Epidemic processes in complex networks

In recent years the research community has accumulated overwhelming evidence for the emergence of complex and heterogeneous connectivity patterns in a wide range of biological and sociotechnical systems. The complex properties of real-world networks have a profound impact on the behavior of equilibrium and nonequilibrium phenomena occurring in various systems, and the study of epidemic spreading is central to our understanding of the unfolding of dynamical processes in complex networks. The theoretical analysis of epidemic spreading in heterogeneous networks requires the development of novel analytical frameworks, and it has produced results of conceptual and practical relevance. A coherent and comprehensive review of the vast research activity concerning epidemic processes is presented, detailing the successful theoretical approaches as well as making their limits and assumptions clear. Physicists, mathematicians, epidemiologists, computer, and social scientists share a common interest in studying epidemic spreading and rely on similar models for the description of the diffusion of pathogens, knowledge, and innovation. For this reason, while focusing on the main results and the paradigmatic models in infectious disease modeling, the major results concerning generalized social contagion processes are also presented. Finally, the research activity at the forefront in the study of epidemic spreading in coevolving, coupled, and time-varying networks is reported.Comment: 62 pages, 15 figures, final versio

Tamper-Resistant Peer-to-Peer Storage for File Integrity Checking.

“... oba es gibt kan Kompromiß, zwischen ehrlich sein und link, a wann’s no so afoch ausschaut, und wann’s noch so üblich is...” — Wolfgang Ambros, 1975 One of the activities of most successful intruders of a computer system is to modify data on the victim, either to hide his/her presence and to destroy the evidence of the break-in, or to subvert the system completely and make it accessible for further abuse without triggering alarms. File integrity checking is one common method to mitigate the effects of successful intrusions by detecting the changes an intruder makes to files on a computer system. Historically file integrity checking has been implemented using tools that operate locally on a single system, which imposes quite some restrictions regarding maintenance and scalability. Recent improvements for large scale environments have introduced trusted central servers which provide secure fingerprint storage and logging facilities, but such centralism presents some new shortcomings

Higher-order dynamics on complex networks

L’estudi de les xarxes complexes ha esdevingut un nou paradigma a l’hora d’entendre i modelar sistemes físics. Uns dels principals punts d’interès són les dinàmiques que hi podem modelar. Però com en tot model, la quantitat de informació que podem representar-hi està limitada per la seva complexitat. La motivació principal d’aquesta tesi és l’estudi de l’efecte que un increment de la complexitat estructural, relacional i temporal té sobre tres importants àrees d’estudi: l’evolució de la cooperació, la propagació de malalties, i l’estudi de la mobilitat humana. En aquest treball hem utilitzat dilemes socials per estudiar com evoluciona la cooperació dins d’una població. Incrementant l’ordre de complexitat estructural de les xarxes, permetent que els individus és puguin relacionar en diferents contextos socials, s’ha mostrat cabdal a l’hora d’explicar algunes característiques sobre l’aparició de comportaments altruistes. Utilitzant aquestes noves estructures, les xarxes multicapa, permetem als membres de la població cooperar en determinat contextos i de no fer-ho en d’altres i això, com analíticament demostrem, augmenta l’espectre d’escenaris allà on cooperació i defecció poden sobreviure. Seguidament, estudiem els models de propagació de malalties des de el punt de vista dels enllaços entre individus. Amb aquest augment de la complexitat relacional dels models epidèmics, aconseguim extreure informació que ens permet, entre altres coses, definir una mesura d’influència d’un enllaç a la propagació de l’epidèmia. Utilitzem aquest fet per a proposar una nova mesura de contenció, basada en l’eliminació dels enllaços més influents, que es mostra més eficient que altres mètodes previs. Finalment, proposem un mètode per a descriure la mobilitat que permet capturar patrons recurrents i heterogeneïtats en els temps que els individus estan en un lloc abans de desplaçar-se a un altre. Aquestes propietats són intrínseques a la mobilitat humana i el fet de poder-les capturar, tot i el cost d’augmentar l’ordre temporal, és crític, com demostrem, a l’hora de modelar com les epidèmies és difonen per mitja del moviment de les persones.El estudio de redes complejas se ha convertido en un nuevo paradigma para comprender y modelar sistemas físicos. Uno de los principales puntos de interés son las dinámicas que podemos modelar. Pero como en todo modelo, la cantidad de información que podemos representar está limitada por su complejidad. La motivación principal de esta tesis es estudiar el efecto que un incremento de la complejidad estructural, relacional y temporal tiene sobre tres importantes áreas de estudio: la evolución de la cooperación, la propagación de enfermedades, y el estudio de la movilidad humana. En este trabajo hemos utilizado dilemas sociales para estudiar cómo evoluciona la cooperación dentro de una población. Incrementando el orden de complejidad estructural de las redes, permitiendo que los individuos se puedan relacionar en diferentes contextos sociales, se ha demostrado capital para explicar algunas de las características sobre la aparición de comportamientos altruistas. Utilizando estas nuevas estructuras, las redes multicapa, permitimos a los miembros de la población cooperar en determinados contextos y no hacerlo en otros, con lo que, como demostramos analíticamente, aumenta el espectro de escenarios en los que la cooperación y la defección pueden sobrevivir. A continuación, estudiamos modelos de propagación de enfermedades desde el punto de vista de los enlaces entre individuos. Con este aumento de complejidad relacional de los modelos epidémicos, conseguimos extraer información que nos permite, entre otras cosas, definir una medida de contención, basada en la eliminación de los enlaces más influyentes, que se muestra más eficaz que otros métodos previos. Finalmente, proponemos un método para describir la movilidad que permite capturar patrones recurrentes y heterogeneidades en los tiempos que los individuos están en un lugar antes de desplazarse a otro. Estas propiedades son intrínsecas a la movilidad humana y el hecho de poder capturarlas, a pesar de incrementar el orden temporal, es crítico, como demostramos, para modelar cómo las epidemias se difunden por medio del movimiento de las personas.The study of complex networks has become a new paradigm to understand and model physical systems. One of the points of interest is the dynamics that we can model. However, as with any model, the amount of information that we can represent is limited by its complexity. The primary motivation of this thesis is the study of the effect that an increase in structural, relational and temporal complexity has on three critical areas of study: the evolution of cooperation, epidemic spreading and human mobility. In this work, we have used social dilemmas to study how cooperation within a population evolves. Increasing the order of structural complexity of the networks, allowing individuals to interact in different social contexts, has shown to be crucial to explain some features about the emergence of altruistic behaviors. Using these new structures, multilayer networks, we allow members of the population to cooperate in specific contexts and defect in others, and this, as we analytically demonstrate, increases the spectrum of scenarios where both strategies can survive. Next, we study the models of epidemic spreading from the point of view of the links between individuals. With this increase in the relational complexity of the epidemic models, we can extract information that allows us, among other things, to define a measure of the contribution of a link to the spreading. We use this metric to propose a new containment measure, based on the elimination of the most influential links, which is more effective than other previous methods. Finally, we propose a method to describe mobility that allows capturing recurrent and heterogeneous patterns in the times that individuals stay in a place before moving to another. These properties are intrinsic to human mobility, and the fact of being able to capture them, despite the cost of increasing the temporal order is critical, as we demonstrate, when it comes to modeling how epidemics spread through the movement of the people

An Initial Framework Assessing the Safety of Complex Systems

Trabajo presentado en la Conference on Complex Systems, celebrada online del 7 al 11 de diciembre de 2020.Atmospheric blocking events, that is large-scale nearly stationary atmospheric pressure patterns, are often associated with extreme weather in the mid-latitudes, such as heat waves and cold spells which have significant consequences on ecosystems, human health and economy. The high impact of blocking events has motivated numerous studies. However, there is not yet a comprehensive theory explaining their onset, maintenance and decay and their numerical prediction remains a challenge. In recent years, a number of studies have successfully employed complex network descriptions of fluid transport to characterize dynamical patterns in geophysical flows. The aim of the current work is to investigate the potential of so called Lagrangian flow networks for the detection and perhaps forecasting of atmospheric blocking events. The network is constructed by associating nodes to regions of the atmosphere and establishing links based on the flux of material between these nodes during a given time interval. One can then use effective tools and metrics developed in the context of graph theory to explore the atmospheric flow properties. In particular, Ser-Giacomi et al. [1] showed how optimal paths in a Lagrangian flow network highlight distinctive circulation patterns associated with atmospheric blocking events. We extend these results by studying the behavior of selected network measures (such as degree, entropy and harmonic closeness centrality)at the onset of and during blocking situations, demonstrating their ability to trace the spatio-temporal characteristics of these events.This research was conducted as part of the CAFE (Climate Advanced Forecasting of sub-seasonal Extremes) Innovative Training Network which has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 813844

Investing in The Health and Well-Being of Young Adults

This report was prepared to assist federal, state, and local policy makers and program leaders, as well as employers, nonprofit organizations, and other community partners, in developing and enhancing policies and programs to improve young adults' health, safety, and well-being. The report also suggests priorities for research to inform policy and programs for young adults.Young adulthood - ages approximately 18 to 26 - is a critical period of development with long-lasting implications for a person's economic security, health and well-being. Young adults are key contributors to the nation's workforce and military services and, since many are parents, to the healthy development of the next generation. Although 'millennials' have received attention in the popular media in recent years, young adults are too rarely treated as a distinct population in policy, programs, and research. Instead, they are often grouped with adolescents or, more often, with all adults. Currently, the nation is experiencing economic restructuring, widening inequality, a rapidly rising ratio of older adults, and an increasingly diverse population. The possible transformative effects of these features make focus on young adults especially important. A systematic approach to understanding and responding to the unique circumstances and needs of today's young adults can help to pave the way to a more productive and equitable tomorrow for young adults in particular and our society at large

Statistical Physics of Opinion and Social Conflict

The rise and development of opinion groups, just as their clash in social conflict, are notoriously difficult to study due to a complex interplay between structure and dynamics. The intricate feedback between psychological and sociological processes, tied with an ample variability of individual traits, makes these systems challenging both intellectually and methodologically. Yet regular patterns do emerge from the collective behavior of dissimilar people, seen in population and crime rates, in protest movements and the adoption of innovations. Statistical physics comes then as an apt and successful framework for their study, characterizing society as the common product of single wills, interactions among people and external effects. The work in this Thesis provides mathematical descriptions for the evolution of opinions in society, based on simple mechanisms of individual conduct and group influence. Such models abstract the inherent complexity of human behavior by reducing people to opinion variables spread over a network of social interactions, with variables and interactions changing in time at the pace of a handful of equations. Their macroscopic properties are interpreted as the emergence of social groups and of conflict between them due to opinion disagreement, and compared with small controlled experiments or with large online records of social activity. The extensive analysis of these models, both numerical and analytical, leads to a couple of generic observations on the link between opinion and social conflict. First, the emergence of consensual groups in society may be regulated by well-separated time scales of opinion dynamics and network evolution, and by a distribution of personality traits in the population. Our social environment can then be fragmented as more people turn against the collective mood, ultimately forming minorities as a response to external influence. Second, the exchange of views in collaborative tasks may lead not only to the rise and resolution of opinion issues, but to an intermediate state where conflicts appear periodically. In this way strife and cooperation, so much a part of human nature, can be emulated by surprisingly simple interactions among individuals

Identifying and Harnessing Concurrency for Parallel and Distributed Network Simulation

Although computer networks are inherently parallel systems, the parallel execution of network simulations on interconnected processors frequently yields only limited benefits. In this thesis, methods are proposed to estimate and understand the parallelization potential of network simulations. Further, mechanisms and architectures for exploiting the massively parallel processing resources of modern graphics cards to accelerate network simulations are proposed and evaluated