About: Application of COVID-19 pneumonia diffusion data to predict epidemic situation

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Application of COVID-19 pneumonia diffusion data to predict epidemic situation
source	MedRxiv
abstract	Objective: To evaluate novel coronavirus pneumonia cases by establishing the mathematical model of the number of confirmed cases daily, and to assess the current situation and development of the epidemic situation, so as to provide a digital basis for decision-making. Methods: The number of newly confirmed covid-19 cases per day was taken as the research object, and the seven-day average value (M)) and the sequential value (R) of M were calculated to study the occurrence and development of covid-19 epidemic through the analysis of charts and data. Results: M reflected the current situation of epidemic development; R reflected the current level of infection and the trend of epidemic development. Conclusion: The current data can be used to evaluate the number of people who have been infected, and when R < 1, the peak of epidemic can be predicted.
has issue date	2020-04-14(xsd:dateTime)
bibo:doi	10.1101/2020.04.11.20061432
has license	medrxiv
sha1sum (hex)	24cbb530b13194a5af02a3e537fb02b7f3963e8a
schema:url	https://doi.org/10.1101/2020.04.11.20061432
resource representing a document's title	Application of COVID-19 pneumonia diffusion data to predict epidemic situation
resource representing a document's body	covid:24cbb530b13194a5af02a3e537fb02b7f3963e8a#body_text
is schema:about of	named entity 'decision-making' named entity 'CURRENT' named entity 'mathematical model' named entity 'mathematical model' named entity 'epidemic' »more»

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