Prediction of ILI following the COVID-19 pandemic in China by using a partial differential equation

The COVID-19 outbreak has significantly disrupted the lives of individuals worldwide.Following the lifting of COVID-19 interventions,there is a heightened risk of future outbreaks from other circulating respiratory infections,such as influenza-like illness(ILI).Accurate prediction models for ILI cases are crucial in enabling governments to implement necessary measures and persuade individuals to adopt personal precautions against the disease.This paper aims to provide a forecasting model for ILI cases with actual cases.We propose a specific model utilizing the partial differential equation(PDE)that will be developed and validated using real-world data obtained from the Chinese National Influenza Center.Our model combines the effects of transboundary spread among regions in China mainland and human activities’impact on ILI transmission dynamics.The simulated results demonstrate that our model achieves excellent predictive performance.Additionally,relevant factors influencing the dissemination are further examined in our analysis.Furthermore,we investigate the effectiveness of travel restrictions on ILI cases.Results can be used to utilize to mitigate the spread of disease.

ReTweeting Analysis and Prediction in Microblogs: An Epidemic Inspired Approach

Microblogs currently play an important role in social communication. Hot topics currently being tweeted can quickly become popular within a very short time as a result of retweeting. Gaining an understanding of the retweeting behavior is desirable for a number of tasks such as topic detection, personalized message recommendation, and fake information monitoring and prevention. Interestingly, the propagation of tweets bears some similarity to the spread of infectious diseases. We present a method to model the tweets' spread behavior in microblogs based on the classic Susceptible-Infectious-Susceptible (SIS) epidemic model that was developed in the medical field for the spread of infectious diseases. On the basis of this model, future retweeting trends can be predicted. Our experiments on data obtained from the Chinese micro-blogging website Sina Weibo show that the proposed model has lower predictive error compared to the four commonly used prediction methods.

ANALYSIS OF AN SI EPIDEMIC MODEL WITH NONLINEAR TRANSMISSION AND STAGE STRUCTURE

A disease transmission model of SI type with stage structure is formulated. The stability of disease free equilibrium, the existence and uniqueness of an endemic equilibrium, the existence of a global attractor are investigated.

Dynamic properties of epidemic spreading on finite size complex networks

The Internet presents a complex topological structure, on which computer viruses can easily spread. By using theoretical analysis and computer simulation methods, the dynamic process of disease spreading on finite size networks with complex topological structure is investigated. On the finite size networks, the spreading process of SIS （susceptibleinfected-susceptible） model is a finite Markov chain with an absorbing state. Two parameters, the survival probability and the conditional infecting probability, are introduced to describe the dynamic properties of disease spreading on finite size networks. Our results can help understanding computer virus epidemics and other spreading phenomena on communication and social networks. Also, knowledge about the dynamic character of virus spreading is helpful for adopting immunity policy.

Analysis of an Epidemic Model with Age of Vaccination

A simple SI epidemic model with age of vaccination is discussed in this paper.Both vexing birth rate, the mortality rate caused by disease and vaccine waning rate areconsidered in this model. We prove that the global dynamics is completely determined bythe basic reproductive number R（ψ）（ψ denotes per capita vaccination rate）. If R（0） 〈 1,the disease-free equilibrium is a global attractor; If R（ψ） 〈： 1, the disease-free equilibriumis locally asymptotically stable; If R（ψ） ：〉 1, an unique endemic equilibrium exists and islocally asymptotically stable under certain condition.

ANALYSIS OF AN SIS EPIDEMIOLOGIC MODEL WITH VARIABLE POPULATION SIZE AND A DELAY

Epidemiologic model of SIS type has a delay corresponding to the infectious period and disease related deaths,so that the population size is variable.The population dynamics structure is recruitment and natural births with natural deaths.The incidence term is of the standard incidence.Here the thresholds and equilibria are detemined,and stabilities are examined.The persistence of the infectious disease and disease related deaths can lead to a new equilibrium population size below the carrying capacity.

COEXISTENCE FOR MULTIPLE LARGEST REPRODUCTION RATIOS OF A MULTI-STRAIN SIS EPIDEMIC MODEL

In this paper, to complete the global dynamics of a multi-strains SIS epidemic model, we establish a precise result on coexistence for the cases of the partial and complete duplicated multiple largest reproduction ratios for this model.

Equilibrium and kinetic Si isotope fractionation factors and their implications for Si isotope distributions in the Earth's surface environments

Several important equilibrium Si isotope fractionation factors among minerals,organic molecules and the H_4SiO_4 solution are complemented to facilitate the explanation of the distributions of Si isotopes in Earth's surface environments.The results reveal that,in comparison to aqueous H_4SiO_4,heavy Si isotopes will be significantly enriched in secondary silicate minerals.On the contrary,quadra-coordinated organosilicon complexes are enriched in light silicon isotope relative to the solution.The extent of ^(28)Si-enrichment in hyper-coordinated organosilicon complexes was found to be the largest.In addition,the large kinetic isotope effect associated with the polymerization of monosilicic acid and dimer was calculated,and the results support the previous statement that highly ^(28)Sienrichment in the formation of amorphous quartz precursor contributes to the discrepancy between theoretical calculations and field observations.With the equilibrium Si isotope fractionation factors provided here,Si isotope distributions in many of Earth's surface systems can be explained.For example,the change of bulk soil δ^(30)Si can be predicted as a concave pattern with respect to the weathering degree,with the minimum value where allophane completely dissolves and the total amount of sesquioxides and poorly crystalline minerals reaches their maximum.When,under equilibrium conditions,the well-crystallized clays start to precipitate from the pore solutions,the bulk soil δ^(30)Si will increase again and reach a constant value.Similarly,the precipitation of crystalline smectite and the dissolution of poorly crystalline kaolinite may explain the δ^(30)Si variations in the ground water profile.The equilibrium Si isotope fractionations among the quadracoordinated organosilicon complexes and the H_4SiO_4solution may also shed light on the Si isotope distributions in the Si-accumulating plants.

An SIS epidemic model with diffusion

The aim of this paper is to study the diffusion. We first study the well-posedness of the dynamics of an SIS epidemic model with model. And then, by using linearization method and constructing suitable Lyapunov function, we establish the local and global stability of the disease-free equilibrium and the endemic equilibrium, respectively. Furthermore, in view of Schauder fixed point theorem, we show that the model admits traveling wave solutions con- necting the disease-free equilibrium and the endemic equilibrium when R0 〉 1 and c 〉 c^＊. And also, by virtue of the two-sided Laplace transform, we prove that the model has no traveling wave solution connecting the two equilibria when R0 〉 1 and c ∈（0, c^＊）.

The Game-Theoretical Model of Using Insecticide-Treated Bed-Nets to Fight Malaria

Malaria infection is a major problem in many countries. The use of the Insecticide-Treated Bed-Nets (ITNs) has been shown to significantly reduce the number of malaria infections;however, the effectiveness is often jeopardized by improper handling or human behavior such as inconsistent usage. In this paper, we present a game-theoretical model for ITN usage in communities with malaria infections. We show that it is in the individual’s self interest to use the ITNs as long as the malaria is present in the community. Such an optimal ITN usage will significantly decrease the malaria prevalence and under some conditions may even lead to complete eradication of the disease.

Influential nodes identification in complex networks based on global and local information

Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In this paper,we comprehensively consider the global position and local structure to identify influential nodes.The number of iterations in the process of k-shell decomposition is taken into consideration,and the improved k-shell decomposition is then put forward.The improved k-shell decomposition and degree of target node are taken as the benchmark centrality,in addition,as is well known,the effect between node pairs is inversely proportional to the shortest path length between two nodes,and then we also consider the effect of neighbors on target node.To evaluate the performance of the proposed method,susceptible-infected(SI)model is adopted to simulate the spreading process in four real networks,and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.

Epidemic spreading on networks with vaccination

In this paper, a new susceptible-infected-susceptible （SIS） model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns （the recovered individuals have or have not immunity） on scale-free networks are discussed. Both theoretical and numerical analyses are presented. The epidemic thresholds related to the vaccination rate, the vaccination-invalid rate and the vaccination success rate on scale-free networks are demonstrated, showing different results from the reported observations. This reveals that whether or not the epidemic can spread over a network under vaccination control is determined not only by the network structure but also by the medicine＇s effective duration. Moreover, for a given infective rate, the proportion of individuals to vaccinate can be calculated theoretically for the case that the recovered nodes have immunity. Finally, simulated results are presented to show how to control the disease prevalence.

Predicting Resting-state Functional Connectivity With Efficient Structural Connectivity

The complex relationship between structural connectivity(SC) and functional connectivity(FC) of human brain networks is still a critical problem in neuroscience. In order to investigate the role of SC in shaping resting-state FC, numerous models have been proposed. Here, we use a simple dynamic model based on the susceptible-infected-susceptible(SIS) model along the shortest paths to predict FC from SC. Unlike the previous dynamic model based on SIS theory, we focus on the shortest paths as the principal routes to transmit signals rather than the empirical structural brain network. We first simplify the structurally connected network into an efficient propagation network according to the shortest paths and then combine SIS infection theory with the efficient network to simulate the dynamic process of human brain activity. Finally, we perform an extensive comparison study between the dynamic models embedded in the efficient network, the dynamic model embedded in the structurally connected network and dynamic mean field(DMF) model predicting FC from SC. Extensive experiments on two different resolution datasets indicate that i) the dynamic model simulated on the shortest paths can predict FC among both structurally connected and unconnected node pairs; ii) though there are fewer links in the efficient propagation network, the predictive power of FC derived from the efficient propagation network is better than the dynamic model simulated on a structural brain network; iii) in comparison with the DMF model,the dynamic model embedded in the shortest paths is found to perform better to predict FC.

Reduced Differential Transform Method for Solving Nonlinear Biomathematics Models

In this paper,we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model.The reduced differential transforms method(RDTM)is one of the interesting methods for finding the approximate solutions for nonlinear problems.We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model.We discuss the numerical results at some special values of parameters in the approximate solutions.We use the computer software package such as Mathematical to find more iteration when calculating the approximate solutions.Graphical results and discussed quantitatively are presented to illustrate behavior of the obtained approximate solutions.

Random walk immunization strategy on scale-free networks

A novel immunization strategy called the random walk immunization strategy on scale-free networks is proposed. Different from other known immunization strategies, this strategy works as follows： a node is randomly chosen from the network. Starting from this node, randomly walk to one of its neighbor node; if the present node is not immunized, then immunize it and continue the random walk; otherwise go back to the previous node and randomly walk again. This process is repeated until a certain fraction of nodes is immunized. By theoretical analysis and numerical simulations, we found that this strategy is very effective in comparison with the other known immunization strategies.

Epidemic spreading on random surfer networks with infected avoidance strategy

In this paper, we study epidemic spreading on random surfer networks with infected avoidance （IA） strategy. In particular, we consider that susceptible individuals＇ moving direction angles are affected by the current location information received from infected individuals through a directed information network. The model is mainly analyzed by discrete-time numerical simulations. The results indicate that the IA strategy can restrain epidemic spreading effectively. However, when long-distance jumps of individuals exist, the IA strategy＇s effectiveness on restraining epidemic spreading is heavily reduced. Finally, it is found that the influence of the noises from information transferring process on epidemic spreading is indistinctive.

A stochastic epidemic model on homogeneous networks

In this paper, a stochastic SIS epidemic model on homogeneous networks is considered. The largest Lyapunov exponent is calculated by Oseledec multiplicative ergodic theory, and the stability condition is determined by the largest Lyapunov exponent. The probability density function for the proportion of infected individuals is found explicitly, and the stochastic bifurcation is analysed by a probability density function. In particular, the new basic reproductive number R^＊, that governs whether an epidemic with few initial infections can become an endemic or not, is determined by noise intensity. In the homogeneous networks, despite of the basic productive number R0 〉1, the epidemic will die out as long as noise intensity satisfies a certain condition.

Spontaneous Infection and Periodic Evolving of Domain in a Diffusive SIS Epidemic Model

In this paper, we consider a susceptible-infective-susceptible(SIS) reaction-diffusion epidemic model with spontaneous infection and logistic source in a periodically evolving domain. Using the iterative technique,the uniform boundedness of solution is established. In addition, the spatial-temporal risk index R0(ρ) depending on the domain evolution rate ρ(t) as well as its analytical properties are discussed. The monotonicity of R0(ρ)with respect to the diffusion coefficients of the infected dI, the spontaneous infection rate η(ρ(t)y) and interval length L is investigated under appropriate conditions. Further, the existence and asymptotic behavior of periodic endemic equilibria are explored by upper and lower solution method. Finally, some numerical simulations are presented to illustrate our analytical results. Our results provide valuable information for disease control and prevention.

Bifurcation analysis of an SIS epidemic model with a generalized non-monotonic and saturated incidence rate

In this paper,a new generalized non-monotonic and saturated incidence rate was introduced into a susceptible-infected-susceptible(SIS)epidemic model to account for inhibitory effect and crowding effect.The dynamic properties of the model were studied by qualitative theory and bifurcation theory.It is shown that when the infuence of psychological factors is large,the model has only disease-free equilibrium point,and this disease-free equilibrium point is globally asymptotically stable;when the influence of psychological factors is small,for some parameter conditions,the model has a unique endemic equilibrium point,which is a cusp point of co-dimension two,and for other parameter conditions the model has two endemic equilibrium points,one of which could be weak focus or center.In addition,the results of the model undergoing saddle-node bifurcation,Hopf bifurcation and Bogdanov-Takens bifurcation as the parameters vary were also proved.These results shed light on the impact of psychological behavior of susceptible people on the disease transmission.

Backward Bifurcation in Simple SIS Model

We describe and analyze a simple SIS model with treatment. In particular, we give a completely qualitative analysis by means of the theory of asymptotically autonomous system. It is found that a backward bifurcation occurs if the adequate contact rate or the capacity is small. It is also found that there exists bistable endemic equilibria. In the case of disease-induced death, it is shown that the backward bifurcation also occurs. Moreover, there is no limit cycle under some conditions, and the subcritical Hopf bifurcation occurs under another conditions.