Problem Of Contagion Research Articles

Government intervention, linkages and financial fragility

We examine how financial integration affects financial stability and what government intervention maximizes stability and well-being, in a setup where depositors can obtain information on the quality of investments in their bank but there is a friction that prevents them from determining the quality of the investments of the other banks in the system. In this way, depositors will try to withdraw their deposits when they observe that the expected profitability in their bank is low. This situation will lead to a contagion problem as troubled banks may be forced to liquidate their investments in other banks. To prevent this contagion risk and reduce the costs of crises, we look at various policies governments can use, such as recapitalizing troubled banks, increasing capital requirements, or a lender-of-last-resort policy.

Collective dynamics in science and society

This editorial paper presents the articles published in a special issue devoted to active particle methods applied to modeling, qualitative analysis, and simulation of the collective dynamics of large systems of interacting living entities in science and society. The modeling approach refers to the mathematical tools of behavioral swarms theory and to the kinetic theory of active particles. Applications focus on classical problems of swarms theory, on crowd dynamics related to virus contagion problems, and to multiscale problems related to the derivation of models at a large scale from the mathematical description at the microscopic scale. A critical analysis of the overall contents of the issue is proposed, with the aim to provide a forward look to research perspectives.

Coupling kinetic theory approaches for pedestrian dynamics and disease contagion in a confined environment

The goal of this work is to study an infectious disease spreading in a medium size population occupying a confined environment. For this purpose, we consider a kinetic theory approach to model crowd dynamics in bounded domains and couple it to a kinetic equation to model contagion. The interactions of a person with other pedestrians and the environment are modeled by using tools of game theory. The pedestrian dynamics model allows to weight between two competing behaviors: the search for less congested areas and the tendency to follow the stream unconsciously in a panic situation. Each person in the system has a contagion level that is affected by the people in their neighborhood. For the numerical solution of the coupled problem, we propose a numerical algorithm that at every time step solves one crowd dynamics problem and one contagion problem, i.e. with no subiterations between the two. We test our coupled model on a problem involving a small crowd walking through a corridor.

Simplicial SIS model in scale-free uniform hypergraph

The hypergraph offers a platform to study structural properties emerging from more complicated and higher-order than pairwise interactions among constituents and dynamical behavior such as the spread of information or disease. Recently, a simplicial contagion problem was introduced and considered using a simplicial susceptible-infected-susceptible (SIS) model. Although recent studies have investigated random hypergraphs with a Poisson-type facet degree distribution, hypergraphs in the real world can have a power-law type of facet degree distribution. Here, we consider the SIS contagion problem on scale-free uniform hypergraphs and find that a continuous or hybrid epidemic transition occurs when the hub effect is dominant or weak, respectively. We determine the critical exponents analytically and numerically. We discuss the underlying mechanism of the hybrid epidemic transition.

Mapping of stock exchanges: contagion from a new perspective

ABSTRACTThis paper addresses the contagion problem between stock exchanges and uses self-organizing maps (SOMs) to develop a two-dimensional map based on five market variables from 48 stock exchanges around the world for the 2000–2012 period. The study addresses markets worldwide that have different levels of economic development. Using five market variables, we group stock exchanges into distinctive clusters and analyze their similarities, differences, and dynamics. The technique applied, artificial neural networks (ANNs), is a non-parametric visualization tool to study the dynamics of the markets worldwide following a non-traditional perspective based on the specific formation of groups and their evolution. Each group is defined by the Euclidean distances between markets. There are certain common features, both economic and geographic, within the migrant and static exchanges, which offer new insights. By applying the standard contagion methodology to the resulting groups, we study the spread of the subprime crisis and find evidence of contagion, as well as a high interdependence between markets for the entire period under consideration.

Contagion of Cheating Behaviors in Online Social Networks

Human behaviors are known to spread through social contact. The diffusion process on social networks has also been leveraged to understand the spread of undesirable contagion. The contagion of malicious or even criminal behaviors in online social networks is just beginning to attract attention. Here, we study the social contagion problem of cheating behavior found in the massively multiplayer online role-playing game (MMORPG) that provides a lifelike environment with rich and realistic user interactions. Because cheating users boast an abnormal thus conspicuous degree of success, it has a strong chance of being noticed by their friends and leading them to cheat themselves. To detect and prevent cheating, it is beneficial to understand this dynamic as a contagion problem. In this paper, we show the existence of the contagion of cheating. We then explore various possible social reinforcement mechanisms after introducing several factors to quantify the effect of social reinforcement on the contagion and analyze the dynamics of bot diffusion in an extensive user interaction log from a major MMORPG.

The Inverse Contagion Problem (ICP) vs.: Predicting site contagion in real time, when network links are not observable

We study the inverse contagion problem (ICP). As opposed to the direct contagion problem, in which the network structure is known and the question is when each node will be contaminated, in the inverse problem the links of the network are unknown but a sequence of contagion histories (the times when each node was contaminated) is observed. We consider two versions of the ICP: The strong problem (SICP), which is the reconstruction of the network and has been studied before, and the weak problem (WICP), which requires “only” the prediction (at each time step) of the nodes that will be contaminated at the next time step (this is often the real life situation in which a contagion is observed and predictions are made in real time). Moreover, our focus is on analyzing the increasing accuracy of the solution, as a function of the number of contagion histories already observed. For simplicity, we discuss the simplest (deterministic and synchronous) contagion dynamics and the simplest solution algorithm, which we have applied to different network types.The main result of this paper is that the complex problem of the convergence of the ICP for a network can be reduced to an individual property of pairs of nodes: the “false link difficulty”. By definition, given a pair of unlinked nodes i and j, the difficulty of the false link (i,j) is the probability that in a random contagion history, the nodes i and j are not contaminated at the same time step (or at consecutive time steps). In other words, the “false link difficulty” of a non-existing network link is the probability that the observations during a random contagion history would not rule out that link. This probability is relatively straightforward to calculate, and in most instances relies only on the relative positions of the two nodes (i,j) and not on the entire network structure.We have observed the distribution of false link difficulty for various network types, estimated it theoretically and confronted it (successfully) with the numerical simulations. Based on it, we estimated analytically the convergence of the ICP solution (as a function of the number of contagion histories observed), and found it to be in perfect agreement with simulation results. Finally, the most important insight we obtained is that SICP and WICP are have quite different properties: if one in interested only in the operational aspect of predicting how contagion will spread, the links which are most difficult to decide about are the least influential on contagion dynamics. In other words, the parts of the network which are harder to reconstruct are also least important for predicting the contagion dynamics, up to the point where a (large) constant number of false links in the network (i.e. non-convergence of the network reconstruction procedure) implies a zero rate of the node contagion prediction errors (perfect convergence of the WICP). Thus, the contagion prediction problem (WICP) difficulty is very different from the network reconstruction problem (SICP), in as far as links which are difficult to reconstruct are quite harmless in terms of contagion prediction capability (WICP).

Gobernanza de la salud dermatológica: Modelo de prevención sanitaria y tratamiento con implicaciones para un dispositivo de intervención desde el Trabajo Social

Studies of the Social Work of dermatological health show that prevention is a low cost factor with respect to the treatment of a disease acquired by a contamination of parasites. In that sense, a documentary, cross-sectional and descriptive study was carried out with a non-probabilistic selection of indexed sources, registered in ISSN and DOI, with the purpose of establishing an integral model for the study Of an outbreak of dermatological contamination and to derive the strategies of intervention from the Social Work in institutions of basic education. The McKendrick (1926: 100) propagation model proved to be the most complete, although it offers the integration of other models that explain the problem of contagion and the future scenarios of treatment, recontagio and prevention. The need to carry out strategies for prevention and promotion of disease-free lifestyles, as well as individual self-care as collective co-responsibility, is highlighted.

Study on the Mechanism of Enterprise Group’s Credit Risk Contagion

In the face of today’s credit risk contagion problems of enterprise group, only through combining macroscopic economic environment with microscopic credit risk contagion mechanism of enterprise group can the macro-source and production mechanism of enterprise group’s credit risk contagion be clearly observed. This paper constructs multi-index hierarchically structured model through analysis of quantifiable weight determining mechanism to analyze the credit risk contagion mechanism of enterprise groups, and obtains the source and proportion of the credit risk of enterprise group generated under the influence of national macro-environment, and then analyzes the credit risk contagion mechanism of enterprise groups.

A novel consensus based prediction strategy for data sensing

Financial contagion problems have been extensively studied in area of financial research. Most of the works focus on studying the contagion effect on the financial system. Contagion prediction is considered as one of the most important strategies to prevent contagion. But the prediction issue is seldom researched in the financial area. Traditional financial management uses a centralized method to predict contagion risk. But the central management cannot instantly acquire complete information of entire network. A decentralized method is needed to achieve a prediction in real time. This paper introduces a distributed risk contagion prediction strategy of the financial network. Firstly, consensus algorithm is used to distributively acquire contagion risk information of the entire financial network. This distributed strategy enables the system to instantly predict the risk of contagion. Secondly, the impact of the financial crisis could enormously influence the convergency of consensus algorithm. So a consensus based Kalman filter (CAF) is proposed to maintain the convergency of consensus and ensure the accuracy of the prediction. Finally, the strategy is tested in different kinds of financial systems which are impacted by different levels of the financial crisis. The simulation result shows that the strategy is robust, flexible and feasible for practical use. It also proves that the proposed strategy can provide an accurate prediction in any condition.

1998 Rusya Krizi: Bir “Şok Terapi”nin Sonucu muydu?

The “openness” promoted by the liberalisation process referred, ironically, to the openness to the financial crises in developing world in the 1990s. Russian case was the leading one among them, in which the “shock therapy” implemented by the neo-liberal perspective has been still under discussion. The paper analyzes and discusses such crisis in terms of the relevant models of crisis. The paper maintains that contrary to the general view shaped by neo-liberal perspective, the Russian Crisis has several compounds, which cannot be easily tackled in terms of either first or second generation models, rather points to the third generation models. Since the third generation models can be handled as a combination of theories such as financial market failures, highly volatile capital flows and contagion problems the paper finds out that those are the most appropriate ones for the Russian case contrary to the neoliberal perspective.

Microcredit games with noisy signals: Contagion and free-riding

The advent of microcredit financing has remarkably improved access to credit for the poor in many developing countries. Although several microcredit programs have adopted the joint liability scheme, economic theory suggests that joint liability could increase strategic default through contagion and free-riding. This paper aims at studying the extent of free-riding and contagion in joint liability lending. By using data from experimental repayment games conducted in Vietnam, with noisy signals that resemble actual microcredit programs, we found that subjects were motivated to free-ride under the joint liability scheme. While most empirical research in this area has focused on the problem of contagion, our findings point to the significance of investigating free-riding behavior under joint liability schemes. Analyses reveal that the free-riding tendency may be led by the irresponsiveness of repayment and shouldering behavior to the partner’s seemingly strategic default in the previous round.

Research on Banking Crisis Contagion Dynamics Based on the Complex Network of System Engineering

For the banking crisis contagion problem on the Financial Engineering, a crisis contagion dynamic model is proposed for the banking network based on the Complex Network of latest System Engineering theory. The model combines the contagion process of risk, the network structural features and the behavior characteristics of banking crisis. Contagion dynamics simulation and analysis are made for this model, and a conclusion is draw that the ultimate number of the immune state banks in the crisis banking network depends on contagion probability and network structure. Finally, we discuss that the role of contagion threshold value for the immune strategy for crisis contagion in the banking network, which are important for control the extent of crisis contagion.