About: Modeling COVID-19 epidemics in an Excel spreadsheet: Democratizing the access to first-hand accurate predictions of epidemic outbreaks

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Modeling COVID-19 epidemics in an Excel spreadsheet: Democratizing the access to first-hand accurate predictions of epidemic outbreaks Goto Sponge NotDistinct Permalink

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Modeling COVID-19 epidemics in an Excel spreadsheet: Democratizing the access to first-hand accurate predictions of epidemic outbreaks
Creator	González-González, Everardo Moisés Alvarez, Mario Trujillo-De Santiago, Grissel
Source	MedRxiv
abstract	COVID-19, the first pandemic of this decade and the second in less than 15 years, has harshly taught us that viral diseases do not recognize boundaries; however, they truly do discriminate between aggressive and mediocre containment responses. We present a simple epidemiological model that is amenable to implementation in Excel spreadsheets and sufficiently accurate to reproduce observed data on the evolution of the COVID-19 pandemics in different regions (i.e., Italy, Spain, and New York City (NYC)). We also show that the model can be adapted to closely follow the evolution of COVID-19 in any large city by simply adjusting two parameters related to (a) population density and (b) aggressiveness of the response from a society/government to epidemics. Moreover, we show that this simple epidemiological simulator can be used to assess the efficacy of the response of a government/society to an outbreak.
has issue date	2020-03-27(xsd:dateTime)
bibo:doi	10.1101/2020.03.23.20041590
has license	medrxiv
sha1sum (hex)	87591fa3e8ee53f63d931a69f0e936b7ee15e5c2
schema:url	https://doi.org/10.1101/2020.03.23.20041590
resource representing a document's title	Modeling COVID-19 epidemics in an Excel spreadsheet: Democratizing the access to first-hand accurate predictions of epidemic outbreaks
resource representing a document's body	covid:87591fa3e8ee53f63d931a69f0e936b7ee15e5c2#body_text
is schema:about of	named entity 'response' named entity 'Italy' named entity 'data' named entity 'Excel spreadsheet' named entity 'AMENABLE' named entity 'CITY' named entity 'PARAMETERS' named entity 'DATA' named entity 'PANDEMICS' named entity 'AGGRESSIVENESS' named entity 'REGIONS' named entity 'COVID-19' named entity 'Spain' named entity 'epidemics' named entity 'evolution' named entity 'COVID-19' named entity 'spreadsheets' named entity 'epidemic' named entity 'Excel' named entity 'spreadsheet' named entity 'Democratizing' named entity 'COVID-19' named entity 'Excel' named entity 'epidemic' named entity 'Madrid' named entity 'preprint' named entity 'New York City' named entity 'differential equations' named entity 'preprint' named entity 'asymptomatic' named entity 'medRxiv' named entity 'SARS' named entity 'New York City' named entity 'Tehran' named entity 'SARS-COV-2' named entity 'COVID' named entity 'COVID' named entity 'epidemiology' named entity 'asymptomatic' named entity 'influenza A/H1N1' named entity 'asymptomatic' named entity 'epidemic' named entity 'preprint' named entity 'CC-BY-NC-ND 4.0' named entity 'evolution' named entity 'New York City' named entity 'Iran' named entity '21 days' named entity 'time series' named entity 'Tehran' named entity 'New York City' named entity 'preprint' named entity 'evolution' named entity 'Pittsburgh' named entity 'COVID-19' named entity 'preprint' named entity 'exponential phase' named entity 'epidemics' named entity 'South Korea' named entity 'epidemiological model' named entity 'epidemic' named entity 'immune response' named entity 'Spain' named entity 'preprint' named entity 'Iran' named entity 'COVID' named entity 'preprint' named entity 'preprint' named entity 'medRxiv' named entity 'Spain' named entity 'epidemics' named entity 'medRxiv' named entity 'peer review' named entity 'Spain' named entity 'preprint' named entity 'mortality rate' named entity 'Monterrey' named entity 'medRxiv' named entity 'preprint' named entity 'COVID-19 infection' named entity 'Iran' named entity 'epidemics' named entity 'epidemic'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software