Variations in epidemic distribution with some characteristic parameters

Considering the spread of an epidemic among a population of mobile agents that can get infected and maintain the infection for a period, we investigate the variation in the homogeneity of the distribution of the epidemic with the remaining time of infection τ, the velocity modulus of the agent v, and the infection rate α. We find that the distribution of the infected cluster size is always exponential. By analyzing the variation of the characteristic infected cluster size coefficient, we show that the inhomogeneity of epidemic distribution increases with an increase in τ for very low v, while it decreases with an increase in τ for moderate v. The epidemic distribution also tends to a homogeneous state as both v and α increase.     

Optical detection of wound infection in vivo by near infrared diffuse reflectance spectroscopy

Detection of bacterial infection is important for deciding optimal treatment and management for wound. In the paper, near infrared diffuse reflectance spectroscopy is proposed for detection wound infection in vivo with optical properties. A porcine model is used as experimental subject in the detection of wound infection. The spectrally resolved data of the wounds are analyzed to extract the optical properties including reduced scattering coefficient and absorption coefficient. Based on optical properties, an ensemble model of chain-like agent genetic optimized Support Vector Machine is applied to discriminate wound infection. The experimental results demonstrate the feasibility and effectiveness of the method for rapid and noninvasive detection of wound infection using optical properties.     

A Transnational and Transregional Study of the Impact and Effectiveness of Social Distancing for COVID-19 Mitigation

We present an analysis of the relationship between SARS-CoV-2 infection rates and a social distancing metric from data for all the states and most populous cities in the United States and Brazil, all the 22 European Economic Community countries and the United Kingdom. We discuss why the infection rate, instead of the effective reproduction number or growth rate of cases, is a proper choice to perform this analysis when considering a wide span of time. We obtain a strong Spearman’s rank order correlation between the social distancing metric and the infection rate in each locality. We show that mask mandates increase the values of Spearman’s correlation in the United States, where a mandate was adopted. We also obtain an explicit numerical relation between the infection rate and the social distancing metric defined in the present work.     

Infants' monaural localization of sounds: effects of unilateral ear infection

The aim in this study was to examine the impact of unilateral ear infection (i.e., otitis media with effusion) on infants' localization of sounds in the horizontal place. Twenty eight infants 6 to 18 months of age were tested at the time of an ear infection, as well as 2 weeks later. Sound localization was measured using a two-alternative forced-choice procedure to examine infants' abilities to discriminate a sound shift of 8 degrees, 12 degrees, 16 degrees, and 20 degrees off midline and along the horizontal axis, either ipsilateral or contralateral to the infected ear. A head and/or eye movement in the direction of the sound was designated as a correct response and was visually reinforced. Results revealed significant negative effects of unilateral ear infection on sound localization performance. All infants showed more correct localization responses for sounds shifted ipsilateral to the problem ear 2 weeks following their ear infection than at the time of the infection. Localization of sounds shifted contralateral to the infected ear did not vary with test date, and significantly exceeded ipsilateral performance when tested at the time of an ear infection. Results are consistent with adult data which indicates that, with unilateral hearing loss, a sound ipsilateral to the problem ear is displaced in location along the horizontal axis toward the well-functioning ear. These findings indicate the importance of balanced binaural functioning for horizontal localization and highlight the plasticity of the developing human auditory system.     

Interactions of multiple strain pathogen diseases in the presence of coinfection, cross immunity, and arbitrary strain diversity

A model for coinfection in multiple strain infectious diseases is developed to incorporate coinfection statuses, immune and infection history, and cross immunity. It is solved for the symmetric interior equilibrium through the use of a ladder operator formalism inspired by quantum mechanical methods. We find that coinfection can fundamentally affects transmission dynamics with important epidemiologic and evolutionary consequences. It can significantly shift the distribution of age at infection for highly antigenically diverse pathogens so that in small host populations, an evolutionary strategy maximizing individual strain transmissibility might be less optimal than one which maximizes the total prevalence of all strains in the system. Alternatively, mechanisms which inhibit coinfection and thus increase total infection prevalence may be evolutionarily advantageous.     

Small world effect in an epidemiological model

A model for the spread of an infection is analyzed for different population structures. The interactions within the population are described by small world networks, ranging from ordered lattices to random graphs. For the more ordered systems, there is a fluctuating endemic state of low infection. At a finite value of the disorder of the network, we find a transition to self-sustained oscillations in the size of the infected subpopulation.     

Sexually transmitted infections and the marriage problem

We study an SIS epidemiological model for a sexually transmitted infection in a monogamous population where the formation and breaking of couples is governed by individual preferences. The mechanism of couple recombination is based on the so-called bar dynamics for the marriage problem. We compare the results with those of random recombination – where no individual preferences exist – for which we calculate analytically the infection incidence and the endemic threshold. We find that individual preferences give rise to a large dispersion in the average duration of different couples, causing substantial changes in the incidence of the infection and in the endemic threshold. Our analysis yields also new results on the bar dynamics, that may be of interest beyond the field of epidemiological models.     

A mathematical model for transmission dynamics of HIV/AIDS with effect of weak CD4+ T cells

A mathematical model is proposed for the dynamics of HIV/AIDS with incorporation of weak CD4⁺ T cells. The model considers three different categories of cells: uninfected CD4⁺ T cells, infected CD4⁺ T cells, and virus. The anticipated model helps to illustrate the many of mystifying features of HIV infection more clearly. This model demonstrates two steady states: an infection-free equilibrium state, in which there is no virus, and an infection equilibrium state, in which virus and infected T cells are present. We have also calculated the local stability of the infection-free equilibrium and infection equilibrium for the model when the valuable reproduction number is less than and greater than one. With the help of Lyapunov's second method and the geometric approach, we are defining the novel conditions for the global stability of infection-free equilibrium state and infection equilibrium state. This study, which knocks off-balance the system, is articulated by a small variation of the parameters conceded by the system from one stable state to an unstable state. The dynamics of this new steady state are calculated both numerically and via the stability analysis.     

Effects of disease characteristics and population distribution on dynamics of epidemic spreading among residential sites

We investigate the spreading processes of epidemic diseases among many residential sites for different disease characteristics and different population distributions by constructing and solving a set of integrodifferential equations for the evolutions of position-dependent infected and infective rates, taking into account the infection processes both within a single site and among different sites. In a spreading process the states of an individual include susceptible (S), incubative (I), active (A) and recovered (R) states. Although the transition from S to I mainly depends on the active rate, the susceptible rate and the connectivity among individuals, the transitions from I to A and from A to R are determined by intrinsic characteristics of disease development in individuals. We adopt incubation and infection periods to describe the intrinsic features of the disease. By numerically solving the equations we find that the asymptotic behavior of the spreading crucially depends on the infection period and the population under affection of an active individual. Other factors, such as the structure of network and the popular distribution, play less important roles. The study may provide useful information for analyzing the key parameters affecting the dynamics and the asymptotic behavior.     

Struggle for space: viral extinction through competition for cells

The design of protocols to suppress the propagation of viral infections is an enduring enterprise, especially hindered by limited knowledge of the mechanisms leading to viral extinction. Here we report on infection extinction due to intraspecific competition to infect susceptible hosts. Beneficial mutations increase the production of viral progeny, while the host cell may develop defenses against infection. For an unlimited number of host cells, a feedback runaway coevolution between host resistance and progeny production occurs. However, physical space limits the advantage that the virus obtains from increasing offspring numbers; thus, infection clearance may result from an increase in host defenses beyond a finite threshold. Our results might be relevant to devise improved control strategies in environments with mobility constraints or different geometrical properties.     

Integrated systemic inflammatory response syndrome epidemic model in scale-free networks

Based on the scale-free network, an integrated systemic inflammatory response syndrome model with artificial immunity, a feedback mechanism, crowd density and the moving activities of an individual can be built. The effects of these factors on the spreading process are investigated through the model. The research results show that the artificial immunity can reduce the stable infection ratio and enhance the spreading threshold of the system. The feedback mechanism can only reduce the stable infection ratio of system, but cannot affect the spreading threshold of the system. The bigger the crowd density is, the higher the infection ratio of the system is and the smaller the spreading threshold is. In addition, the simulations show that the individual movement can enhance the stable infection ratio of the system only under the condition that the spreading rate is high, however, individual movement will reduce the stable infection ratio of the system.     

Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell–cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.     

The fastest spreader in SIS epidemics on networks

Identifying the fastest spreaders in epidemics on a network helps to ensure an efficient spreading. By ranking the average spreading time for different spreaders, we show that the fastest spreader may change with the effective infection rate of a SIS epidemic process, which means that the time-dependent influence of a node is usually strongly coupled to the dynamic process and the underlying network. With increasing effective infection rate, we illustrate that the fastest spreader changes from the node with the largest degree to the node with the shortest flooding time. (The flooding time is the minimum time needed to reach all other nodes if the process is reduced to a flooding process.) Furthermore, by taking the local topology around the spreader and the average flooding time into account, we propose the spreading efficiency as a metric to quantify the efficiency of a spreader and identify the fastest spreader, which is adaptive to different infection rates in general networks.     

Recurrent host mobility in spatial epidemics: beyond reaction-diffusion

Human mobility is a key factor in spatial disease dynamics and related phenomena. In computational models host mobility is typically modeled by diffusion in space or on metapolulation networks. Alternatively, an effective force of infection across distance has been introduced to capture spatial dispersal implicitly. Both approaches do not account for important aspects of natural human mobility, diffusion does not capture the high degree of predictability in natural human mobility patters, e.g. the high percentage of return movements to individuals’ base location, the effective force of infection approach assumes immediate equilibrium with respect to dispersal. These conditions are typically not met in natural scenarios. We investigate an epidemiological model that explicitly captures natural individual mobility patterns. We systematically investigate generic dynamical features of the model on regular lattices as well as metapopulation networks and show that generally the model exhibits significant dynamical differences in comparison to ordinary diffusion and effective force of infection models. For instance, the natural human mobility model exhibits a saturation of wave front speeds and a novel type of invasion threshold that is a function of the return rate in mobility patterns. In the light of these new findings and with the availability of precise and pervasive data on human mobility our approach provides a framework for a more sophisticated modeling of spatial disease dynamics.     

Risks of an epidemic in a two-layered railway-local area traveling network

In view of the huge investments into the construction of high speed rails systems in USA, Japan, and China, we present a two-layer traveling network model to study the risks that the railway network poses in case of an epidemic outbreak. The model consists of two layers with one layer representing the railway network and the other representing the local-area transportation subnetworks. To reveal the underlying mechanism, we also study a simplified model that focuses on how a major railway affects an epidemic. We assume that the individuals, when they travel, take on the shortest path to the destination and become non-travelers upon arrival. When an infection process co-evolves with the traveling dynamics, the railway serves to gather a crowd, transmit the disease, and spread infected agents to local area subnetworks. The railway leads to a faster initial increase in infected agents and a higher steady state infection, and thus poses risks; and frequent traveling leads to a more severe infection. These features revealed in simulations are in agreement with analytic results of a simplified version of the model.     

The impact of human activity patterns on asymptomatic infectious processes in complex networks

The study of the impact of human activity patterns on network dynamics has attracted a lot of attention in recent years. However, individuals’ knowledge of their own physical states has rarely been incorporated into modeling processes. In real life, for certain infectious processes, infected agents may not have any visible or physical signs and symptoms; therefore, they may believe that they are uninfected even when they have been infected asymptomatically. This infection awareness factor is covered neither in the classical epidemic models such as SIS nor in network propagation studies. In this article, we propose a novel infectious process model that differentiates between the infection awareness states and the physical states of individuals and extend the SIS model to deal with both asymptomatic infection characteristics and human activity patterns. With regards to the latter, we focus particularly on individuals’ testing action, which is to determine whether an individual is infected by an epidemic. The simulation results show that less effort is required in controlling the disease when the transmission probability is either very small or large enough and that Poisson activity patterns are more effective than heavy-tailed patterns in controlling and eliminating asymptomatic infectious diseases due to the long-tail characteristic.     

Epidemiological impact of waning immunization on a vaccinated population

This is an epidemiological SIRV model based study that is designed to analyze the impact of vaccination in containing infection spread, in a 4-tiered population compartment comprised of susceptible, infected, recovered and vaccinated agents. While many models assume a lifelong protection through vaccination, we focus on the impact of waning immunization due to conversion of vaccinated and recovered agents back to susceptible ones. Two asymptotic states exist, the “disease-free equilibrium” and the “endemic equilibrium” and we express the transitions between these states as function of the vaccination and conversion rates and using the basic reproduction number. We find that the vaccination of newborns and adults have different consequences on controlling an epidemic. Also, a decaying disease protection within the recovered sub-population is not sufficient to trigger an epidemic at the linear level. We perform simulations for a parameter set mimicking a disease with waning immunization like pertussis. For a diffusively coupled population, a transition to the endemic state can proceed via the propagation of a traveling infection wave, described successfully within a Fisher-Kolmogorov framework.     

Martensitic phase transition from cubic to tetragonal V<Subscript>3</Subscript>Si: an electronic structure study

We analyze the epidemic spread via a contact infection process in an immobile population within the Susceptible-Infected-Removed (SIR) model. We present both the results of stochastic simulations assuming different numbers of individuals (degrees of freedom) per cell as well as the solution of the corresponding deterministic equations. For the last ones we show that the appropriate system of nonlinear partial differential equations (PDE) allows for a complete separation of variables and present the approximate analytical expressions for the infection wave in different ranges of parameters. Comparing these results with the direct Monte-Carlo simulations we discuss the domain of applicability of the PDE models and their restrictions.     

Looking inside phytoplasma-infected sieve elements: A combined microscopy approach using Arabidopsis thaliana as a model plant

Phytoplasmas are phloem-inhabiting plant pathogens that affect over one thousand plant species, representing a severe threat to agriculture. The absence of an effective curative strategy and the economic importance of many affected crops make a priority of studying how plants respond to phytoplasma infection. Nevertheless, the study of phytoplasmas has been hindered by the extreme difficulty of culturing them in vitro and by impediments to natural host plant surveys such as low phytoplasma titre, long plant life cycle and poor knowledge of natural host-plant biology. Stating correspondence between macroscopic symptoms of phytoplasma infected Arabidopsis thaliana and those observed in natural host plants, over the last decade some authors have started to use this plant as a model for studying phytoplasma-plant interactions. Nevertheless, the morphological and ultrastructural modifications occurring in A. thaliana tissues following phytoplasma infection have never been described in detail. In this work, we adopted a combined-microscopy approach to verify if A. thaliana can be considered a reliable model for the study of phytoplasma-plant interactions at the microscopical level.The consistent presence of phytoplasma in infected phloem allowed detailed study of the infection process and the relationship established by phytoplasmas with different components of the sieve elements. In infected A. thaliana, phytoplasmas induced strong disturbances of host plant development that were mainly due to phloem disorganization and impairment. Light microscopy showed collapse, necrosis and hyperplasia of phloem cells. TEM observations of sieve elements identified two common plant-responses to phytoplasma infection: phloem protein agglutination and callose deposition.     

感染减毒鼠伤寒沙门氏菌对小鼠粪样代谢组的影响——WIPM和Bruker 500 MHz核磁共振波谱仪检测结果的比较

鼠伤寒沙门氏菌属于胞内侵袭性兼性厌氧菌,减毒后的鼠伤寒沙门氏菌安全性大大提高,已被广泛用于病毒、细菌及寄生虫疫苗的研制.但是目前还没有研究利用代谢组学方法来分析减毒鼠伤寒沙门氏菌感染对宿主和肠道菌群相互作用的影响.同时中国科学院武汉物理与数学研究所自主研发的WIPM 500 MHz核磁共振(NMR)波谱仪已经研制成功,但是该谱仪是否可以用于代谢组学研究尚未经过考证.本研究同时使用WIPM和Bruker500 MHz核磁共振波谱仪对同一批减毒鼠伤寒沙门氏菌感染小鼠的粪样进行检测,并结合多变量数据分析方法来研究减毒鼠伤寒沙门氏菌感染对小鼠粪样代谢组的影响.研究结果表明,WIPM NMR波谱仪检测数据的分析结果与Bruker NMR波谱仪的实验结果具有高度的一致性,表明WIPM谱仪可以用于代谢组学研究.研究发现减毒鼠伤寒沙门氏菌感染能够引起小鼠粪样代谢物中多种氨基酸和尿嘧啶含量的上升,并伴有胆汁酸、乳酸和丙酸含量的下降.以上代谢物含量的改变表明,减毒鼠伤寒沙门氏菌感染使小鼠肠道微生物的代谢功能发生了紊乱.