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Towards Identifying and Predicting Spatial Epidemics on Complex Meta-population Networks

In the past decade, the network science community has witnessed huge advances in the threshold theory, prediction and control of epidemic dynamics on complex networks. While along with the understanding of spatial epidemics on meta-population networks achieved so far, more challenges have opened the...

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Detalles Bibliográficos
Autores principales: Li, Xiang, Wang, Jian-Bo, Li, Cong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122965/
http://dx.doi.org/10.1007/978-981-10-5287-3_6
Descripción
Sumario:In the past decade, the network science community has witnessed huge advances in the threshold theory, prediction and control of epidemic dynamics on complex networks. While along with the understanding of spatial epidemics on meta-population networks achieved so far, more challenges have opened the door to identify, retrospect, and predict the epidemic invasion process. This chapter reviews the recent progress towards identifying susceptible-infected compartment parameters and spatial invasion pathways on a meta-population network as well as the minimal case of two-subpopulation version, which may also extend to the prediction of spatial epidemics as well. The artificial and empirical meta-population networks verify the effectiveness of our proposed solutions to the concerned problems. Finally, the whole chapter concludes with the outlook of future research.