0.65, and 0.36 million for the four herds, respectively. Furthermore, the increased vaccine and medicine costs  were also calculated for sows and piglets. Overall, the total losses in the four breeding herds were estimated to be ¥3.34, ¥1.65, ¥3.82, and ¥1.66 million, equal to an average of ¥822.75 per sow, ranging from ¥668.14 to ¥1004.43. The majority of the losses (56.92%) in the breeding herds were due to the reduction in revenue caused by decreased weaned piglets, and secondary losses were health costs with a proportion of 26.32%. The analyses of these parameters and losses are summarized in The economic impact of PRRS on fattening herds was calculated  and mainTaken together, as shown in With few exceptions, PRRS has been considered to impose substantial economic losses, and PRRS economic studies have been conducted in the last century . SeveralAmong the four outbreaks, the calculated economic effect of the PRRS outbreak was ¥1424.37 per sow ¥1049.78–¥1609.70) from breeding to fattening, higher losses than the estimates of previous studies in other countries –¥1609.70. HoweverAs mentioned previously, there was no gold standard to determine the economic losses attributable to the PRRS outbreak. An obvious limitation of this study was the exclusion of co-infected and secondary diseases impacting production, especially the potential porcine circovirus type 2 (PCV2) subclinical infection . The PCROur current study provides an exploration for evaluating the economic impact of PRRS in China. More analyses from different production systems or enterprises, at the herd level, and even at the national level, should be conducted for profitable intervention strategies and warranting economic input decisions in the future.The original contributions presented in the study are included in the article/Ethical review and approval was not required for the study of animals in accordance with the local legislation and institutional requirements. Written informed consent from owners of the animals was not required to participate in this study in accordance with the national legislation and the institutional requirements.ZZ and XQ interpreted the data and drafted the work. XQ co-ordinated the study. ZL, SY, and FR acquired the data from the management system used in the farms. TB, LS, and HL analyzed the data. BZ and LZ provided advice for the research analysis. All authors read and approved the final manuscript.This work was supported by the Natural Science Foundation of Jiangsu Province (BK20201005) and Nanjing Dr. Vet Health Management Co., Ltd.Authors ZL, SY, FR, and XQ were employed by the company Nanjing Dr. Vet Health Management Co., Ltd. The authors declare that this study received funding from Nanjing Dr. Vet Health Management Co., Ltd. The funder had the following involvement in the study: collection, analysis, and the decision to submit it for publication.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.