Model applied to exponental growth of covid 19
The Malthus growth model is the most widely used law to model dynamic processes. In this work, we use the Malthusian theory to estimate the growth rate of new daily cases of COVID-19 infection and two periods of time in which this type of growth occurred, the first of 41 days and the second of 101 d...
- Autores:
-
Vergel Ortega, Mawency
Ibarguen Mondragon, Eduardo
Gómez Vergel, Carlos Sebastian
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Universidad Francisco de Paula Santander
- Repositorio:
- Repositorio Digital UFPS
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.ufps.edu.co:ufps/1077
- Acceso en línea:
- http://repositorio.ufps.edu.co/handle/ufps/1077
https://doi.org/10.36260/rbr.v9i11.1119
- Palabra clave:
- Modelo de Malthus
crecimiento exponencial de COVID 19
- Rights
- openAccess
- License
- Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)
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Model applied to exponental growth of covid 19 |
| dc.title.translated.none.fl_str_mv |
El modelo de Malthus aplicado al crecimiento exponencial de Covid 19 |
| title |
Model applied to exponental growth of covid 19 |
| spellingShingle |
Model applied to exponental growth of covid 19 Modelo de Malthus crecimiento exponencial de COVID 19 |
| title_short |
Model applied to exponental growth of covid 19 |
| title_full |
Model applied to exponental growth of covid 19 |
| title_fullStr |
Model applied to exponental growth of covid 19 |
| title_full_unstemmed |
Model applied to exponental growth of covid 19 |
| title_sort |
Model applied to exponental growth of covid 19 |
| dc.creator.fl_str_mv |
Vergel Ortega, Mawency Ibarguen Mondragon, Eduardo Gómez Vergel, Carlos Sebastian |
| dc.contributor.author.none.fl_str_mv |
Vergel Ortega, Mawency Ibarguen Mondragon, Eduardo Gómez Vergel, Carlos Sebastian |
| dc.subject.proposal.spa.fl_str_mv |
Modelo de Malthus crecimiento exponencial de COVID 19 |
| topic |
Modelo de Malthus crecimiento exponencial de COVID 19 |
| description |
The Malthus growth model is the most widely used law to model dynamic processes. In this work, we use the Malthusian theory to estimate the growth rate of new daily cases of COVID-19 infection and two periods of time in which this type of growth occurred, the first of 41 days and the second of 101 days. In the first one, the growth rate was 10 times greater than in the second one. From the results, it is concluded that the United States, Spain, France, Italy, Germany and the United Kingdom were the countries that had the greatest impact on exponential growth during the first period, while the Americas, Russia and India were the ones that contributed the most in the second one. |
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2020 |
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2020-11-11 |
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2021-11-18T15:01:32Z |
| dc.date.available.none.fl_str_mv |
2021-11-18T15:01:32Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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http://repositorio.ufps.edu.co/handle/ufps/1077 |
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https://doi.org/10.36260/rbr.v9i11.1119 |
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http://repositorio.ufps.edu.co/handle/ufps/1077 https://doi.org/10.36260/rbr.v9i11.1119 |
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eng |
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eng |
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Revista Boletin Redipe |
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Vol.9 No.11.(2019) |
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164 |
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11 (2020) |
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159 |
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9 |
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Ibarguen-Mondragon E, Vergel-Ortega M, Gómez Vergel CS. El modelo de Malthus aplicado al crecimiento exponencial de Covid 19. bol.redipe [Internet]. 11 de noviembre de 2020 [citado 18 de noviembre de 2021];9(11):159-64. Disponible en: https://revista.redipe.org/index.php/1/article/view/1119 |
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Revista Boletin Redipe |
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Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0) |
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openAccess |
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Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0) http://purl.org/coar/access_right/c_abf2 |
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Bogota ,Colombia |
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https://revista.redipe.org/index.php/1/article/view/1119 |
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Vergel Ortega, Mawencye1db451514df4d6eb054b4e8e3bf1e42600Ibarguen Mondragon, Eduardo4ebf5068c622d6f6fddc9aa0b33b704dGómez Vergel, Carlos Sebastian149eaa606ea34b6c8eb9c0e2469775642021-11-18T15:01:32Z2021-11-18T15:01:32Z2020-11-11http://repositorio.ufps.edu.co/handle/ufps/1077https://doi.org/10.36260/rbr.v9i11.1119The Malthus growth model is the most widely used law to model dynamic processes. In this work, we use the Malthusian theory to estimate the growth rate of new daily cases of COVID-19 infection and two periods of time in which this type of growth occurred, the first of 41 days and the second of 101 days. In the first one, the growth rate was 10 times greater than in the second one. From the results, it is concluded that the United States, Spain, France, Italy, Germany and the United Kingdom were the countries that had the greatest impact on exponential growth during the first period, while the Americas, Russia and India were the ones that contributed the most in the second one.El modelo de crecimiento de Malthus es la ley más utilizada para modelar procesos dinámicos. En este trabajo utilizamos la teoría maltusiana para estimar la tasa de crecimiento de los nuevos casos diarios de infección por COVID-19 y dos períodos de tiempo en los que se produjo este tipo de crecimiento, el primero de 41 días y el segundo de 101 días. En el primero, la tasa de crecimiento fue 10 veces mayor que en el segundo. De los resultados se concluye que Estados Unidos, España, Francia, Italia, Alemania y el Reino Unido fueron los países que tuvieron mayor impacto en el crecimiento exponencial durante el primer período, mientras que América, Rusia e India fueron los que más contribuyeron en el segundo.application/pdfengRevista Boletin RedipeBogota ,ColombiaRevista Boletin RedipeVol.9 No.11.(2019)16411 (2020)1599Ibarguen-Mondragon E, Vergel-Ortega M, Gómez Vergel CS. El modelo de Malthus aplicado al crecimiento exponencial de Covid 19. bol.redipe [Internet]. 11 de noviembre de 2020 [citado 18 de noviembre de 2021];9(11):159-64. Disponible en: https://revista.redipe.org/index.php/1/article/view/1119Revista Boletin RedipeEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0.info:eu-repo/semantics/openAccessAtribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0)http://purl.org/coar/access_right/c_abf2https://revista.redipe.org/index.php/1/article/view/1119Model applied to exponental growth of covid 19El modelo de Malthus aplicado al crecimiento exponencial de Covid 19Artículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85Modelo de Malthuscrecimiento exponencial de COVID 19Juliano S (2007) Population dynamics Journal of the American Mosquito Control Association 23 (2) 265-275Jean R Mee T Kirkby N and Williams M 2015 Quantifying uncertainty in radiotherapy demand at the local and national lavel using the Malthus model Clin. Oncol 27(2) 92-98Brander J and Taylor M (1998) The simple economics of Easter Island: A Ricardo-Malthus model of renewable use Am Econ Rev 88(1) 119-138Turner M and Cunneen C (1986) Malthus and his time (New York: Springer)Ibarguen-Mondragón E, Romero J, Esteva L, Cerón M and Hidalgo-Bonilla S (2019) Stability and periodic solutions for a model of bacterial resistance to antibiotics caused by mutations and plasmids Appl. Math. Model 76 238-251Wangersky P (1978) Lotka-Volterra population models Annual Review of Ecology and Systematics 9 189-218Smith D, Battle K, Hay S, Barker C, Scott T and McKenzie F (2012) Ross Macdonald and a theory for the dynamics and control of mosquito-transmitted pathogens PLoS pathog 8 4 e10025883Monod J (1949) The growth of bacterial cultures Annual review of microbiology 3(1) 371-394Malthus T, Winch D and James P (1992) Malthus An Essay on the Principle of Population (New York: Cambridge University Press)Apostolopoulos I, Mpesiana T (2020) Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks Physical and Engineering Sciences in Medicine 43(2) 635-640Drummond A and Rambaut A (2007) BEAST: Bayesian evolutionary analysis by sampling trees BMC Evol Biol 7(214) 725-736Ibarguen-Mondragón E, Revelo-Romo D, Hidalgo A, García H and Galeano L (2020) Mathematical modelling of MS2 virus inactivation by Al/Fe-PILC-activated catalytic wet peroxide oxidation J. Math. Anal. Appli. 385 7205World Health Organization 2020 Coronavirus disease (2019) (COVID-19): situation report, 1Hongzhou L, Charles W, Stratton Y (2019) Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle, J Med Virol, Special Issue 92(4) 789-798ORIGINALModel applied to exponental growth of covid 19.pdfModel applied to exponental growth of covid 19.pdfapplication/pdf405649https://repositorio.ufps.edu.co/bitstream/ufps/1077/1/Model%20applied%20to%20exponental%20growth%20of%20covid%2019.pdfb13ada901535ff8d56ffef44f69d84c8MD51open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.ufps.edu.co/bitstream/ufps/1077/2/license.txt2f9959eaf5b71fae44bbf9ec84150c7aMD52open accessTEXTModel applied to exponental growth of covid 19.pdf.txtModel applied to exponental growth of covid 19.pdf.txtExtracted texttext/plain20605https://repositorio.ufps.edu.co/bitstream/ufps/1077/3/Model%20applied%20to%20exponental%20growth%20of%20covid%2019.pdf.txt2d2f761501b8d3129087e2db1558cdfbMD53open accessTHUMBNAILModel applied to exponental growth of covid 19.pdf.jpgModel applied to exponental growth of covid 19.pdf.jpgGenerated Thumbnailimage/jpeg12436https://repositorio.ufps.edu.co/bitstream/ufps/1077/4/Model%20applied%20to%20exponental%20growth%20of%20covid%2019.pdf.jpg9321a9962dbb633e886e6e24ebd237cdMD54open accessufps/1077oai:repositorio.ufps.edu.co:ufps/10772022-05-23 10:53:24.029open accessRepositorio Universidad Francisco de Paula 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 incorporada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
0000-0001-8285-2968e1db451514df4d6eb054b4e8e3bf1e42600 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