Individual risk-aversion responses tune epidemics to critical transmissibility (R = 1).

Changes in human behaviour are a major determinant of epidemic dynamics. Collective activity can be modified through imposed control measures, but spontaneous changes can also arise as a result of uncoordinated individual responses to the perceived risk of contagion. Here, we introduce a stochastic epidemic model implementing population responses driven by individual time-varying risk aversion. The model reveals an emergent mechanism for the generation of multiple infection waves of decreasing amplitude that progressively tune the effective reproduction number to its critical value R = 1. In successive waves, individuals with gradually lower risk propensity are infected. The overall mechanism shapes well-defined risk-aversion profiles over the whole population as the epidemic progresses. We conclude that uncoordinated changes in human behaviour can by themselves explain major qualitative and quantitative features of the epidemic process, like the emergence of multiple waves and the tendency to remain around R = 1 observed worldwide after the first few waves of COVID-19.

Heaps' Law and Heaps functions in tagged texts: evidences of their linguistic relevance.

We study the relationship between vocabulary size and text length in a corpus of 75 literary works in English, authored by six writers, distinguishing between the contributions of three grammatical classes (or 'tags,' namely, nouns, verbs and others), and analyse the progressive appearance of new words of each tag along each individual text. We find that, as prescribed by Heaps' Law, vocabulary sizes and text lengths follow a well-defined power-law relation. Meanwhile, the appearance of new words in each text does not obey a power law, and is on the whole well described by the average of random shufflings of the text. Deviations from this average, however, are statistically significant and show systematic trends across the corpus. Specifically, we find that the appearance of new words along each text is predominantly retarded with respect to the average of random shufflings. Moreover, different tags add systematically distinct contributions to this tendency, with verbs and others being respectively more and less retarded than the mean trend, and nouns following instead the overall mean. These statistical systematicities are likely to point to the existence of linguistically relevant information stored in the different variants of Heaps' Law, a feature that is still in need of extensive assessment.

Fat tails and black swans: Exact results for multiplicative processes with resets.

We consider a class of multiplicative processes which, added with stochastic reset events, give origin to stationary distributions with power-law tails-ubiquitous in the statistics of social, economic, and ecological systems. Our main goal is to provide a series of exact results on the dynamics and asymptotic behavior of increasingly complex versions of a basic multiplicative process with resets, including discrete and continuous-time variants and several degrees of randomness in the parameters that control the process. In particular, we show how the power-law distributions are built up as time elapses, how their moments behave with time, and how their stationary profiles become quantitatively determined by those parameters. Our discussion emphasizes the connection with financial systems, but these stochastic processes are also expected to be fruitful in modeling a wide variety of social and biological phenomena.

Cooperative action of coherent groups in broadly heterogeneous populations of interacting chemical oscillators.

We present laboratory experiments on the effects of global coupling in a population of electrochemical oscillators with a multimodal frequency distribution. The experiments show that complex collective signals are generated by this system through spontaneous emergence and joint operation of coherently acting groups representing hierarchically organized resonant clusters. Numerical simulations support these experimental findings. Our results suggest that some forms of internal self-organization, characteristic for complex multiagent systems, are already possible in simple chemical systems.

Critical behavior of propagation on small-world networks.

We report numerical evidence that an epidemiclike model, which can be interpreted as the propagation of a rumor, exhibits critical behavior at a finite randomness of the underlying small-world network. The transition occurs between a regime where the rumor "dies" in a small neighborhood of its origin, and a regime where it spreads over a finite fraction of the whole population. Critical exponents are evaluated through finite-size scaling analysis, and the dependence of the critical randomness with the network connectivity is studied. The behavior of this system as a function of the small-network randomness bears noticeable similarities with an epidemiological model reported recently [M. Kuperman and G. Abramson, Phys. Rev. Lett. 86, 2909 (2001)], in spite of substantial differences in the respective dynamical rules.

Synchronization of Kauffman networks.

We analyze the synchronization transition for a pair of coupled identical Kauffman networks in the chaotic phase. The annealed model for Kauffman networks shows that synchronization appears through a transcritical bifurcation and provides an approximate description for the whole dynamics of the coupled networks. We show that these analytical predictions are in good agreement with numerical results for sufficiently large networks and study finite-size effects in detail. Preliminary analytical and numerical results for partially disordered networks are also presented.

On the genealogy of a population of biparental individuals.

If one goes backward in time, the number of ancestors of an individual doubles at each generation. This exponential growth very quickly exceeds the population size, when this size is finite. As a consequence, the ancestors of a given individual cannot be all different and most remote ancestors are repeated many times in any genealogical tree. The statistical properties of these repetitions in genealogical trees of individuals for a panmictic closed population of constant size N can be calculated. We show that the distribution of the repetitions of ancestors reaches a stationary shape after a small number G(c) approximately log N of generations in the past, that only about 80% of the ancestral population belongs to the tree (due to coalescence of branches), and that two trees for individuals in the same population become identical after G(c)generations have elapsed. Our analysis is easy to extend to the case of exponentially growing population.

Stochastic multiplicative processes with reset events.

We study a stochastic multiplicative process with reset events. It is shown that the model develops a stationary power-law probability distribution for the relevant variable, whose exponent depends on the model parameters. Two qualitatively different regimes are observed, corresponding to intermittent and regular behavior. In the boundary between them, the mean value of the relevant variable is time independent, and the exponent of the stationary distribution equals -2. The addition of diffusion to the system modifies in a nontrivial way the profile of the stationary distribution. Numerical and analytical results are presented.

Noise-induced breakdown of coherent collective motion in swarms.

We consider swarms formed by populations of self-propelled particles with attractive long-range interactions. These swarms represent multistable dynamical systems and can be found either in coherent traveling states or in an incoherent oscillatory state where translational motion of the entire swarm is absent. Under increasing the noise intensity, the coherent traveling state of the swarms is destroyed and an abrupt transition to the oscillatory state takes place.

Experimental evidence of power-law trapping-time distributions in porous media.

We present experimental results of solute transport in porous samples made of packings of activated carbon porous grains. Exchange experiments, where the tagged solution initially saturating the medium is replaced with the same solution without tracer, are accurately described by macroscopic transport equations. On the other hand, in desorption experiments, where the tagged solution is replaced by water, the solute concentration exhibits a power-law decay for long times, which requires a more detailed, mesoscopic description. We reproduce this behavior within a continuous-time random-walk approach, where the waiting time distribution is related to the desorption isotherm. Results are compatible with a power-law trapping time distribution with divergent first moment, characteristic of anomalous (sub)diffusion.