scholarly journals Communicating uncertainty in epidemic models

Epidemics ◽  
2021 ◽  
pp. 100520
Author(s):  
Ruth McCabe ◽  
Mara D. Kont ◽  
Nora Schmit ◽  
Charles Whittaker ◽  
Alessandra Løchen ◽  
...  
Keyword(s):  
Epidemic Models

scholarly journals Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

2021 ◽  
Vol 13 (3) ◽  
pp. 76
Author(s):  
Quintino Francesco Lotito ◽  
Davide Zanella ◽  
Paolo Casari
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Simulation Models ◽  
Epidemic Models ◽  
Time Varying ◽  
Fake News ◽  
Network Access ◽  
Spreading Process ◽  
Network Topologies ◽  
Access Patterns

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading.

Runge–Kutta pairs suited for SIR‐type epidemic models

2020 ◽  
Author(s):  
Vladislav N. Kovalnogov ◽  
Theodore E. Simos ◽  
Charalampos Tsitouras
Keyword(s):  
Epidemic Models ◽  
Runge Kutta

scholarly journals Applications of the Poincare-Hopf Theorem: Epidemic Models and Lotka-Volterra Systems

2021 ◽  
pp. 1-1
Author(s):  
Mengbin Ye ◽  
Ji Liu ◽  
Brian D.O. Anderson ◽  
Ming Cao
Keyword(s):  
Epidemic Models ◽  
Volterra Systems ◽  
Hopf Theorem

A new look at the simple epidemic process

1979 ◽  
Vol 16 (01) ◽  
pp. 198-202 ◽  
Author(s):  
L. Billard ◽  
H. Lacayo ◽  
N. A. Langberg
Keyword(s):  
Waiting Times ◽  
Classical Model ◽  
Epidemic Models ◽  
Underlying Structure ◽  
Epidemic Process ◽  
Insight Into ◽  
New Look

Classical epidemic models have invariably proved to be mathematically intractable. By considering the distribution of the number of infectives in a simple epidemic process as a convolution of exponential waiting times, the solution to the classical model is obtained easily giving more insight into the underlying structure. The idea can be extended to other simple epidemic models.

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