Cargando…

Model based on COVID-19 evidence to predict and improve pandemic control

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 distanc...

Descripción completa

Detalles Bibliográficos
Autores principales: González, Rafael I., Moya, Pablo S., Bringa, Eduardo M., Bacigalupe, Gonzalo, Ramírez-Santana, Muriel, Kiwi, Miguel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270358/
https://www.ncbi.nlm.nih.gov/pubmed/37319168
http://dx.doi.org/10.1371/journal.pone.0286747
_version_ 1785059315730612224
author González, Rafael I.
Moya, Pablo S.
Bringa, Eduardo M.
Bacigalupe, Gonzalo
Ramírez-Santana, Muriel
Kiwi, Miguel
author_facet González, Rafael I.
Moya, Pablo S.
Bringa, Eduardo M.
Bacigalupe, Gonzalo
Ramírez-Santana, Muriel
Kiwi, Miguel
author_sort González, Rafael I.
collection PubMed
description 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.
format Online
Article
Text
id pubmed-10270358
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-102703582023-06-16 Model based on COVID-19 evidence to predict and improve pandemic control González, Rafael I. Moya, Pablo S. Bringa, Eduardo M. Bacigalupe, Gonzalo Ramírez-Santana, Muriel Kiwi, Miguel PLoS One Research Article 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. Public Library of Science 2023-06-15 /pmc/articles/PMC10270358/ /pubmed/37319168 http://dx.doi.org/10.1371/journal.pone.0286747 Text en © 2023 González et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
González, Rafael I.
Moya, Pablo S.
Bringa, Eduardo M.
Bacigalupe, Gonzalo
Ramírez-Santana, Muriel
Kiwi, Miguel
Model based on COVID-19 evidence to predict and improve pandemic control
title Model based on COVID-19 evidence to predict and improve pandemic control
title_full Model based on COVID-19 evidence to predict and improve pandemic control
title_fullStr Model based on COVID-19 evidence to predict and improve pandemic control
title_full_unstemmed Model based on COVID-19 evidence to predict and improve pandemic control
title_short Model based on COVID-19 evidence to predict and improve pandemic control
title_sort model based on covid-19 evidence to predict and improve pandemic control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10270358/
https://www.ncbi.nlm.nih.gov/pubmed/37319168
http://dx.doi.org/10.1371/journal.pone.0286747
work_keys_str_mv AT gonzalezrafaeli modelbasedoncovid19evidencetopredictandimprovepandemiccontrol
AT moyapablos modelbasedoncovid19evidencetopredictandimprovepandemiccontrol
AT bringaeduardom modelbasedoncovid19evidencetopredictandimprovepandemiccontrol
AT bacigalupegonzalo modelbasedoncovid19evidencetopredictandimprovepandemiccontrol
AT ramirezsantanamuriel modelbasedoncovid19evidencetopredictandimprovepandemiccontrol
AT kiwimiguel modelbasedoncovid19evidencetopredictandimprovepandemiccontrol