About: Coupled disease–behavior dynamics on complex networks: A review

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Coupled disease–behavior dynamics on complex networks: A review
Creator	Wang, Zhen Wang, Lin Wu, Zhi-Xi Bauch, Chris Andrews, Michael
topic	covid:50fa01990b8405f86066ae116511615d2ab3a01c#this
Source	Elsevier; Medline; PMC
abstract	It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease–behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease–behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.
has issue date	2015-07-08(xsd:dateTime)
bibo:doi	10.1016/j.plrev.2015.07.006
bibo:pmid	26211717
has license	no-cc
sha1sum (hex)	50fa01990b8405f86066ae116511615d2ab3a01c
schema:url	https://doi.org/10.1016/j.plrev.2015.07.006
resource representing a document's title	Coupled disease–behavior dynamics on complex networks: A review
has PubMed Central identifier	PMC7105224
has PubMed identifier	26211717
schema:publication	Phys Life Rev
resource representing a document's body	covid:50fa01990b8405f86066ae116511615d2ab3a01c#body_text
is http://vocab.deri.ie/void#inDataset of	https://covidontheweb.inria.fr:4443/about/id/http/ns.inria.fr/covid19/50fa01990b8405f86066ae116511615d2ab3a01c
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