The role of time scale in the spreading of asymmetrically interacting diseases

Diseases and other contagion phenomena in nature and society can interact asymmetrically, such that one can benefit from the other, which in turn impairs the first, in analogy with predator-prey systems. Here, we consider two models for interacting disease-like dynamics with asymmetric interactions and different associated time scales. Using rate equations for homogeneously mixed populations, we show that the stationary prevalences and phase diagrams of each model behave differently with respect to variations of the relative time scales. We also characterize in detail the regime where transient oscillations are observed, a pattern that is inherent to asymmetrical interactions but often ignored in the literature. Our results contribute to a better understanding of disease dynamics in particular, and interacting processes in general, and could provide interesting insights for real-world applications, most notably, the interplay between the dynamics of fact-checked and fake news.Comment: 11 pages and 8 figure

Modeling the effects of social distancing on the large-scale spreading of diseases

To contain the propagation of emerging diseases that are transmissible from human to human, non-pharmaceutical interventions (NPIs) aimed at reducing the interactions between humans are usually implemented. One example of the latter kind of measures is social distancing, which can be either policy-driven or can arise endogenously in the population as a consequence of the fear of infection. However, if NPIs are lifted before the population reaches herd immunity, further re-introductions of the pathogen would lead to secondary infections. Here we study the effects of different social distancing schemes on the large scale spreading of diseases. Specifically, we generalize metapopulation models to include social distancing mechanisms at the subpopulation level and model short- and long-term strategies that are fed with local or global information about the epidemics. We show that different model ingredients might lead to very diverse outcomes in different subpopulations. Our results suggest that there is not a unique answer to the question of whether contention measures are more efficient if implemented and managed locally or globally and that model outcomes depends on how the full complexity of human interactions is taken into account

Epidemic spreading in populations of mobile agents with adaptive behavioral response

Despite the advanced stage of epidemic modeling, there is a major demand for methods to incorporate behavioral responses to the spread of a disease, such as social distancing and adoption of prevention methods. Mobility plays an important role on epidemic dynamics and is also affected by behavioral changes, but there are many situations in which real mobility data is incomplete or inaccessible. We present a model for epidemic spreading in temporal networks of mobile agents that incorporates local behavioral responses. Susceptible agents are allowed to move towards the opposite direction of infected agents in their neighborhood. We show that this mechanism considerably decreases the stationary prevalence when the spatial density of agents is low. However, for higher densities, the mechanism causes an abrupt phase transition, where a new bistable phase appears. We develop a semi-analytic approach for the case when the mobility is fast compared to the disease dynamics, and use it to argue that the bistability is caused by the emergence of spatial clusters of susceptible agents. Finally, we characterize the temporal networks formed in the fast mobility regime, showing how the degree distributions and other metrics are affected by the behavioral mechanism. Our work incorporates results previously known from adaptive networks into population of mobile agents, which can be further developed to be used in mobility-driven models

Disease and information spreading at different speeds in multiplex networks

Nowadays, one of the challenges we face when carrying out modeling of epidemic spreading is to develop methods to control disease transmission. In this article we study how the spreading of knowledge of a disease affects the propagation of that disease in a population of interacting individuals. For that, we analyze the interaction between two different processes on multiplex networks: the propagation of an epidemic using the susceptible-infected-susceptible dynamics and the dissemination of information about the disease—and its prevention methods—using the unaware-aware-unaware dynamics, so that informed individuals are less likely to be infected. Unlike previous related models where disease and information spread at the same time scale, we introduce here a parameter that controls the relative speed between the propagation of the two processes. We study the behavior of this model using a mean-field approach that gives results in good agreement with Monte Carlo simulations on homogeneous complex networks. We find that increasing the rate of information dissemination reduces the disease prevalence, as one may expect. However, increasing the speed of the information process as compared to that of the epidemic process has the counterintuitive effect of increasing the disease prevalence. This result opens an interesting discussion about the effects of information spreading on disease propagation

Epidemic spreading with awareness and different time scales in multiplex networks

One of the major issues in theoretical modeling of epidemic spreading is the development of methods to control the transmission of an infectious agent. Human behavior plays a fundamental role in the spreading dynamics and can be used to stop a disease from spreading or to reduce its burden, as individuals aware of the presence of a disease can take measures to reduce their exposure to contagion. In this paper, we propose a mathematical model for the spread of diseases with awareness in complex networks. Unlike previous models, the information is propagated following a generalized Maki-Thompson rumor model. Flexibility on the timescale between information and disease spreading is also included. We verify that the velocity characterizing the diffusion of information awareness greatly influences the disease prevalence. We also show that a reduction in the fraction of unaware individuals does not always imply a decrease of the prevalence, as the relative timescale between disease and awareness spreading plays a crucial role in the systems' dynamics. This result is shown to be independent of the network topology. We finally calculate the epidemic threshold of our model, and show that it does not depend on the relative timescale. Our results provide a new view on how information influence disease spreading and can be used for the development of more efficient methods for disease control

Las estrategias sociales en el rendimiento académico de los estudiantes

The objective was to determine the influence of the use of social strategies on the academic performance of language students at a national university. The study has a quantitative approach. The design is pre-experimental and the sample was 40 students. The information is compiled in a pre-test - post-test pedagogical test and a methodological application guide of social strategies to improve the performance of a foreign language. It was concluded that the use of social strategies significantly influences the academic performance of students.El objetivo fue determinar la influencia del uso de estrategias sociales en el rendimiento académico de los estudiantes de idiomas de una universidad nacional peruana. El estudio es de enfoque cuantitativo. El diseño es pre experimental y la muestra fue de 40 estudiantes. La información es recopilada en una prueba pedagógica de pre test – post test y una guía de aplicación metodológica de las estrategias sociales para mejorar el rendimiento de una lengua extranjera. Se concluyó que el uso de las estrategias sociales influye significativamente en el rendimiento académico de los estudiantes

Los métodos de enseñanza de lenguas extranjeras y las estrategias sociales en estudiantes universitarios

The objective was to analyze the relationship between foreign language teaching methods and social strategies in university students. The study is of a non-experimental, cross-sectional quantitative approach. The design is correlational. The sample was 94 students, and the information was collected in two Likert scales. The conclusion is that there is a direct and significant relationship between foreign language teaching methods and social strategies. In other words, if there is more cooperation and empathy, students will become more involved in their learning of the foreign language.El objetivo fue analizar la relación entre los métodos de enseñanza de lenguas extranjeras y las estrategias sociales, en estudiantes universitarios. El estudio es de enfoque cuantitativo no experimental, transversal. El diseño es correlacional. La muestra fue de 94 estudiantes, y la información fue recopilada en dos escalas de Likert. La conclusión es que existe una relación directa y significativa entre los métodos la enseñanza de lenguas extranjeras y las estrategias sociales. Es decir que, si hay más cooperación y empatía, los estudiantes se involucrarían más en su aprendizaje de la lengua extranjera