Logistics estimation of the COVID-19 vaccination process in Peru

Descripción del Articulo

While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination proce...

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Detalles Bibliográficos
Autores: Marín-Machuca , Olegario, Dávila-Solar, Luis Alberto, Blas-Ramos, Walter Eduardo, López-Ráez, Luz Eufemia, Alvarado-Zambrano, Fredy Aníbal, Alvarado-Zambrano, Ricardo Arnaldo, Marín-Sánchez, Obert
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Ricardo Palma
Repositorio:Revistas - Universidad Ricardo Palma
Lenguaje:español
OAI Identifier:oai:oai.revistas.urp.edu.pe:article/5675
Enlace del recurso:http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675
Nivel de acceso:acceso abierto
Materia:COVID-19
critical time
logistics estimation
Peru
vaccination
velocity
estimación logística
Perú
tiempo crítico
vacunación
velocidad
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oai_identifier_str oai:oai.revistas.urp.edu.pe:article/5675
network_acronym_str REVURP
network_name_str Revistas - Universidad Ricardo Palma
repository_id_str
dc.title.none.fl_str_mv Logistics estimation of the COVID-19 vaccination process in Peru
Estimación logística del proceso de vacunación contra la COVID-19 en el Perú
title Logistics estimation of the COVID-19 vaccination process in Peru
spellingShingle Logistics estimation of the COVID-19 vaccination process in Peru
Marín-Machuca , Olegario
COVID-19
critical time
logistics estimation
Peru
vaccination
velocity
COVID-19
estimación logística
Perú
tiempo crítico
vacunación
velocidad
title_short Logistics estimation of the COVID-19 vaccination process in Peru
title_full Logistics estimation of the COVID-19 vaccination process in Peru
title_fullStr Logistics estimation of the COVID-19 vaccination process in Peru
title_full_unstemmed Logistics estimation of the COVID-19 vaccination process in Peru
title_sort Logistics estimation of the COVID-19 vaccination process in Peru
dc.creator.none.fl_str_mv Marín-Machuca , Olegario
Dávila-Solar, Luis Alberto
Blas-Ramos, Walter Eduardo
López-Ráez, Luz Eufemia
Alvarado-Zambrano, Fredy Aníbal
Alvarado-Zambrano, Ricardo Arnaldo
Marín-Sánchez, Obert
author Marín-Machuca , Olegario
author_facet Marín-Machuca , Olegario
Dávila-Solar, Luis Alberto
Blas-Ramos, Walter Eduardo
López-Ráez, Luz Eufemia
Alvarado-Zambrano, Fredy Aníbal
Alvarado-Zambrano, Ricardo Arnaldo
Marín-Sánchez, Obert
author_role author
author2 Dávila-Solar, Luis Alberto
Blas-Ramos, Walter Eduardo
López-Ráez, Luz Eufemia
Alvarado-Zambrano, Fredy Aníbal
Alvarado-Zambrano, Ricardo Arnaldo
Marín-Sánchez, Obert
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv COVID-19
critical time
logistics estimation
Peru
vaccination
velocity
COVID-19
estimación logística
Perú
tiempo crítico
vacunación
velocidad
topic COVID-19
critical time
logistics estimation
Peru
vaccination
velocity
COVID-19
estimación logística
Perú
tiempo crítico
vacunación
velocidad
description While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination process in Peru, to estimate the number of people vaccinated, the critical time for which the estimated rate of vaccinated people has been the highest value, and to specify the date on which the highest number of people vaccinated has occurred. The methodology was based on determining the form of dispersion of the vaccination process, this being a logistic distribution and considering that a mathematical model is a mathematical description, by means of a function of a real-world phenomenon, such as the number of people vaccinated against the COVID-19 disease. The model presented a correlation coefficient r=-0.95, the critical time (tc) was 286 days and the maximum rate of vaccinated persons 143071 persons/day, dated December thirteenth, 2022: between March second, 2021, and March ninth, 2022. The estimated number of people vaccinated against COVID-19 disease was determined by the equation N ̂=28601461/(1+89.0602×e^(-0, 0157×t) ) and the rate of change or rate of estimated persons vaccinated against COVID-19 in Peru was calculated by the equation (dN ̂)/dt=(39949527,1600×e^(-0,0157×t))/〖(1+89,0602×e^(-0,0157×t))〗^2; the correlation coefficient between the elapsed time t (days) and the number of people vaccinated (N), based on twenty-five cases, was r=-0.95, representing a "very strong correlation" between the elapsed time (t) and the number of people vaccinated (N), and the coefficient of determination indicates that 89.47 % of the variance in N is explained by t;  for the vaccination process against COVID-19 in the country; concluding that the theory of Bronshtein & Semendiaev and the logistic models can be adequately applied to pandemic and epidemiological phenomena, that the critical time (tc), for the contagions was two hundred eighty-six days, reaching its maximum speed of contagion estimated at 112142 persons/day.
publishDate 2023
dc.date.none.fl_str_mv 2023-04-29
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo evaluado por pares
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675
10.31381/paideia.v13i1.5675
url http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675
identifier_str_mv 10.31381/paideia.v13i1.5675
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/7784
http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/8419
dc.rights.none.fl_str_mv Derechos de autor 2023 Paideia XXI
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2023 Paideia XXI
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Universidad Ricardo Palma
publisher.none.fl_str_mv Universidad Ricardo Palma
dc.source.none.fl_str_mv Paideia XXI; Vol. 13 Núm. 1 (2023): Paideia XXI; 51-63
Paideia XXI; Vol. 13 No. 1 (2023): Paideia XXI: Advance publication; 51-63
2519-5700
2221-7770
10.31381/paideia.v13i1
reponame:Revistas - Universidad Ricardo Palma
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instname_str Universidad Ricardo Palma
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spelling Logistics estimation of the COVID-19 vaccination process in PeruEstimación logística del proceso de vacunación contra la COVID-19 en el Perú Marín-Machuca , Olegario Dávila-Solar, Luis Alberto Blas-Ramos, Walter Eduardo López-Ráez, Luz Eufemia Alvarado-Zambrano, Fredy Aníbal Alvarado-Zambrano, Ricardo Arnaldo Marín-Sánchez, Obert COVID-19 critical time logistics estimation Peru vaccination velocity COVID-19 estimación logística Perú tiempo crítico vacunación velocidad While it is true that vaccines generate immunity with a high degree of effectiveness and that in Peru, a certain time was spent initiating the COVID-19 disease, a vaccination process that was developed logistically. The objective was to obtain the mathematical model of the COVID-19 vaccination process in Peru, to estimate the number of people vaccinated, the critical time for which the estimated rate of vaccinated people has been the highest value, and to specify the date on which the highest number of people vaccinated has occurred. The methodology was based on determining the form of dispersion of the vaccination process, this being a logistic distribution and considering that a mathematical model is a mathematical description, by means of a function of a real-world phenomenon, such as the number of people vaccinated against the COVID-19 disease. The model presented a correlation coefficient r=-0.95, the critical time (tc) was 286 days and the maximum rate of vaccinated persons 143071 persons/day, dated December thirteenth, 2022: between March second, 2021, and March ninth, 2022. The estimated number of people vaccinated against COVID-19 disease was determined by the equation N ̂=28601461/(1+89.0602×e^(-0, 0157×t) ) and the rate of change or rate of estimated persons vaccinated against COVID-19 in Peru was calculated by the equation (dN ̂)/dt=(39949527,1600×e^(-0,0157×t))/〖(1+89,0602×e^(-0,0157×t))〗^2; the correlation coefficient between the elapsed time t (days) and the number of people vaccinated (N), based on twenty-five cases, was r=-0.95, representing a "very strong correlation" between the elapsed time (t) and the number of people vaccinated (N), and the coefficient of determination indicates that 89.47 % of the variance in N is explained by t;  for the vaccination process against COVID-19 in the country; concluding that the theory of Bronshtein & Semendiaev and the logistic models can be adequately applied to pandemic and epidemiological phenomena, that the critical time (tc), for the contagions was two hundred eighty-six days, reaching its maximum speed of contagion estimated at 112142 persons/day.Si bien es cierto que las vacunas generan inmunidad con alto grado de efectividad y que en el Perú se realizó cierto tiempo iniciada enfermedad COVID-19; proceso de vacunación que se desarrolló logísticamente; cuyo propósito fue obtener un  modelo matemático del proceso de vacunación contra la enfermedad de la  COVID-19 en el Perú, para estimar el número de personas vacunadas, el tiempo crítico para el cual la velocidad estimada de personas vacunadas ha sido la de mayor valor, y precisar la fecha en que se ha producido la mayor cantidad de personas vacunadas. La metodología se basó en determinar la forma de dispersión del proceso de vacunación, siendo esta una distribución logística y teniendo en cuenta que un modelo matemático es una descripción matemática, mediante una función de un fenómeno del mundo real, como el número de vacunados contra la enfermedad COVID-19. El modelo presentó un coeficiente de correlación   , el tiempo crítico (  y la velocidad máxima de personas vacunadas , de fecha trece de diciembre del 2022; entre el dos de marzo del 2021 y el nueve de marzo del 2022. El número estimado de personas vacunadas contra la enfermedad COVID-19 fue determinado por la ecuación  y la razón de cambio o velocidad de personas estimadas vacunadas contra la COVID-19 en el Perú, se calculó por la ecuación  ; el coeficiente de correlación entre el tiempo transcurrido t (días) y el número de personas vacunadas ( ), basado en veinticinco casos, fue de , representando una “correlacion muy fuerte” entre el tiempo transcurrido ( ) y el número de personas vacunadas ( ), y el coeficiente de determinación indica que el 89,47 % de la variancia en  es explicada por ;  para el proceso de vacunación contra la COVID-19 en el país; concluyendo que la teoría de Bronshtein & Semendiaev y los  modelos logísticos se pueden aplicar adecuadamente a fenómenos pandémicos y epidemiológicos, que el tiempo crítico ( ), para los contagios fue de doscientos ochenta y seis días, llegando a su velocidad máxima de contagio estimados de .Universidad Ricardo Palma2023-04-29info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulo evaluado por paresapplication/pdftext/htmlhttp://revistas.urp.edu.pe/index.php/Paideia/article/view/567510.31381/paideia.v13i1.5675Paideia XXI; Vol. 13 Núm. 1 (2023): Paideia XXI; 51-63Paideia XXI; Vol. 13 No. 1 (2023): Paideia XXI: Advance publication; 51-632519-57002221-777010.31381/paideia.v13i1reponame:Revistas - Universidad Ricardo Palmainstname:Universidad Ricardo Palmainstacron:URPspahttp://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/7784http://revistas.urp.edu.pe/index.php/Paideia/article/view/5675/8419Derechos de autor 2023 Paideia XXIinfo:eu-repo/semantics/openAccessoai:oai.revistas.urp.edu.pe:article/56752023-12-16T02:50:55Z
score 13.982926
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