From networked SIS model to the Gompertz function

@article{Estrada2022FromNS,
  title={From networked SIS model to the Gompertz function},
  author={Ernesto Estrada and Paolo Bartesaghi},
  journal={Appl. Math. Comput.},
  year={2022},
  volume={419},
  pages={126882}
}
1 Citations

Figures and Tables from this paper

Dynamic Model for Caragana korshinskii Shrub Aboveground Biomass Based on Theoretical and Allometric Growth Equations

As one of the ways to achieve carbon neutralization, shrub biomass plays an important role for natural resource management decision making in arid regions. To investigate biomass dynamic variations

References

SHOWING 1-10 OF 46 REFERENCES

A new Gompertz-type diffusion process with application to random growth.

Slow variation in the Gompertz model

TLDR
This investigation considers a particularly useful population model---the Gompertz model---in the case where the model parameters vary slowly with time, and multi-timing methods construct an approximate expression for the population that has the advantages of being both explicit and giving results comparable to those obtained from numerical calculations.

Collective dynamics of ‘small-world’ networks

TLDR
Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.

Comparison of the logistic and the Gompertz curve under different constraints

TLDR
A comparison between the Gompertz and the logistic curve has been performed to find out the more favorable curve in fitting the growth data.

Universality in COVID-19 spread in view of the Gompertz function

TLDR
It is demonstrated that universal scaling behavior is observed in the current coronavirus (COVID-19) spread in various countries and the recently proposed indicator so-called the K value, the increasing rate of infected people in one week, is found to show universal behavior.

Mixing patterns in networks.

  • M. Newman
  • Computer Science
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2003
TLDR
This work proposes a number of measures of assortative mixing appropriate to the various mixing types, and applies them to a variety of real-world networks, showing that assortsative mixing is a pervasive phenomenon found in many networks.

Transient Dynamics of Epidemic Spreading and Its Mitigation on Large Networks

TLDR
A theoretical framework is developed that allows for an accurate closed-form approximate solution to the original SI dynamics on any arbitrary network, which captures the temporal dynamics over all time and is tighter than the existing approximation, and also to provide a new interpretation via reliability theory.

Quantifying network heterogeneity.

  • Ernesto Estrada
  • Computer Science, Mathematics
    Physical review. E, Statistical, nonlinear, and soft matter physics
  • 2010
TLDR
It is shown that this heterogeneity index can be expressed as a quadratic form of the Laplacian matrix of the network, which allows a spectral representation of network heterogeneity and gives bounds for this index, which is equal to zero for any regular network and equal to one only for star graphs.

Degree heterogeneity of graphs and networks. I. Interpretation and the “heterogeneity paradox”

  • E. Estrada
  • Mathematics
    Journal of Interdisciplinary Mathematics
  • 2019
Abstract A series of new results about the degree heterogeneity index (Estrada, Phys. Rev. E, 82 (2010), 066102) are provided here using both analytical and computational methods. This index