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dc.contributor.author
González, Rafael I.  
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Moya, Pablo S.  
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Bringa, Eduardo Marcial  
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Bacigalupe, Gonzalo  
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Ramírez Santana, Muriel  
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Kiwi, Miguel  
dc.date.available
2024-07-17T11:58:10Z  
dc.date.issued
2023-06  
dc.identifier.citation
González, Rafael I.; Moya, Pablo S.; Bringa, Eduardo Marcial; Bacigalupe, Gonzalo; Ramírez Santana, Muriel; et al.; Model based on COVID-19 evidence to predict and improve pandemic control; Public Library of Science; Plos One; 18; 6; 6-2023; 1-16  
dc.identifier.issn
1932-6203  
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http://hdl.handle.net/11336/240158  
dc.description.abstract
Based on the extensive data accumulated during the COVID-19 pandemic, we put forward simple to implement indicators, that should alert authorities and provide early warnings of an impending sanitary crisis. In fact, Testing, Tracing, and Isolation (TTI) in conjunction with disciplined social distancing and vaccination were expected to achieve negligible COVID-19 contagion levels; however, they proved to be insufficient, and their implementation has led to controversial social, economic and ethical challenges. This paper focuses on the development of simple indicators, based on the experience gained by COVID-19 data, which provide a sort of yellow light as to when an epidemic might expand, despite some short term decrements. We show that if case growth is not stopped during the 7 to 14 days after onset, the growth risk increases considerably, and warrants immediate attention. Our model examines not only the COVID contagion propagation speed, but also how it accelerates as a function of time. We identify trends that emerge under the various policies that were applied, as well as their differences among countries. The data for all countries was obtained from ourworldindata.org. Our main conclusion is that if the reduction spread is lost during one, or at most two weeks, urgent measures should be implemented to avoid scenarios in which the epidemic gains strong impetus.  
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application/pdf  
dc.language.iso
eng  
dc.publisher
Public Library of Science  
dc.rights
info:eu-repo/semantics/openAccess  
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https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
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PANDEMIC CONTROL  
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MODEL  
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COVID-19  
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Epidemiología  
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Ciencias de la Salud  
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CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Model based on COVID-19 evidence to predict and improve pandemic control  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-07-16T12:24:48Z  
dc.journal.volume
18  
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6  
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1-16  
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Estados Unidos  
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San Francisco  
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Fil: González, Rafael I.. Universidad Mayor; Chile  
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Fil: Moya, Pablo S.. Universidad de Chile; Chile  
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Fil: Bringa, Eduardo Marcial. Universidad de Mendoza. Facultad de Ingenieria; Argentina. Universidad Mayor; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina  
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Fil: Bacigalupe, Gonzalo. Massachusetts Institute of Technology; Estados Unidos  
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Fil: Ramírez Santana, Muriel. Universidad Católica del Norte; Chile  
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Fil: Kiwi, Miguel. Universidad de Chile; Chile  
dc.journal.title
Plos One  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://dx.plos.org/10.1371/journal.pone.0286747  
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info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1371/journal.pone.0286747