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Determining the key elements of interconnected infrastructure and complex systems is paramount to ensure system functionality and integrity. This work quantifies the dominance of the networks' nodes in their respective neighborhoods, introducing a centrality metric, DomiRank, that integrates local and global topological information via a tunable parameter. We present an analytical formula and an efficient parallelizable algorithm for DomiRank centrality, making it applicable to massive networks. From the networks' structure and function perspective, nodes with high values of DomiRank highlight fragile neighborhoods whose integrity and functionality are highly dependent on those dominant nodes. Underscoring this relation between dominance and fragility, we show that DomiRank systematically outperforms other centrality metrics in generating targeted attacks that effectively compromise network structure and disrupt its functionality for synthetic and real-world topologies. Moreover, we show that DomiRank-based attacks inflict more enduring damage in the network, hindering its ability to rebound and, thus, impairing system resilience. DomiRank centrality capitalizes on the competition mechanism embedded in its definition to expose the fragility of networks, paving the way to design strategies to mitigate vulnerability and enhance the resilience of critical infrastructures., (© 2024. The Author(s).)

Although ubiquitous, interactions in groups of individuals are not yet thoroughly studied. Frequently, single groups are modeled as critical-mass dynamics, which is a widespread concept used not only by academics but also by politicians and the media. However, less explored questions are how a collection of groups will behave and how their intersection might change the dynamics. Here, we formulate this process as binary-state dynamics on hypergraphs. We showed that our model has a rich behavior beyond discontinuous transitions. Notably, we have multistability and intermittency. We demonstrated that this phenomenology could be associated with community structures, where we might have multistability or intermittency by controlling the number or size of bridges between communities. Furthermore, we provided evidence that the observed transitions are hybrid. Our findings open new paths for research, ranging from physics, on the formal calculation of quantities of interest, to social sciences, where new experiments can be designed., (© 2023. The Author(s).)

Rumors and information spreading emerge naturally from human-to-human interactions and have a growing impact on our everyday life due to increasing and faster access to information, whether trustworthy or not. A popular mathematical model for spreading rumors, data, or news is the Maki-Thompson model. Mean-field approximations suggested that this model does not have a phase transition, with rumors always reaching a fraction of the population. Conversely, here, we show that a continuous phase transition is present in this model. Moreover, we explore a modified version of the Maki-Thompson model that includes a forgetting mechanism, changing the Markov chain's nature and allowing us to use a plethora of analytic and numeric methods. Particularly, we characterize the subcritical behavior, where the lifespan of a rumor increases as the spreading rate drops, following a power-law relationship. Our findings show that the dynamic behavior of rumor models is much richer than shown in previous investigations., (© 2022. The Author(s).)

In Tuberculosis (TB), given the complexity of its transmission dynamics, observations of reduced epidemiological risk associated with preventive interventions can be difficult to translate into mechanistic interpretations. Specifically, in clinical trials of vaccine efficacy, a readout of protection against TB disease can be mapped to multiple dynamical mechanisms, an issue that has been overlooked so far. Here, we describe this limitation and its effect on model-based evaluations of vaccine impact. Furthermore, we propose a methodology to analyze efficacy trials that circumvents it, leveraging a combination of compartmental models and stochastic simulations. Using our approach, we can disentangle the different possible mechanisms of action underlying vaccine protection effects against TB, conditioned to trial design, size, and duration. Our results unlock a deeper interpretation of the data emanating from efficacy trials of TB vaccines, which renders them more interpretable in terms of transmission models and translates into explicit recommendations for vaccine developers.

Plasmodium knowlesi is a zoonotic parasite transmitted from macaques causing malaria in humans in Southeast Asia. Plasmodium parasites bind to red blood cell (RBC) surface receptors, many of which are sialylated. While macaques synthesize the sialic acid variant N-glycolylneuraminic acid (Neu5Gc), humans cannot because of a mutation in the enzyme CMAH that converts N-acetylneuraminic acid (Neu5Ac) to Neu5Gc. Here we reconstitute CMAH in human RBCs for the reintroduction of Neu5Gc, which results in enhancement of P. knowlesi invasion. We show that two P. knowlesi invasion ligands, PkDBPβ and PkDBPγ, bind specifically to Neu5Gc-containing receptors. A human-adapted P. knowlesi line invades human RBCs independently of Neu5Gc, with duplication of the sialic acid-independent invasion ligand, PkDBPα and loss of PkDBPγ. Our results suggest that absence of Neu5Gc on human RBCs limits P. knowlesi invasion, but that parasites may evolve to invade human RBCs through the use of sialic acid-independent pathways.

While human societies are extraordinarily cooperative in comparison with other social species, the question of why we cooperate with unrelated individuals remains open. Here we report results of a lab-in-the-field experiment with people of different ages in a social dilemma. We find that the average amount of cooperativeness is independent of age except for the elderly, who cooperate more, and a behavioural transition from reciprocal, but more volatile behaviour to more persistent actions towards the end of adolescence. Although all ages react to the cooperation received in the previous round, young teenagers mostly respond to what they see in their neighbourhood regardless of their previous actions. Decisions then become more predictable through midlife, when the act of cooperating or not is more likely to be repeated. Our results show that mechanisms such as reciprocity, which is based on reacting to previous actions, may promote cooperation in general, but its influence can be hindered by the fluctuating behaviour in the case of children.

The macaque malaria parasite Plasmodium knowlesi has recently emerged as an important zoonosis in Southeast Asia. Infections are typically mild but can cause severe disease, achieving parasite densities similar to fatal Plasmodium falciparum infections. Here we show that a primate-adapted P. knowlesi parasite proliferates poorly in human blood due to a strong preference for young red blood cells (RBCs). We establish a continuous in vitro culture system by using human blood enriched for young cells. Mathematical modelling predicts that parasite adaptation for invasion of older RBCs is a likely mechanism leading to high parasite densities in clinical infections. Consistent with this model, we find that P. knowlesi can adapt to invade a wider age range of RBCs, resulting in proliferation in normal human blood. Such cellular niche expansion may increase pathogenesis in humans and will be a key feature to monitor as P. knowlesi emerges in human populations.