Muhua Zheng, Wei Wang, Ming Tang, Jie Zhou, Stefano Boccaletti and Zonghua Liu discovered new features of two (or multiple) peak epidemic patterns and developed an edge-based theory to explain the numerical results. The authors used measles data from Project Tycho and the results can be applied to disease forecasting as well as the prevention of secondary disease epidemics.
Related Project Tycho Datasets
United States of America - Measles
The study of epidemic spreading on populations of networked individuals has seen recently a great deal of significant progresses. A common point of all past studies is, however, that there is only one peak of infected density in each single epidemic spreading episode. At variance, real data from different cities over the world suggest that, besides a major single peak trait of infected density, a finite probability exists for a pattern made of two (or multiple) peaks. We show that such a latter feature is fully distinctive of a multilayered network of interactions, and reveal that actually a two peaks pattern emerges from different time delays at which the epidemic spreads in between the two layers. Further, we show that essential ingredients are different degree distributions in the two layers and a weak coupling condition between the layers themselves. Moreover, an edge-based theory is developed which fully explains all numerical results. Our findings may therefore be of significance for protecting secondary disasters of epidemics, which are definitely undesired in real life.
Read the full article