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.

Spreading dynamics in networks under context-dependent behavior.

In some systems, the behavior of the constituent units can create a "context" that modifies the direct interactions among them. This mechanism of indirect modification inspired us to develop a minimal model of context-dependent spreading. In our model, agents actively impede (favor) or not diffusion during an interaction, depending on the behavior they observe among all the peers in the group within which that interaction occurs. We divide the population into two behavioral types and provide a mean-field theory to parametrize mixing patterns of arbitrary type-assortativity within groups of any size. As an application, we examine an epidemic-spreading model with context-dependent adoption of prophylactic tools such as face masks. By analyzing the distributions of groups' size and type-composition, we uncover a rich phenomenology for the basic reproduction number and the endemic state. We analytically show how changing the group organization of contacts can either facilitate or hinder epidemic spreading, eventually moving the system from the subcritical to the supercritical phase and vice versa, depending mainly on sociological factors, such as whether the prophylactic behavior is hardly or easily induced. More generally, our work provides a theoretical foundation to model higher-order contexts and analyze their dynamical implications, envisioning a broad theory of context-dependent interactions that would allow for a new systematic investigation of a variety of complex systems.

Analysis of SARS-CoV-2 in wastewater for prevalence estimation and investigating clinical diagnostic test biases.

Here we analyze SARS-CoV-2 genome copies in Catalonia's wastewater during the Omicron peak and develop a mathematical model to estimate the number of infections and the temporal relationship between reported and unreported cases. 1-liter samples from 16 wastewater treatment plants were collected and used in a compartmental epidemiological model. The average correlation between genome copies and reported cases was 0.85, with an average delay of 8.8 days. The model estimated that 53% of the population was infected, compared to the 19% reported cases. The under-reporting was highest in November and December 2021. The maximum genome copies shed in feces by an infected individual was estimated to range from 1.4×108 gc/g to 4.4×108 gc/g. Our framework demonstrates the potential of wastewater data as a leading indicator for daily new infections, particularly in contexts with low detection rates. It also serves as a complementary tool for prevalence estimation and offers a general approach for integrating wastewater data into compartmental models.

Joint Analysis of the Epidemic Evolution and Human Mobility During the First Wave of COVID-19 in Spain: Retrospective Study.

BACKGROUND: The initial wave of the COVID-19 pandemic placed a tremendous strain on health care systems worldwide. To mitigate the spread of the virus, many countries implemented stringent nonpharmaceutical interventions (NPIs), which significantly altered human behavior both before and after their enactment. Despite these efforts, a precise assessment of the impact and efficacy of these NPIs, as well as the extent of human behavioral changes, remained elusive. OBJECTIVE: In this study, we conducted a retrospective analysis of the initial wave of COVID-19 in Spain to better comprehend the influence of NPIs and their interaction with human behavior. Such investigations are vital for devising future mitigation strategies to combat COVID-19 and enhance epidemic preparedness more broadly. METHODS: We used a combination of national and regional retrospective analyses of pandemic incidence alongside large-scale mobility data to assess the impact and timing of government-implemented NPIs in combating COVID-19. Additionally, we compared these findings with a model-based inference of hospitalizations and fatalities. This model-based approach enabled us to construct counterfactual scenarios that gauged the consequences of delayed initiation of epidemic response measures. RESULTS: Our analysis demonstrated that the pre-national lockdown epidemic response, encompassing regional measures and heightened individual awareness, significantly contributed to reducing the disease burden in Spain. The mobility data indicated that people adjusted their behavior in response to the regional epidemiological situation before the nationwide lockdown was implemented. Counterfactual scenarios suggested that without this early epidemic response, there would have been an estimated 45,400 (95% CI 37,400-58,000) fatalities and 182,600 (95% CI 150,400-233,800) hospitalizations compared to the reported figures of 27,800 fatalities and 107,600 hospitalizations, respectively. CONCLUSIONS: Our findings underscore the significance of self-implemented prevention measures by the population and regional NPIs before the national lockdown in Spain. The study also emphasizes the necessity for prompt and precise data quantification prior to enacting enforced measures. This highlights the critical interplay between NPIs, epidemic progression, and human behavior. This interdependence presents a challenge in predicting the impact of NPIs before they are implemented.

Characterization of interactions' persistence in time-varying networks.

Many complex networked systems exhibit volatile dynamic interactions among their vertices, whose order and persistence reverberate on the outcome of dynamical processes taking place on them. To quantify and characterize the similarity of the snapshots of a time-varying network-a proxy for the persistence,-we present a study on the persistence of the interactions based on a descriptor named temporality. We use the average value of the temporality, [Formula: see text], to assess how "special" is a given time-varying network within the configuration space of ordered sequences of snapshots. We analyse the temporality of several empirical networks and find that empirical sequences are much more similar than their randomized counterparts. We study also the effects on [Formula: see text] induced by the (time) resolution at which interactions take place.

A link model approach to identify congestion hotspots.

Congestion emerges when high demand peaks put transportation systems under stress. Understanding the interplay between the spatial organization of demand, the route choices of citizens and the underlying infrastructures is thus crucial to locate congestion hotspots and mitigate the delay. Here we develop a model where links are responsible for the processing of vehicles, which can be solved analytically before and after the onset of congestion, and provide insights into the global and local congestion. We apply our method to synthetic and real transportation networks, observing a strong agreement between the analytical solutions and the Monte Carlo simulations, and a reasonable agreement with the travel times observed in 12 cities under congested phase. Our framework can incorporate any type of routing extracted from real trajectory data to provide a more detailed description of congestion phenomena, and could be used to dynamically adapt the capacity of road segments according to the flow of vehicles, or reduce congestion through hotspot pricing.

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'.

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.

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.

Percolation in networks with local homeostatic plasticity.

Percolation is a process that impairs network connectedness by deactivating links or nodes. This process features a phase transition that resembles paradigmatic critical transitions in epidemic spreading, biological networks, traffic and transportation systems. Some biological systems, such as networks of neural cells, actively respond to percolation-like damage, which enables these structures to maintain their function after degradation and aging. Here we study percolation in networks that actively respond to link damage by adopting a mechanism resembling synaptic scaling in neurons. We explain critical transitions in such active networks and show that these structures are more resilient to damage as they are able to maintain a stronger connectedness and ability to spread information. Moreover, we uncover the role of local rescaling strategies in biological networks and indicate a possibility of designing smart infrastructures with improved robustness to perturbations.

Reflexiones sobre cómo evaluar y mejorar la respuesta a la pandemia de COVID-19 / Insight on how to assess and improve the response to the COVID-19 pandemic

La pandemia de COVID-19ha afectado de manera particularmente intensa a España, pese a su nivel de desarrollo y la elogiada solidez de su Sistema Nacional de Salud. Para comprender qué ha pasado e identificar cómo mejorar la respuesta creemos imprescindible una evaluación independiente multidisciplinaria de la esfera sanitaria, política y socioeconómica. En este trabajo proponemos objetivos, principios, metodología y dimensiones a evaluar, además de esbozar el tipo de resultados y conclusiones esperadas. Nos inspiramos en los requerimientos formulados por el panel independiente de la Organización Mundial de la Salud y en las experiencias evaluativas en otros países, y detallamos la propuesta de aspectos multidimensionales que deben valorarse. La idea es comprender aspectos clave en los ámbitos estudiados y su margen de mejora en lo relativo a preparación, gobernanza, marco normativo, estructuras del Sistema Nacional de Salud (atención primaria, hospitalaria y de salud pública), sector de educación, esquemas de protección social, minimización del impacto económico, y marco y reformas en el ámbito laboral para una sociedad más resiliente. En definitiva, buscamos que este ejercicio sirva no solo para el presente, sino también para que en el futuro estemos mejor preparados y con más ágil capacidad de recuperación ante las amenazas pandémicas que puedan surgir. (AU)

The COVID-19 pandemic has hit Spain particularly hard, despite being a country with a developed economy and being praised for the robustness of its national health system. In order to understand what happened and to identify how to improve the response, we believe that an independent multi-disciplinary evaluation of the health, political and socio-economic spheres is essential. In this piece we propose objectives, principles, methodology and dimensions to be evaluated, as well as outlining the type of results and conclusions expected. Inspired by the requirements formulated by the WHO Independent Panel for Pandemic Preparedness and Response and by experiences in other countries, we detail the multidimensional aspects to be evaluated. The goal is to understand key aspects in the studied areas and their scope for improvement in terms of preparedness, governance, regulatory framework, national health system structures (primary care, hospital, and public health), education sector, social protection schemes, minimization of economic impact, and labour framework and reforms for a more resilient society. We seek to ensure that this exercise serves not only at present, but also that in the future we are better prepared and more agile in terms of our ability to recover from any pandemic threats that may arise. (AU)

[Insight on how to assess and improve the response to the COVID-19 pandemic]. / Reflexiones sobre cómo evaluar y mejorar la respuesta a la pandemia de COVID-19.

The COVID-19 pandemic has hit Spain particularly hard, despite being a country with a developed economy and being praised for the robustness of its national health system. In order to understand what happened and to identify how to improve the response, we believe that an independent multi-disciplinary evaluation of the health, political and socio-economic spheres is essential. In this piece we propose objectives, principles, methodology and dimensions to be evaluated, as well as outlining the type of results and conclusions expected. Inspired by the requirements formulated by the WHO Independent Panel for Pandemic Preparedness and Response and by experiences in other countries, we detail the multidimensional aspects to be evaluated. The goal is to understand key aspects in the studied areas and their scope for improvement in terms of preparedness, governance, regulatory framework, national health system structures (primary care, hospital, and public health), education sector, social protection schemes, minimization of economic impact, and labour framework and reforms for a more resilient society. We seek to ensure that this exercise serves not only at present, but also that in the future we are better prepared and more agile in terms of our ability to recover from any pandemic threats that may arise.

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'.

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.

Connecting intercity mobility with urban welfare.

While significant effort has been devoted to understand the role of intraurban characteristics on sustainability and growth, much remains to be understood about the effect of interurban interactions and the role cities have in determining each other's urban welfare. Here we consider a global mobility network of population flows between cities as a proxy for the communication between these regions, and analyze how it correlates with socioeconomic indicators. We use several measures of centrality to rank cities according to their importance in the mobility network, finding PageRank to be the most effective measure for reflecting these prosperity indicators. Our analysis reveals that the characterization of the welfare of cities based on mobility information hinges on their corresponding development stage. Namely, while network-based predictions of welfare correlate well with economic indicators in mature cities, for developing urban areas additional information about the prosperity of their mobility neighborhood is needed. We develop a simple generative model for the allocation of population flows out of a city that balances the costs and benefits of interaction with other cities that are successful, finding that it provides a strong fit to the flows observed in the global mobility network and highlights the differences in flow patterns between developed and developing urban regions. Our results hint towards the importance of leveraging interurban connections in service of urban development and welfare.

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.

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.

Management of Biliopancreatic Limb Bleeding after Roux-en-Y Gastric Bypass: A Case Report.

The Roux-en-Y gastric bypass is one of the most extensive surgical treatments for obesity. The treatment of upper gastrointestinal bleeding after Roux-en-Y gastric bypass is complex due to the difficulty of accessing the excluded gastric antrum and duodenal bulb. There is no consensus regarding the management of this complication. While various techniques have been described to access the biliopancreatic limb, double-balloon enteroscopy is the most commonly used. If double-balloon enteroscopy is unavailable, a pediatric colonoscope may be used as an alternative; however, its use in such cases has not been described. We report the case of a 50-year-old male patient who underwent gastric bypass 13 years ago and was admitted for a second episode of upper gastrointestinal bleeding. The initial approach using upper endoscopy, colonoscopy, and abdominal computed tomography angiography did not reveal the cause of gastrointestinal hemorrhage; therefore, an endoscopic study of the biliopancreatic limb was performed using a pediatric colonoscope. A Forrest Ib ulcer was found in the duodenal bulb, and endoscopic therapy was administered. The evolution was found to be satisfactory.