Introduction to Temporal Network Epidemiology

Author(s):  
Naoki Masuda ◽  
Petter Holme
2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Yuan Bai ◽  
Bo Yang ◽  
Lijuan Lin ◽  
Jose L. Herrera ◽  
Zhanwei Du ◽  
...  

2019 ◽  
Vol 7 (1) ◽  
pp. 52-69 ◽  
Author(s):  
Petter Holme ◽  
Luis E. C. Rocha

AbstractWe investigate the impact of misinformation about the contact structure on the ability to predict disease outbreaks. We base our study on 31 empirical temporal networks and tune the frequencies in errors in the node identities or time stamps of contacts. We find that for both these spreading scenarios, the maximal misprediction of both the outbreak size and time to extinction follows an stretched exponential convergence as a function of the error frequency. We furthermore determine the temporal-network structural factors influencing the parameters of this convergence.


2021 ◽  
Vol 18 (179) ◽  
pp. 20210019
Author(s):  
Naoki Masuda ◽  
Joel C. Miller ◽  
Petter Holme

Diseases spread over temporal networks of interaction events between individuals. Structures of these temporal networks hold the keys to understanding epidemic propagation. One early concept of the literature to aid in discussing these structures is concurrency—quantifying individuals’ tendency to form time-overlapping ‘partnerships’. Although conflicting evaluations and an overabundance of operational definitions have marred the history of concurrency, it remains important, especially in the area of sexually transmitted infections. Today, much of theoretical epidemiology uses more direct models of contact patterns, and there is an emerging body of literature trying to connect methods to the concurrency literature. In this review, we will cover the development of the concept of concurrency and these new approaches.


2020 ◽  
Author(s):  
Ariel L Rivas ◽  
Jose Febles Patron ◽  
Steve D. Smith ◽  
Folorunso Fasina ◽  
James B. Hittner

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