About: Self‐organized criticality in human epidemiology

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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	Self‐organized criticality in human epidemiology
Creator	Stollenwerk, Nico
Source	PMC
abstract	As opposed to most sociological fields, data are available in good quality for human epidemiology, describing the interaction between individuals being susceptible to or infected by a disease. Mathematically, the modelling of such systems is done on the level of stochastic master equations, giving likelihood functions for real live data. We show in a case study of meningococcal disease, that the observed large fluctuations of outbreaks of disease among the human population can be explained by the theory of accidental pathogens, leading the system towards a critical state, characterized by power laws in outbreak distributions. In order to make the extremely difficult parameter estimation close to a critical state with absorbing boundary possible, we investigate new algorithms for simulation of the disease dynamics on the basis of winner takes all strategies, and combine them with previously developed parameter estimation schemes.
has issue date	2005-07-20(xsd:dateTime)
bibo:doi	10.1063/1.2008613
bibo:pmid	32255878
has license	cc-by
sha1sum (hex)	69f740ed7b5f1e8b0f7c53156c578166d8abbe5e
schema:url	https://doi.org/10.1063/1.2008613
resource representing a document's title	Self‐organized criticality in human epidemiology
has PubMed Central identifier	PMC7108766
has PubMed identifier	32255878
schema:publication	AIP Conf Proc
resource representing a document's body	covid:69f740ed7b5f1e8b0f7c53156c578166d8abbe5e#body_text
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