The evolution of depressive symptomatology across three waves of the COVID-19 pandemic: A 17-month representative longitudinal study of the adult population

This 17-month longitudinal study on a representative sample of 4,361 Norwegian adults employs an observational ABAB design across six repeated assessments and three pandemic waves to systematically investigate the evolution of depressive symptomatology across all modifications of viral mitigation protocols (VMPs) from their onset to termination. Using Latent Change Score Models to analyze 26,166 observations, the study empirically corroborates that critical fluctuations in depressive symptomatology within and across individuals occur during the first three months of the pandemic, after which symptom trajectories are predominantly consolidated throughout the pandemic period. Contrary to established belief, female sex, young age, lower education and preexisting psychiatric diagnosis only served as adequate predictors of the initial shocks to symptomatology observed during the onset of the pandemic, and did not adequately predict subsequent change and the critical fluctuations observed in symptoms within and across individuals. Population-level trajectories demonstrated that symptom levels increased in accordance with the presence and strictness of VMPs. Upon predominant termination of VMPs, population-level symptoms began declining, while large heterogeneity was present across the adult population. Detrimental long-term adversities were revealed by 10% of the adults. These individuals displayed chaotic adaptation to the pandemic and its VMPs, exhibiting substantial increases in clinical levels of symptomatology ensuing partial re-opening of society and through the remainder of the pandemic, with these deleterious symptoms further projected to remain heightened ahead. Number of times exposed to quarantine was incrementally tied with increases in contemporaneously experienced and long-term depressive adversities, while information obtainment through unmonitored sources was associated with contemporaneous but not long-term states of heightened symptomatology.

Self-Organised Critical Dynamics as a Key to Fundamental Features of Complexity in Physical, Biological, and Social Networks

Studies of many complex systems have revealed new collective behaviours that emerge through the mechanisms of self-organised critical fluctuations. Subject to the external and endogenous driving forces, these collective states with long-range spatial and temporal correlations often arise from the intrinsic dynamics with the threshold nonlinearity and geometry-conditioned interactions. The self-similarity of critical fluctuations enables us to describe the system using fewer parameters and universal functions that, on the other hand, can simplify the computational and information complexity. Currently, the cutting-edge research on self-organised critical systems across the scales strives to formulate a unifying mathematical framework, utilise the critical universal properties in information theory, and decipher the role of hidden geometry. As a prominent example, we study the field-driven spin dynamics on the hysteresis loop in a network with higher-order structures described by simplicial complexes, which provides a geometric-frustration environment. While providing motivational illustrations from physical, biological, and social systems, along with their networks, we also demonstrate how the self-organised criticality occurs at the interplay of the complex topology and driving mode. This study opens up new promising routes with powerful tools to address a long-standing challenge in the theory and applications of complexity science ingrained in the efficient analysis of self-organised critical states under the competing higher-order interactions embedded in complex geometries.

Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics

As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate $$\beta$$ β is not significantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, $$\beta > \beta _c$$ β > β c ) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, $$\beta < \beta _c$$ β < β c ) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with $$r(t) \approx 1$$ r ( t ) ≈ 1 hovering around its threshold value.

Nematic quantum criticality in an Fe-based superconductor revealed by strain-tuning

Quantum criticality may be essential to understanding a wide range of exotic electronic behavior; however, conclusive evidence of quantum critical fluctuations has been elusive in many materials of current interest. An expected characteristic feature of quantum criticality is power-law behavior of thermodynamic quantities as a function of a nonthermal tuning parameter close to the quantum critical point (QCP). Here, we observed power-law behavior of the critical temperature of the coupled nematic/structural phase transition as a function of uniaxial stress in a representative family of iron-based superconductors, providing direct evidence of quantum critical nematic fluctuations in this material. These quantum critical fluctuations are not confined within a narrow regime around the QCP but rather extend over a wide range of temperatures and compositions.

Quantum criticality in a layered iridate

Iridates provide a fertile ground to investigate correlated electrons in the presence of strong spin-orbit coupling. Bringing these systems to the proximity of a metal-insulator quantum phase transition is a challenge that must be met to access quantum critical fluctuations with charge and spin-orbital degrees of freedom. Here, electrical transport and Raman scattering measurements provide evidence that a metal-insulator quantum critical point is effectively reached in 5% Co-doped Sr2IrO4 with high structural quality. The dc-electrical conductivity shows a linear temperature dependence that is successfully captured by a model involving a Co acceptor level at the Fermi energy that becomes gradually populated at finite temperatures, creating thermally-activated holes in the Jeff = 1/2 lower Hubbard band. The so-formed quantum critical fluctuations are exceptionally heavy and the resulting electronic continuum couples with an optical phonon at all temperatures. The magnetic order and pseudospin-phonon coupling are preserved under the Co doping. This work brings quantum phase transitions, iridates and heavy-fermion physics to the same arena.

Self-Organized Criticality in Economic Fluctuations: The Age of Maturity

Self-Organized Criticality (SOC) has been proposed as a paradigm that may rationalize the emergence of macrofinancial fluctuations. The wave of innovative thinking sparked by this proposal continues to produce interesting contributions in many areas of economics, ranging from macroeconomics to finance. In this review, we propose a guided tour to these achievements, highlighting that analysis of SOC equilibria is a promising avenue to establish a nexus between i) a statistical equilibrium characterized by the spontaneous emergence of dynamic critical fluctuations and ii) a strategic equilibrium concept modeling a large number of interacting players. The critical state is the stable outcome arising from a trade-off between cooperation and competition.