About: Spatial infectious disease epidemiology: on the cusp

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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	Spatial infectious disease epidemiology: on the cusp
Creator	Chowell, G Rothenberg, R
Source	PMC
abstract	Infectious diseases continue to pose a significant public health burden despite the great progress achieved in their prevention and control over the last few decades. Our ability to disentangle the factors and mechanisms driving their propagation in space and time has dramatically advanced in recent years. The current era is rich in mathematical and computational tools and detailed geospatial information, including sociodemographic, geographic, and environmental data, which are essential to elucidate key drivers of infectious disease transmission from epidemiological and genetic data. Indeed, this paradigm shift was driven by dramatic advances in complex systems approaches along with substantial improvements in data availability and computational power. The burgeoning output of infectious disease spatial modeling suggests that we are close to a fully integrated approach for early epidemic detection and intervention. This special collection in BMC Medicine aims to bring together a broad range of quantitative investigations that improve our understanding of the spatiotemporal transmission dynamics of infectious diseases in order to mitigate their impact on the human population.
has issue date	2018-10-18(xsd:dateTime)
bibo:doi	10.1186/s12916-018-1184-6
bibo:pmid	30333024
has license	cc-by
sha1sum (hex)	ed31dd4b98138fa11aef81a8d21f01d9b572bb39
schema:url	https://doi.org/10.1186/s12916-018-1184-6
resource representing a document's title	Spatial infectious disease epidemiology: on the cusp
has PubMed Central identifier	PMC6193292
has PubMed identifier	30333024
schema:publication	BMC Med
resource representing a document's body	covid:ed31dd4b98138fa11aef81a8d21f01d9b572bb39#body_text
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