About: Modelling death rates due to COVID-19: A Bayesian approach

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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	Modelling death rates due to COVID-19: A Bayesian approach
Creator	Bayes, Cristian Sal Y Rosas, Giancarlo Valdivieso, Luis
source	ArXiv
abstract	Objective: To estimate the number of deaths in Peru due to COVID-19. Design: With a priori information obtained from the daily number of deaths due to CODIV-19 in China and data from the Peruvian authorities, we constructed a predictive Bayesian non-linear model for the number of deaths in Peru. Exposure: COVID-19. Outcome: Number of deaths. Results: Assuming an intervention level similar to the one implemented in China, the total number of deaths in Peru is expected to be 612 (95%CI: 604.3 - 833.7) persons. Sixty four days after the first reported death, the 99% of expected deaths will be observed. The inflexion point in the number of deaths is estimated to be around day 26 (95%CI: 25.1 - 26.8) after the first reported death. Conclusion: These estimates can help authorities to monitor the epidemic and implement strategies in order to manage the COVID-19 pandemic.
has issue date	2020-04-06(xsd:dateTime)
has license	arxiv
sha1sum (hex)	d3bf2b6f10dbe7ba6f218a8d5696b9e6bb7adb44
resource representing a document's title	Modelling death rates due to COVID-19: A Bayesian approach
resource representing a document's body	covid:d3bf2b6f10dbe7ba6f218a8d5696b9e6bb7adb44#body_text
is schema:about of	named entity 'death rates' named entity '833' named entity 'RESULTS' named entity 'CHINA' named entity 'INFORMATION' »more»

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