https://doi.org/10.1140/epjb/s10051-024-00675-7
Regular Article - Statistical and Nonlinear Physics
Rapid disease spread on dense networks with power-law topology
División de Control y Sistemas Dinámicos, Instituto Potosino de Investigación Científica y Tecnológica (IPICYT), Camino a la Presa San José 2055, San Luis Potosí, 78216, San Luis Potosí, México
Received:
18
November
2023
Accepted:
15
March
2024
Published online:
3
May
2024
Models of disease spread in networks typically focus on exploring various measures to reduce the spread of disease across individuals within a network. However, the topology of the underlying network plays an important role in determining the best time to implement mitigation measures to achieve better results. In this article we show the behavior of the well-known SIR (susceptible-infected-removed) and SIS (susceptible-infected-susceptible) models over networks with both scale-free and dense structure with power-law topology 
with 
. Focusing on the maximum number of infected individuals (
) and the number of days before it emerges, i.e., the speed at which infected individuals increase. We show that as the network structure becomes dense, i.e., the number of connections among the individuals within the network increases and 
approaches one, tends to be higher and it emerges rapidly. In those cases, implementing quick mitigation measures is very important. In this sense, we found that mitigation measures like social distancing can help to reduce the amount of infected individuals, specially when 
. Moreover, for bellow three, social distancing loses its effectiveness as mitigation measure.
J. J. Esquivel-Gómez and J. G. Barajas-Ramírez have contributed equally to this work.
Guest editors: Tiziana Di Matteo, Giorgio Kaniadakis, Antonio Scarfone, Gianpiero Gervino.
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© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
