Scenario simulation to predict the behavior of COVID-19 in Perú
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , |
Tipo de documento: | preprint |
Idioma: | spa |
Título da fonte: | SciELO Preprints |
Texto Completo: | https://preprints.scielo.org/index.php/scielo/preprint/view/2851 |
Resumo: | COVID-19 has been a multi-dimensional challenge for humanity, even more so for decision-makers responsible for acting in an accurate and timely manner to confront it. In Peru, with a current favorable trend of the Pandemic, the spread of the Delta variant is imminent, hence they require predictive information that makes it possible to make early decisions to mitigate its effects. Consequently, the objective was established to simulate scenarios applying physical-mathematical modeling, which predict the behavior of COVID-19 in Peru and facilitate decision-making. As methods and techniques were applied: analysis-synthesis, documentary review and physical-mathematical modeling using tools and functions of the MATLAB software. The following are recognized as results: determination of the behavior of the main variables of COVID-19 in Peru; physical-mathematical model based on the classic SIR with new compartments related to vaccination and those exposed, as well as its adjustment to the data from Peru; simulation of scenarios, including the Delta variant, for deceased, accumulated infected, unvaccinated infected and vaccinated infected. It was concluded that: The model conceived for the simulation of COVID-19 evolution scenarios, demonstrated its ability to predict the behavior of the most important variables that determine said evolution in Peru; another wave of infections must occur and cumulative figures between 2.9 and 3.36 million infected and between 215 and 255 thousand deaths must be reached; The main mitigation strategies should be aimed at guaranteeing social distancing and isolation, as well as increasing the vaccination regimen. |
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Scenario simulation to predict the behavior of COVID-19 in PerúSimulación de escenarios para predecir el comportamiento de la COVID-19 en PerúCOVID-19scenario predictionDelta variantphysical-mathematical modelingCOVID-19predicción de escenariosvariante Deltamodelación físico-matemáticaCOVID-19 has been a multi-dimensional challenge for humanity, even more so for decision-makers responsible for acting in an accurate and timely manner to confront it. In Peru, with a current favorable trend of the Pandemic, the spread of the Delta variant is imminent, hence they require predictive information that makes it possible to make early decisions to mitigate its effects. Consequently, the objective was established to simulate scenarios applying physical-mathematical modeling, which predict the behavior of COVID-19 in Peru and facilitate decision-making. As methods and techniques were applied: analysis-synthesis, documentary review and physical-mathematical modeling using tools and functions of the MATLAB software. The following are recognized as results: determination of the behavior of the main variables of COVID-19 in Peru; physical-mathematical model based on the classic SIR with new compartments related to vaccination and those exposed, as well as its adjustment to the data from Peru; simulation of scenarios, including the Delta variant, for deceased, accumulated infected, unvaccinated infected and vaccinated infected. It was concluded that: The model conceived for the simulation of COVID-19 evolution scenarios, demonstrated its ability to predict the behavior of the most important variables that determine said evolution in Peru; another wave of infections must occur and cumulative figures between 2.9 and 3.36 million infected and between 215 and 255 thousand deaths must be reached; The main mitigation strategies should be aimed at guaranteeing social distancing and isolation, as well as increasing the vaccination regimen.La COVID-19 ha constituido un reto de múltiples dimensiones para la humanidad, aún más para los decisores responsables de accionar de manera certera y oportuna para su enfrentamiento. En Perú, con una tendencia actual favorable de la Pandemia, es inminente la propagación de la variante Delta, de allí que requieran de informaciones predictivas que posibiliten tomar decisiones anticipadas para mitigar sus efectos. Consecuentemente se estableció como objetivo simular escenarios aplicando la modelación físico-matemática, que predigan el comportamiento de la COVID-19 en Perú y faciliten la toma de decisiones. Como métodos y técnicas se aplicaron: análisis-síntesis, revisión documental y modelación físico-matemática mediante herramientas y funciones del software MATLAB. Se reconocen como resultados: determinación del comportamiento de las principales variables de la COVID-19 en Perú; modelo físico-matemático basado en el clásico SIR con nuevos compartimientos relacionados con la vacunación y los expuestos, así como su ajuste a los datos de Perú; simulación de escenarios, incluyendo la variante Delta, para fallecidos, infectados acumulados, infectados no vacunados e infectados vacunados. Se concluyó que: El modelo concebido para la simulación de escenarios de evolución de la COVID-19, demostró su capacidad de predicción del comportamiento de las variables más importantes que determinan dicha evolución en Perú; debe ocurrir otra ola de contagios y llegarse a cifras acumulativas entre 2,9 y 3,36 millones de infectados y entre 215 y 255 mil fallecidos; las principales estrategias de mitigación deben dirigirse a garantizar el distanciamiento y aislamiento social, así como a incrementar el régimen de vacunación.SciELO PreprintsSciELO PreprintsSciELO Preprints2021-09-08info:eu-repo/semantics/preprintinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://preprints.scielo.org/index.php/scielo/preprint/view/285110.1590/SciELOPreprints.2851spahttps://preprints.scielo.org/index.php/scielo/article/view/2851/5016Copyright (c) 2021 Héctor Eduardo Sánchez Vargas, Luis Alberto Taramona Ruiz, Amyrsa Salgado Rodríguez, Maribel Huatuco Lozano, Fernando Castillo Picónhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessVargas, Héctor Eduardo SánchezRuiz, Luis Alberto TaramonaRodríguez, Amyrsa SalgadoLozano, Maribel HuatucoPicón, Fernando Castilloreponame:SciELO Preprintsinstname:SciELOinstacron:SCI2021-08-25T04:51:45Zoai:ops.preprints.scielo.org:preprint/2851Servidor de preprintshttps://preprints.scielo.org/index.php/scieloONGhttps://preprints.scielo.org/index.php/scielo/oaiscielo.submission@scielo.orgopendoar:2021-08-25T04:51:45SciELO Preprints - SciELOfalse |
dc.title.none.fl_str_mv |
Scenario simulation to predict the behavior of COVID-19 in Perú Simulación de escenarios para predecir el comportamiento de la COVID-19 en Perú |
title |
Scenario simulation to predict the behavior of COVID-19 in Perú |
spellingShingle |
Scenario simulation to predict the behavior of COVID-19 in Perú Vargas, Héctor Eduardo Sánchez COVID-19 scenario prediction Delta variant physical-mathematical modeling COVID-19 predicción de escenarios variante Delta modelación físico-matemática |
title_short |
Scenario simulation to predict the behavior of COVID-19 in Perú |
title_full |
Scenario simulation to predict the behavior of COVID-19 in Perú |
title_fullStr |
Scenario simulation to predict the behavior of COVID-19 in Perú |
title_full_unstemmed |
Scenario simulation to predict the behavior of COVID-19 in Perú |
title_sort |
Scenario simulation to predict the behavior of COVID-19 in Perú |
author |
Vargas, Héctor Eduardo Sánchez |
author_facet |
Vargas, Héctor Eduardo Sánchez Ruiz, Luis Alberto Taramona Rodríguez, Amyrsa Salgado Lozano, Maribel Huatuco Picón, Fernando Castillo |
author_role |
author |
author2 |
Ruiz, Luis Alberto Taramona Rodríguez, Amyrsa Salgado Lozano, Maribel Huatuco Picón, Fernando Castillo |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Vargas, Héctor Eduardo Sánchez Ruiz, Luis Alberto Taramona Rodríguez, Amyrsa Salgado Lozano, Maribel Huatuco Picón, Fernando Castillo |
dc.subject.por.fl_str_mv |
COVID-19 scenario prediction Delta variant physical-mathematical modeling COVID-19 predicción de escenarios variante Delta modelación físico-matemática |
topic |
COVID-19 scenario prediction Delta variant physical-mathematical modeling COVID-19 predicción de escenarios variante Delta modelación físico-matemática |
description |
COVID-19 has been a multi-dimensional challenge for humanity, even more so for decision-makers responsible for acting in an accurate and timely manner to confront it. In Peru, with a current favorable trend of the Pandemic, the spread of the Delta variant is imminent, hence they require predictive information that makes it possible to make early decisions to mitigate its effects. Consequently, the objective was established to simulate scenarios applying physical-mathematical modeling, which predict the behavior of COVID-19 in Peru and facilitate decision-making. As methods and techniques were applied: analysis-synthesis, documentary review and physical-mathematical modeling using tools and functions of the MATLAB software. The following are recognized as results: determination of the behavior of the main variables of COVID-19 in Peru; physical-mathematical model based on the classic SIR with new compartments related to vaccination and those exposed, as well as its adjustment to the data from Peru; simulation of scenarios, including the Delta variant, for deceased, accumulated infected, unvaccinated infected and vaccinated infected. It was concluded that: The model conceived for the simulation of COVID-19 evolution scenarios, demonstrated its ability to predict the behavior of the most important variables that determine said evolution in Peru; another wave of infections must occur and cumulative figures between 2.9 and 3.36 million infected and between 215 and 255 thousand deaths must be reached; The main mitigation strategies should be aimed at guaranteeing social distancing and isolation, as well as increasing the vaccination regimen. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-08 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/preprint info:eu-repo/semantics/publishedVersion |
format |
preprint |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/preprint/view/2851 10.1590/SciELOPreprints.2851 |
url |
https://preprints.scielo.org/index.php/scielo/preprint/view/2851 |
identifier_str_mv |
10.1590/SciELOPreprints.2851 |
dc.language.iso.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://preprints.scielo.org/index.php/scielo/article/view/2851/5016 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
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https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO Preprints SciELO Preprints SciELO Preprints |
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SciELO |
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SciELO Preprints |
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SciELO Preprints |
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SciELO Preprints - SciELO |
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