Triadic Approximation Reveals the Role of Interaction Overlap on the Spread of Complex Contagions on Higher-Order Networks.

Contagion processes relying on the exposure to multiple sources are prevalent in social systems, and are effectively represented by hypergraphs. In this Letter, we derive a mean-field model that goes beyond node- and pair-based approximations. We reveal how the stability of the contagion-free state is decided by either two- or three-body interactions, and how this is strictly related to the degree of overlap between these interactions. Our findings demonstrate the dual effect of increased overlap: it lowers the invasion threshold, yet produces smaller outbreaks. Corroborated by numerical simulations, our results emphasize the significance of the chosen representation in describing a higher-order process.

On the number of stable solutions in the Kuramoto model.

We consider a system of n coupled oscillators described by the Kuramoto model with the dynamics given by θ˙=ω+Kf(θ). In this system, an equilibrium solution θ∗ is considered stable when ω+Kf(θ∗)=0, and the Jacobian matrix Df(θ∗) has a simple eigenvalue of zero, indicating the presence of a direction in which the oscillators can adjust their phases. Additionally, the remaining eigenvalues of Df(θ∗) are negative, indicating stability in orthogonal directions. A crucial constraint imposed on the equilibrium solution is that |Γ(θ∗)|≤π, where |Γ(θ∗)| represents the length of the shortest arc on the unit circle that contains the equilibrium solution θ∗. We provide a proof that there exists a unique solution satisfying the aforementioned stability criteria. This analysis enhances our understanding of the stability and uniqueness of these solutions, offering valuable insights into the dynamics of coupled oscillators in this system.

De-escalating therapy in inflammatory bowel disease: Results from an observational study in clinical practice.

BACKGROUND AND OBJECTIVES: Combination therapy with an immunomodulator (IMM) and an anti-TNF is commonly recommended in Crohn's disease (CD) and ulcerative colitis (UC) patients. However, little is known about relapse rates after therapeutic de-escalation. This study aimed to evaluate the risk of relapse in a cohort of UC and CD patients with long-standing clinical remission after discontinuation of IMM or anti-TNF and to identify predictive factors for relapse. METHODS: This retrospective study included patients with UC or CD on combination therapy and clinical remission for at least 6 months. IMM or anti-TNF was stopped upon physician decision. Primary objective was to evaluate the relapse rates after discontinuation of IMM or anti-TNF and to analyze predictors of relapse. RESULTS: The study included 88 patients, 48 patients (54.5%) discontinued IMM and 40 (45.5%) anti-TNF. During follow-up, relapse rates were 16.7% and 52.5% in the IMM discontinuation group and anti-TNF discontinuation group, respectively (p<0.001). Multivariate analysis showed that anti-TNF discontinuation (HR=3.01; 95% CI=1.22-7.43) and ileal CD location (HR=2.36; 95% CI=1.02-5.47) were predictive factors for relapse while inflammatory CD phenotype was a protective factor (HR=0.32; 95% CI=0.11-0.90). Reintroduction of anti-TNF upon relapse was effective and safe. CONCLUSION: Anti-TNF discontinuation led to significantly higher relapse rates compared to IMM discontinuation in UC and CD patients on combination therapy. Anti-TNF discontinuation and ileal CD location were identified as predictive factors for relapse while inflammatory CD phenotype was a protective factor. Retreatment after anti-TNF discontinuation was effective and safe.

Emergence of protective behaviour under different risk perceptions to disease spreading.

The behaviour of individuals is a main actor in the control of the spread of a communicable disease and, in turn, the spread of an infectious disease can trigger behavioural changes in a population. Here, we study the emergence of individuals' protective behaviours in response to the spread of a disease by considering two different social attitudes within the same population: concerned and risky. Generally speaking, concerned individuals have a larger risk aversion than risky individuals. To study the emergence of protective behaviours, we couple, to the epidemic evolution of a susceptible-infected-susceptible model, a decision game based on the perceived risk of infection. Using this framework, we find the effect of the protection strategy on the epidemic threshold for each of the two subpopulations (concerned and risky), and study under which conditions risky individuals are persuaded to protect themselves or, on the contrary, can take advantage of a herd immunity by remaining healthy without protecting themselves, thanks to the shield provided by concerned individuals. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

Behavioural response to heterogeneous severity of COVID-19 explains temporal variation of cases among different age groups.

Together with seasonal effects inducing outdoor or indoor activities, the gradual easing of prophylaxis caused second and third waves of SARS-CoV-2 to emerge in various countries. Interestingly, data indicate that the proportion of infections belonging to the elderly is particularly small during periods of low prevalence and continuously increases as case numbers increase. This effect leads to additional stress on the health care system during periods of high prevalence. Furthermore, infections peak with a slight delay of about a week among the elderly compared to the younger age groups. Here, we provide a mechanistic explanation for this phenomenology attributable to a heterogeneous prophylaxis induced by the age-specific severity of the disease. We model the dynamical adoption of prophylaxis through a two-strategy game and couple it with an SIR spreading model. Our results also indicate that the mixing of contacts among the age groups strongly determines the delay between their peaks in prevalence and the temporal variation in the distribution of cases. This article is part of the theme issue 'Data science approaches to infectious disease surveillance'.

Symmetry-breaking mechanism for the formation of cluster chimera patterns.

The emergence of order in collective dynamics is a fascinating phenomenon that characterizes many natural systems consisting of coupled entities. Synchronization is such an example where individuals, usually represented by either linear or nonlinear oscillators, can spontaneously act coherently with each other when the interactions' configuration fulfills certain conditions. However, synchronization is not always perfect, and the coexistence of coherent and incoherent oscillators, broadly known in the literature as chimera states, is also possible. Although several attempts have been made to explain how chimera states are created, their emergence, stability, and robustness remain a long-debated question. We propose an approach that aims to establish a robust mechanism through which cluster synchronization and chimera patterns originate. We first introduce a stability-breaking method where clusters of synchronized oscillators can emerge. At variance with the standard approach where synchronization arises as a collective behavior of coupled oscillators, in our model, the system initially sets on a homogeneous fixed-point regime, and, only due to a global instability principle, collective oscillations emerge. Following a combination of the network modularity and the model's parameters, one or more clusters of oscillators become incoherent within yielding a particular class of patterns that we here name cluster chimera states.

The interconnection between independent reactive control policies drives the stringency of local containment.

The lack of medical treatments and vaccines upon the arrival of the SARS-CoV-2 virus has made non-pharmaceutical interventions the best allies in safeguarding human lives in the face of the COVID-19 pandemic. Here we propose a self-organized epidemic model with multi-scale control policies that are relaxed or strengthened depending on the extent of the epidemic outbreak. We show that optimizing the balance between the effects of epidemic control and the associated socio-economic cost is strongly linked to the stringency of control measures. We also show that non-pharmaceutical interventions acting at different spatial scales, from creating social bubbles at the household level to constraining mobility between different cities, are strongly interrelated. We find that policy functionality changes for better or worse depending on network connectivity, meaning that some populations may allow for less restrictive measures than others if both have the same resources to respond to the evolving epidemic.

Quadruple therapies are superior to standard triple therapy for Helicobacter pylori first-line eradication in Chile. / Terapias cuádruples son superiores a terapia triple estándar en primera línea de erradicación de Helicobacter pylori en Chile.

INTRODUCTION: Helicobacter pylori infection affects approximately 70% of the Chilean population. It is a public health problem whose eradication treatment is part of the explicit health guarantees in Chile. OBJECTIVES: Characterize the most widely used H. pylori first-line eradication therapies in our environment and evaluate their efficacy. METHODS: A retrospective observational study was carried out where, in patients with certified H. pylori infection, the eradication therapy indicated by the treating physician, its efficacy, adherence and adverse effects, in addition to the eradication certification method used, were evaluated. RESULTS: 242 patients and 4 main therapies were analyzed: standard triple therapy, dual therapy, concomitant therapy, and bismuth quadruple therapy. Eradication rates of 81.9% (95% CI 74.44-87.63), 88.5% (95% CI 73.13-95.67), 93.7% (95% CI 78.07-98.44) and 97.6% (95% CI 84.81-99.67) were observed respectively, with concomitant therapy (RR: 1.14; 95% CI 1.01-1.29; p=.028) and quadruple therapy with bismuth (RR: 1.19; 95% CI 1.09-1.31; p<.001) being significantly more effective than standard triple therapy. Regarding the rate of reported adverse effects, it was 58.5% (95% CI 50.66-65.92), 35.4% (95% CI 24.6-48.11), 22.9% (95% CI 81-37.14) and 63.4% (95% CI 47.8-76.64), having the dual and concomitant therapy significantly fewer adverse effects compared with standard therapy. CONCLUSIONS: Quadruple therapies are superior to standard triple therapy and should be considered as first-line treatment in Chile. Dual therapy is promising. More studies will be required to determine which therapies are most cost-effective.

Geometric unfolding of synchronization dynamics on networks.

We study the synchronized state in a population of network-coupled, heterogeneous oscillators. In particular, we show that the steady-state solution of the linearized dynamics may be written as a geometric series whose subsequent terms represent different spatial scales of the network. Specifically, each additional term incorporates contributions from wider network neighborhoods. We prove that this geometric expansion converges for arbitrary frequency distributions and for both undirected and directed networks provided that the adjacency matrix is primitive. We also show that the error in the truncated series grows geometrically with the second largest eigenvalue of the normalized adjacency matrix, analogously to the rate of convergence to the stationary distribution of a random walk. Last, we derive a local approximation for the synchronized state by truncating the spatial series, at the first neighborhood term, to illustrate the practical advantages of our approach.

Modeling financial distress propagation on customer-supplier networks.

Financial networks have been the object of intense quantitative analysis during the last few decades. Their structure and the dynamical processes on top of them are of utmost importance to understand the emergent collective behavior behind economic and financial crises. In this paper, we propose a stylized model to understand the "domino effect" of distress in client-supplier networks. We provide a theoretical analysis of the model, and we apply it to several synthetic networks and a real customer-supplier network, supplied by one of the largest banks in Europe. Besides, the proposed model allows us to investigate possible scenarios for the functioning of the financial distress propagation and to assess the economic health of the full network. The main novelty of this model is the combination of two stochastic terms: an additive noise, accounting by the capability of trading and paying obligations, and a multiplicative noise representing the variations of the market. Both parameters are crucial to determining the maximum default probability and the diffusion process characteristics.

Baveno VI and Expanded Baveno VI criteria successfully predicts the absence of high-risk gastro-oesophageal varices in a Chilean cohort.

BACKGROUND: Baveno VI and expanded Baveno VI criteria have been recommended to circumvent the need for endoscopy screening in patients with a very low probability of varices needing treatment (VNT). AIM: To validate these criteria in a Latin American population. METHODS: The ability of Baveno VI criteria (liver stiffness measurement (LSM) <20 kPa and platelet count >150 × 103/µL) and expanded Baveno VI criteria (LSM < 25kPa and platelet count >110 × 103/µL) to exclude the presence of VNT was tested in a prospectively recruited cohort of patients with Child-Pugh A liver cirrhosis and with no previous variceal haemorrhage who attended the liver clinics of three major hospitals in Chile. RESULTS: Three hundred patients were included. The median (IQR) age was 61 [18-86] years, median MELD was 8.0 (6-17), median LSM was 17.2 (10.2-77) kPa and median platelet count was 137 (23-464) × 103 /µL. The main aetiology was non-alcoholic fatty liver disease (67.3%). VNT were present in 18% of patients. The Baveno VI criteria had a sensitivity of 98.1% and a specificity of 38.2%, potentially sparing 31.3% of upper endoscopies with a very low risk of missing VNT (1.1%). The expanded Baveno VI criteria had a sensitivity of 90.7% and a specificity of 61%, potentially sparing 51.3% of upper endoscopies with a risk of missing VNT of 3.6%. Both criteria were independently associated with the absence of VNT. CONCLUSION: We validated the Baveno VI and expanded Baveno VI criteria in Chilean population, potentially sparing 31.3% and 51.3% of endoscopies, respectively, with a very low risk of missing VNT. Fondecyt 1191183.

Endemicity and prevalence of multipartite viruses under heterogeneous between-host transmission.

Multipartite viruses replicate through a puzzling evolutionary strategy. Their genome is segmented into two or more parts, and encapsidated in separate particles that appear to propagate independently. Completing the replication cycle, however, requires the full genome, so that a systemic infection of a host requires the concurrent presence of several particles. This represents an apparent evolutionary drawback of multipartitism, while its advantages remain unclear. A transition from monopartite to multipartite viral forms has been described in vitro under conditions of high multiplicity of infection, suggesting that cooperation between defective mutants is a plausible evolutionary pathway towards multipartitism. However, it is unknown how the putative advantages that multipartitism might enjoy at the microscopic level affect its epidemiology, or if an explicit advantange is needed to explain its ecological persistence. In order to disentangle which mechanisms might contribute to the rise and fixation of multipartitism, we here investigate the interaction between viral spreading dynamics and host population structure. We set up a compartmental model of the spread of a virus in its different forms and explore its epidemiology using both analytical and numerical techniques. We uncover that the impact of host contact structure on spreading dynamics entails a rich phenomenology of ecological relationships that includes cooperation, competition, and commensality. Furthermore, we find out that multipartitism might rise to fixation even in the absence of explicit microscopic advantages. Multipartitism allows the virus to colonize environments that could not be invaded by the monopartite form, while homogeneous contacts between hosts facilitate its spread. We conjecture that these features might have led to an increase in the diversity and prevalence of multipartite viral forms concomitantly with the expansion of agricultural practices.

Uncertainty propagation in complex networks: From noisy links to critical properties.

Many complex networks are built up from empirical data prone to experimental error. Thus, the determination of the specific weights of the links is a noisy measure. Noise propagates to those macroscopic variables researchers are interested in, such as the critical threshold for synchronization of coupled oscillators or for the spreading of a disease. Here, we apply error propagation to estimate the macroscopic uncertainty in the critical threshold for some dynamical processes in networks with noisy links. We obtain closed form expressions for the mean and standard deviation of the critical threshold depending on the properties of the noise and the moments of the degree distribution of the network. The analysis provides confidence intervals for critical predictions when dealing with uncertain measurements or intrinsic fluctuations in empirical networked systems. Furthermore, our results unveil a nonmonotonous behavior of the uncertainty of the critical threshold that depends on the specific network structure.

Evolution of Cooperation in the Presence of Higher-Order Interactions: From Networks to Hypergraphs.

Many real systems are strongly characterized by collective cooperative phenomena whose existence and properties still need a satisfactory explanation. Coherently with their collective nature, they call for new and more accurate descriptions going beyond pairwise models, such as graphs, in which all the interactions are considered as involving only two individuals at a time. Hypergraphs respond to this need, providing a mathematical representation of a system allowing from pairs to larger groups. In this work, through the use of different hypergraphs, we study how group interactions influence the evolution of cooperation in a structured population, by analyzing the evolutionary dynamics of the public goods game. Here we show that, likewise to network reciprocity, group interactions also promote cooperation. More importantly, by means of an invasion analysis in which the conditions for a strategy to survive are studied, we show how, in heterogeneously-structured populations, reciprocity among players is expected to grow with the increasing of the order of the interactions. This is due to the heterogeneity of connections and, particularly, to the presence of individuals standing out as hubs in the population. Our analysis represents a first step towards the study of evolutionary dynamics through higher-order interactions, and gives insights into why cooperation in heterogeneous higher-order structures is enhanced. Lastly, it also gives clues about the co-existence of cooperative and non-cooperative behaviors related to the structural properties of the interaction patterns.

Abrupt Desynchronization and Extensive Multistability in Globally Coupled Oscillator Simplexes.

Collective behavior in large ensembles of dynamical units with nonpairwise interactions may play an important role in several systems ranging from brain function to social networks. Despite recent work pointing to simplicial structure, i.e., higher-order interactions between three or more units at a time, their dynamical characteristics remain poorly understood. Here we present an analysis of the collective dynamics of such a simplicial system, namely coupled phase oscillators with three-way interactions. The simplicial structure gives rise to a number of novel phenomena, most notably a continuum of abrupt desynchronization transitions with no abrupt synchronization transition counterpart, as well as extensive multistability whereby infinitely many stable partially synchronized states exist. Our analysis sheds light on the complexity that can arise in physical systems with simplicial interactions like the human brain and the role that simplicial interactions play in storing information.

Multiplex social ecological network analysis reveals how social changes affect community robustness more than resource depletion.

Network analysis provides a powerful tool to analyze complex influences of social and ecological structures on community and household dynamics. Most network studies of social-ecological systems use simple, undirected, unweighted networks. We analyze multiplex, directed, and weighted networks of subsistence food flows collected in three small indigenous communities in Arctic Alaska potentially facing substantial economic and ecological changes. Our analysis of plausible future scenarios suggests that changes to social relations and key households have greater effects on community robustness than changes to specific wild food resources.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Navigability of interconnected networks under random failures.

Assessing the navigability of interconnected networks (transporting information, people, or goods) under eventual random failures is of utmost importance to design and protect critical infrastructures. Random walks are a good proxy to determine this navigability, specifically the coverage time of random walks, which is a measure of the dynamical functionality of the network. Here, we introduce the theoretical tools required to describe random walks in interconnected networks accounting for structure and dynamics inherent to real systems. We develop an analytical approach for the covering time of random walks in interconnected networks and compare it with extensive Monte Carlo simulations. Generally speaking, interconnected networks are more resilient to random failures than their individual layers per se, and we are able to quantify this effect. As an application--which we illustrate by considering the public transport of London--we show how the efficiency in exploring the multiplex critically depends on layers' topology, interconnection strengths, and walk strategy. Our findings are corroborated by data-driven simulations, where the empirical distribution of check-ins and checks-out is considered and passengers travel along fastest paths in a network affected by real disruptions. These findings are fundamental for further development of searching and navigability strategies in real interconnected systems.