Toward epidemic thresholds on temporal networks: a review and open questions

被引：30

作者：

Leitch, Jack ^{[1
]}

Alexander, Kathleen A. ^{[1
,2
]}

Sengupta, Srijan ^{[3
]}

机构：

[1] Virginia Tech, Dept Fish & Wildlife Conservat, Blacksburg, VA 24061 USA

[2] Ctr Conservat African Resources Anim Communities, CARACAL, Kasane, Botswana

[3] Virginia Tech, Dept Stat, Blacksburg, VA USA

来源：

APPLIED NETWORK SCIENCE | 2019年 / 4卷 / 01期

基金：

美国国家科学基金会;

关键词：

Temporal networks; Epidemiology; Epidemic threshold; LATENT SPACE MODELS; COMMUNITY DETECTION; CONTACT NETWORKS; RANDOM GRAPH; PATHOGEN TRANSMISSION; STATISTICAL-METHODS; INFECTIOUS AGENTS; HOST BEHAVIOR; SPREAD; COVARIATION;

D O I：

10.1007/s41109-019-0230-4

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

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