90 citations · 165 across the 6 of their papers we have counts for
6 papers
Collapse transition in epidemic spreading subject to detection with limited resources
Santiago Lamata-Otín, Adriana Reyna-Lara, David Soriano-Paños +2
Compartmental models are the most widely used framework for modeling infectious diseases. These models have been continuously refined to incorporate all the realistic mechanisms th…
Quantifying the heterogeneous impact of lockdown policies on different socioeconomic classes during the first COVID-19 wave in Colombia
Pablo Valgañón, Andrés F. Useche, David Soriano-Paños +2
In the absence of vaccines, the most widespread reaction to curb COVID-19 pandemic worldwide was the implementation of lockdowns or stay-at-home policies. Despite the reported usef…
Explosive cooperation in social dilemmas on higher-order networks
Andrea Civilini, Onkar Sadekar, Federico Battiston +2
Understanding how cooperative behaviours can emerge from competitive interactions is an open problem in biology and social sciences. While interactions are usually modelled as pair…
Polarized opinion states in static networks driven by limited information horizons
Hugo Pérez-Martínez, F. Bauzá Mingueza, David Soriano-Paños +2
The widespread emergence of opinion polarization is often attributed to the rise of social media and the internet, which can promote selective exposure and the formation of echo ch…
Markovian approach to tackle the interaction of simultaneous diseases
David Soriano-Paños, Fakhteh Ghanbarnejad, Sandro Meloni +1
The simultaneous emergence of several abrupt disease outbreaks or the extinction of some serotypes of multi-strain diseases are fingerprints of the interaction between pathogens sp…
Explosive transitions induced by interdependent contagion-consensus dynamics in multiplex networks
David Soriano-Paños, Quantong Guo, Vito Latora +1
We introduce a model to study the delicate relation between the spreading of information and the formation of opinions in social systems. For this purpose, we propose a two-layer m…