About: Modeling and Predicting Human Infectious Diseases

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Modeling and Predicting Human Infectious Diseases
Creator	Perra, Nicola Gonçalves, Bruno
Source	PMC
abstract	The spreading of infectious diseases has dramatically shaped our history and society. The quest to understand and prevent their spreading dates more than two centuries. Over the years, advances in Medicine, Biology, Mathematics, Physics, Network Science, Computer Science, and Technology in general contributed to the development of modern epidemiology. In this chapter, we present a summary of different mathematical and computational approaches aimed at describing, modeling, and forecasting the diffusion of viruses. We start from the basic concepts and models in an unstructured population and gradually increase the realism by adding the effects of realistic contact structures within a population as well as the effects of human mobility coupling different subpopulations. Building on these concepts we present two realistic data-driven epidemiological models able to forecast the spreading of infectious diseases at different geographical granularities. We conclude by introducing some recent developments in diseases modeling rooted in the big-data revolution.
has issue date	2015-04-23(xsd:dateTime)
bibo:doi	10.1007/978-3-319-14011-7_4
has license	no-cc
sha1sum (hex)	dadda1b60e07ca4f6322f8ab772d2099d47be6e8
schema:url	https://doi.org/10.1007/978-3-319-14011-7_4
resource representing a document's title	Modeling and Predicting Human Infectious Diseases
has PubMed Central identifier	PMC7123706
schema:publication	Social Phenomena
resource representing a document's body	covid:dadda1b60e07ca4f6322f8ab772d2099d47be6e8#body_text
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