About: Methods to Determine the End of an Infectious Disease Epidemic: A Short 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	Methods to Determine the End of an Infectious Disease Epidemic: A Short Review
Creator	Nishiura, Hiroshi
Source	PMC
abstract	Deciding the end of an epidemic is frequently associated with forthcoming changes in infectious disease control activities, including downgrading alert level in surveillance and restoring healthcare workers’ working shift back to normal. Despite the practical importance, there have been little epidemiological and laboratory methods that were proposed to determine the end of an epidemic. This short review was aimed to systematically discuss methodological principles of a small number of existing techniques and understand their advantages and disadvantages. Existing epidemiological methods have been mostly limited to a single-and-brief exposure setting, while the application to human-to-human transmissible disease epidemic with stochastic dependence structure in the observed case data has remained to be a statistical challenge. In veterinary applications, a large-scale sampling for laboratory testing has been commonly adapted to substantiate a freedom from disease, but such study has only accounted for binomial sampling process in estimating the error probability of elimination. Surveillance and mathematical modeling are two complementary instruments in the toolbox of epidemiologists. Combining their strengths would be highly beneficial to better define the end of an epidemic.
has issue date	2016-07-28(xsd:dateTime)
bibo:doi	10.1007/978-3-319-40413-4_17
has license	no-cc
sha1sum (hex)	34f138e39337da19b45e22d8bdfa9c633be44b39
schema:url	https://doi.org/10.1007/978-3-319-40413-4_17
resource representing a document's title	Methods to Determine the End of an Infectious Disease Epidemic: A Short Review
has PubMed Central identifier	PMC7123060
schema:publication	Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases
resource representing a document's body	covid:34f138e39337da19b45e22d8bdfa9c633be44b39#body_text
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