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Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru

The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare defi...

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Autores principales: Marín-Machuca, Olegario, Chacón, Ruy D., Alvarez-Lovera, Natalia, Pesantes-Grados, Pedro, Pérez-Timaná, Luis, Marín-Sánchez, Obert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10674587/
https://www.ncbi.nlm.nih.gov/pubmed/38005980
http://dx.doi.org/10.3390/vaccines11111648
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author Marín-Machuca, Olegario
Chacón, Ruy D.
Alvarez-Lovera, Natalia
Pesantes-Grados, Pedro
Pérez-Timaná, Luis
Marín-Sánchez, Obert
author_facet Marín-Machuca, Olegario
Chacón, Ruy D.
Alvarez-Lovera, Natalia
Pesantes-Grados, Pedro
Pérez-Timaná, Luis
Marín-Sánchez, Obert
author_sort Marín-Machuca, Olegario
collection PubMed
description The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare deficiencies. This study employed logistic regression to mathematically model COVID-19’s dynamics in Peru over three years and assessed the correlations between cases, deaths, and people vaccinated. We estimated the critical time (t(c)) for cases (627 days), deaths (389 days), and people vaccinated (268 days), which led to the maximum speed values on those days. Negative correlations were identified between people vaccinated and cases (−0.40) and between people vaccinated and deaths (−0.75), suggesting reciprocal relationships between those pairs of variables. In addition, Granger causality tests determined that the vaccinated population dynamics can be used to forecast the behavior of deaths (p-value < 0.05), evidencing the impact of vaccinations against COVID-19. Also, the coefficient of determination (R(2)) indicated a robust representation of the real data. Using the Peruvian context as an example case, the logistic model’s projections of cases, deaths, and vaccinations provide crucial insights into the pandemic, guiding public health tactics and reaffirming the essential role of vaccinations and resource distribution for an effective fight against COVID-19.
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spelling pubmed-106745872023-10-27 Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru Marín-Machuca, Olegario Chacón, Ruy D. Alvarez-Lovera, Natalia Pesantes-Grados, Pedro Pérez-Timaná, Luis Marín-Sánchez, Obert Vaccines (Basel) Article The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare deficiencies. This study employed logistic regression to mathematically model COVID-19’s dynamics in Peru over three years and assessed the correlations between cases, deaths, and people vaccinated. We estimated the critical time (t(c)) for cases (627 days), deaths (389 days), and people vaccinated (268 days), which led to the maximum speed values on those days. Negative correlations were identified between people vaccinated and cases (−0.40) and between people vaccinated and deaths (−0.75), suggesting reciprocal relationships between those pairs of variables. In addition, Granger causality tests determined that the vaccinated population dynamics can be used to forecast the behavior of deaths (p-value < 0.05), evidencing the impact of vaccinations against COVID-19. Also, the coefficient of determination (R(2)) indicated a robust representation of the real data. Using the Peruvian context as an example case, the logistic model’s projections of cases, deaths, and vaccinations provide crucial insights into the pandemic, guiding public health tactics and reaffirming the essential role of vaccinations and resource distribution for an effective fight against COVID-19. MDPI 2023-10-27 /pmc/articles/PMC10674587/ /pubmed/38005980 http://dx.doi.org/10.3390/vaccines11111648 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Marín-Machuca, Olegario
Chacón, Ruy D.
Alvarez-Lovera, Natalia
Pesantes-Grados, Pedro
Pérez-Timaná, Luis
Marín-Sánchez, Obert
Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title_full Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title_fullStr Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title_full_unstemmed Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title_short Mathematical Modeling of COVID-19 Cases and Deaths and the Impact of Vaccinations during Three Years of the Pandemic in Peru
title_sort mathematical modeling of covid-19 cases and deaths and the impact of vaccinations during three years of the pandemic in peru
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10674587/
https://www.ncbi.nlm.nih.gov/pubmed/38005980
http://dx.doi.org/10.3390/vaccines11111648
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