Login | Register | Forgot your password? | Contact | Español |
Email: Password:

Medwave se preocupa por su privacidad y la seguridad de sus datos personales.
Para poder enviarle a su dirección de correo electrónico su contraseña, es necesario que ingrese su e-mail.


Analysis
Medwave 2020;20(4):e7898 doi: 10.5867/medwave.2020.04.7898
An epidemiological forecast of COVID-19 in Chile based on the generalized SEIR model and the concept of recovered
Camilo Guerrero-Nancuante, Ronald Manríquez P
References | Download PDF |
To Download PDF must login.
Print | A(+) A(-) | Easy read

Key Words: coronavirus, epidemiology, mathematical model, public health

Abstract

The COVID-19 pandemic declared by the World Health Organization (WHO) has generated a wide-ranging debate regarding epidemiological forecasts and the global implications. With the data obtained from the Chilean Ministry of Health (MINSAL), a prospective study was carried out using the generalized SEIR model to estimate the course of COVID-19 in Chile. Three scenarios were estimated: Scenario 1 with official MINSAL data; scenario 2 with official MINSAL data and recovery criteria proposed by international organizations of health; and scenario 3 with official MINSAL data, recovery criteria proposed by international organizations of health, and without considering deaths in the total recovered. There are considerable differences between scenario 1 compared to 2 and 3 in the number of deaths, active patients, and duration of the disease. Scenario 3, considered the most adverse, estimates a total of 11,000 infected people, 1,151 deaths, and that the peak of the disease will occur in the first days of May. We concluded that the concept of “recovered” may be decisive for the epidemiological forecasts of COVID-19 in Chile.


 

Only Spanish version is available.

Licencia Creative Commons Esta obra de Medwave está bajo una licencia Creative Commons Atribución-NoComercial 3.0 Unported. Esta licencia permite el uso, distribución y reproducción del artículo en cualquier medio, siempre y cuando se otorgue el crédito correspondiente al autor del artículo y al medio en que se publica, en este caso, Medwave.

 

La pandemia de COVID-19 declarada por la Organización Mundial de la Salud (OMS) ha generado un amplio debate respecto de las proyecciones epidemiológicas que tendrá a nivel global en nuestro planeta. Con los datos obtenidos del Ministerio de Salud de Chile (MINSAL), se efectuó un estudio prospectivo utilizando un modelo SEIR (Susceptible-Expuesto-Infectado-Recuperado) generalizado con el objetivo de estimar la evolución del COVID-19 en Chile. La estimación se realizó bajo tres escenarios con datos oficiales del Ministerio de Salud: escenario 1 solo con datos oficiales; escenario 2 se añade el criterio de recuperados propuesto por organizaciones internacionales de salud y escenario 3 se incorpora el criterio de recuperados propuesto por organizaciones internacionales de salud, sin considerar fallecidos en el total de recuperados. Existen diferencias considerables entre el escenario 1 en comparación al 2 y 3 en número de fallecidos, enfermos activos y duración de la enfermedad. El escenario 3, considerado el más adverso, estima un total de 11 000 personas contagiadas, 1151 fallecidos y que el máximo de la enfermedad ocurriría durante los primeros días de mayo. Se concluye que el concepto de “recuperado” puede ser decisivo para las proyecciones epidemiológicas de COVID-19 en Chile.

Authors: Camilo Guerrero-Nancuante[1], Ronald Manríquez P[2]

Affiliation:
[1] Escuela de Enfermería, Universidad de Valparaíso, Valparaíso, Chile
[2] Laboratorio de investigación Lab[e]saM, Departamento de Matemática y Estadística, Universidad de Playa Ancha, Valparaíso, Chile

E-mail: camilo.guerrero@uv.cl

Author address:
[1] Angamos 655
Viña del Mar, Chile
Código postal: 2540064

Citation: Guerrero-Nancuante C, Manríquez P R. An epidemiological forecast of COVID-19 in Chile based on the generalized SEIR model and the concept of recovered. Medwave 2020;20(4):e7898 doi: 10.5867/medwave.2020.04.7898

Submission date: 14/4/2020

Acceptance date: 30/4/2020

Publication date: 15/5/2020

Origin: Not commissioned

Type of review: Externally peer-reviewed by three reviewers, double-blind

Comments (0)

We are pleased to have your comment on one of our articles. Your comment will be published as soon as it is posted. However, Medwave reserves the right to remove it later if the editors consider your comment to be: offensive in some sense, irrelevant, trivial, contains grammatical mistakes, contains political harangues, appears to be advertising, contains data from a particular person or suggests the need for changes in practice in terms of diagnostic, preventive or therapeutic interventions, if that evidence has not previously been published in a peer-reviewed journal.

No comments on this article.


To comment please log in

Medwave provides HTML and PDF download counts as well as other harvested interaction metrics.

There may be a 48-hour delay for most recent metrics to be posted.

  1. Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health. 2020 Mar;25(3):278-280. | CrossRef | PubMed |
  2. Singhal T. A Review of Coronavirus Disease-2019 (COVID-19). Indian J Pediatr. 2020 Apr;87(4):281-286. | CrossRef | PubMed |
  3. Xie M, Chen Q. Insight into 2019 novel coronavirus - An updated interim review and lessons from SARS-CoV and MERS-CoV. Int J Infect Dis. 2020 Apr 1;94:119-124. | CrossRef | PubMed |
  4. John Hopkins University, Coronavirus Resource center. New Cases of COVID-19 In World Countries. 2020. [On line]. | Link |
  5. World Health Organization. Coronavirus disease 2019 (COVID-19) Situation Report-46. Geneva; 2020. [On line]. | Link |
  6. Jackson J, Weiss M, Schwarzenberg A, Nelson R. Global Economic Effects of COVID-19. Washington D.C. USA; 2020. [On line]. | Link |
  7. Ministerio de Salud de Chile. Reporte coronavirus 05 de Abril 2020. Santiago de Chile. [On line]. | Link |
  8. Cádiz P. Casos "Recuperados” de Coronavirus: Cómo se mide y qué dice la ciencia sobre contagiarse dos veces. Tele13. 2020. [On line]. | Link |
  9. World Health Organization. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Geneva; 2020. [On line]. | Link |
  10. World Health Organization. Considerations in the investigation of cases and clusters of COVID-19. Geneva; 2020. [On line]. | Link |
  11. Centers for disease control and prevention. Discontinuation of Isolation for Persons with COVID -19 Not in Healthcare Settings. Georgia, USA;2020. [On line]. | Link |
  12. European Centre for Disease prevention and control. Novel coronavirus (SARS-CoV-2) - Discharge criteria for confirmed COVID-19 cases. Solna, Sweden; 2020. [On line]. | Link |
  13. Fest S. Chile cuenta a los muertos por coronavirus como "casos recuperados" porque "no son una fuente de contagios". El Mundo (ES). 2020. [On line]. | Link |
  14. Casals M, Guzmán K, Caylà JA. [Mathematical models used in the study of infectious diseases]. Rev Esp Salud Publica. 2009 Sep-Oct;83(5):689-95. | PubMed |
  15. Fresnadillo-Martínez MJ, García-Sánchez E, García-Merino E, Martín del Rey Á, García-Sánchez JE. Revisión Modelización matemática de la propagación de enfermedades infecciosas : de dónde venimos y hacia dónde vamos. Rev Esp Quimioter. 2013;26(2):81–91. [On line]. | Link |
  16. Peng L, Yang W, Zhang D, Zhuge C, Hong, L. Epidemic analysis of COVID-19 in China by dynamical modeling. Epidemiology. 2020. [On line]. | Link |
  17. Binti-Hamzah F, Lau CH, Nazri H, Ligot DV, Lee G, Tan CL, et al. CoronaTracker: World-wide COVID-19 Outbreak Data Analysis and Prediction. 2020. [On line]. | Link |
  18. Al-Hussein A, Tahir F. Epidemiological Characteristics of COVID-19 Ongoing Epidemic in Iraq. 2020. [On line]. | Link |
  19. Godio A, Pace F, Vergnano A. SEIR Modeling of the Italian Epidemic of SARS-. Preprints. 2020. | CrossRef |
  20. Organización para la cooperación y el desarrollo económicos (OCDE). Panorama de la Salud 2017. Indicadores OCDE. Paris; 2018. | CrossRef |
  21. Córdova-Lepe F, Gutiérrez-Aguilar R, Gutiérrez-Jara JP. Number of COVID-19 cases in Chile at 120 days with data at 21/03/2020 and threshold of daily effort to flatten the epi-curve. Medwave. 2020 Mar 27;20(2):e7861. | CrossRef | PubMed |
  22. Gutiérrez-Aguilar R, Córdova-Lepe F, Muñoz-Quezada MT, Gutiérrez-Jara JP. Modelo de umbral de reducción de tasa diaria de casos COVID-19 para evitar el colapso hospitalario en Chile. Medwave. 2020;20(3):e7871. [On line]. | Link |
  23. Cheynet E. Generalized SEIR Epidemic Model (fitting and computation). GitHub; 2020. [On line]. | Link |
  24. Ascher U, Petzold L. Computer methods for ordinary differential equations and differential-algebraic equations. 1a Ed. Philadelphia (USA): SIAM; 1998.
  25. Miranda B. Covid-19: Eduardo Engel cuestiona la estadística del gobierno y la eficacia de las medidas que está tomando. Centro de Investigación Periodística (CIPER). 2020. [On line]. | Link |
  26. Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health. 2020 May;5(5):e261-e270. | CrossRef | PubMed |
  27. Michael L, Golden K, Lewis M, Nishiura Y, Sambridge M, Tribbia J, et al. An Introduction to Mathematical Modeling of Infectious Diseases. 2a Ed. Cham: Springer International; 2018.
  28. López LR, Rodó X. A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: simulating control scenarios and multi-scale epidemics. 2020. [On line]. | Link |
  29. Yang Z, Zeng Z, Wang K, Wong SS, Liang W, Zanin M, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J Thorac Dis. 2020 Mar;12(3):165-174. | CrossRef | PubMed |
  30. Rojas-Vallejos J. Strengths and limitations of mathematical models in pandemicsthe case of COVID-19 in Chile. Medwave. 2020 Apr 8;20(3):e7876. | CrossRef | PubMed |
  31. Ojeda JM, Cabrera B, Castillo V. ¿Cuánto tardan los resultados de los test? Gobierno admite demora de al menos 48 horas y hospitales, de hasta cinco días. La Tercera. 2020. [On line]. | Link |
Velavan TP, Meyer CG. The COVID-19 epidemic. Trop Med Int Health. 2020 Mar;25(3):278-280. | CrossRef | PubMed |

Singhal T. A Review of Coronavirus Disease-2019 (COVID-19). Indian J Pediatr. 2020 Apr;87(4):281-286. | CrossRef | PubMed |

Xie M, Chen Q. Insight into 2019 novel coronavirus - An updated interim review and lessons from SARS-CoV and MERS-CoV. Int J Infect Dis. 2020 Apr 1;94:119-124. | CrossRef | PubMed |

John Hopkins University, Coronavirus Resource center. New Cases of COVID-19 In World Countries. 2020. [On line]. | Link |

World Health Organization. Coronavirus disease 2019 (COVID-19) Situation Report-46. Geneva; 2020. [On line]. | Link |

Jackson J, Weiss M, Schwarzenberg A, Nelson R. Global Economic Effects of COVID-19. Washington D.C. USA; 2020. [On line]. | Link |

Ministerio de Salud de Chile. Reporte coronavirus 05 de Abril 2020. Santiago de Chile. [On line]. | Link |

Cádiz P. Casos "Recuperados” de Coronavirus: Cómo se mide y qué dice la ciencia sobre contagiarse dos veces. Tele13. 2020. [On line]. | Link |

World Health Organization. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). Geneva; 2020. [On line]. | Link |

World Health Organization. Considerations in the investigation of cases and clusters of COVID-19. Geneva; 2020. [On line]. | Link |

Centers for disease control and prevention. Discontinuation of Isolation for Persons with COVID -19 Not in Healthcare Settings. Georgia, USA;2020. [On line]. | Link |

European Centre for Disease prevention and control. Novel coronavirus (SARS-CoV-2) - Discharge criteria for confirmed COVID-19 cases. Solna, Sweden; 2020. [On line]. | Link |

Fest S. Chile cuenta a los muertos por coronavirus como "casos recuperados" porque "no son una fuente de contagios". El Mundo (ES). 2020. [On line]. | Link |

Casals M, Guzmán K, Caylà JA. [Mathematical models used in the study of infectious diseases]. Rev Esp Salud Publica. 2009 Sep-Oct;83(5):689-95. | PubMed |

Fresnadillo-Martínez MJ, García-Sánchez E, García-Merino E, Martín del Rey Á, García-Sánchez JE. Revisión Modelización matemática de la propagación de enfermedades infecciosas : de dónde venimos y hacia dónde vamos. Rev Esp Quimioter. 2013;26(2):81–91. [On line]. | Link |

Peng L, Yang W, Zhang D, Zhuge C, Hong, L. Epidemic analysis of COVID-19 in China by dynamical modeling. Epidemiology. 2020. [On line]. | Link |

Binti-Hamzah F, Lau CH, Nazri H, Ligot DV, Lee G, Tan CL, et al. CoronaTracker: World-wide COVID-19 Outbreak Data Analysis and Prediction. 2020. [On line]. | Link |

Al-Hussein A, Tahir F. Epidemiological Characteristics of COVID-19 Ongoing Epidemic in Iraq. 2020. [On line]. | Link |

Godio A, Pace F, Vergnano A. SEIR Modeling of the Italian Epidemic of SARS-. Preprints. 2020. | CrossRef |

Organización para la cooperación y el desarrollo económicos (OCDE). Panorama de la Salud 2017. Indicadores OCDE. Paris; 2018. | CrossRef |

Córdova-Lepe F, Gutiérrez-Aguilar R, Gutiérrez-Jara JP. Number of COVID-19 cases in Chile at 120 days with data at 21/03/2020 and threshold of daily effort to flatten the epi-curve. Medwave. 2020 Mar 27;20(2):e7861. | CrossRef | PubMed |

Gutiérrez-Aguilar R, Córdova-Lepe F, Muñoz-Quezada MT, Gutiérrez-Jara JP. Modelo de umbral de reducción de tasa diaria de casos COVID-19 para evitar el colapso hospitalario en Chile. Medwave. 2020;20(3):e7871. [On line]. | Link |

Cheynet E. Generalized SEIR Epidemic Model (fitting and computation). GitHub; 2020. [On line]. | Link |

Ascher U, Petzold L. Computer methods for ordinary differential equations and differential-algebraic equations. 1a Ed. Philadelphia (USA): SIAM; 1998.

Miranda B. Covid-19: Eduardo Engel cuestiona la estadística del gobierno y la eficacia de las medidas que está tomando. Centro de Investigación Periodística (CIPER). 2020. [On line]. | Link |

Prem K, Liu Y, Russell TW, Kucharski AJ, Eggo RM, Davies N, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. Lancet Public Health. 2020 May;5(5):e261-e270. | CrossRef | PubMed |

Michael L, Golden K, Lewis M, Nishiura Y, Sambridge M, Tribbia J, et al. An Introduction to Mathematical Modeling of Infectious Diseases. 2a Ed. Cham: Springer International; 2018.

López LR, Rodó X. A modified SEIR model to predict the COVID-19 outbreak in Spain and Italy: simulating control scenarios and multi-scale epidemics. 2020. [On line]. | Link |

Yang Z, Zeng Z, Wang K, Wong SS, Liang W, Zanin M, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J Thorac Dis. 2020 Mar;12(3):165-174. | CrossRef | PubMed |

Rojas-Vallejos J. Strengths and limitations of mathematical models in pandemicsthe case of COVID-19 in Chile. Medwave. 2020 Apr 8;20(3):e7876. | CrossRef | PubMed |

Ojeda JM, Cabrera B, Castillo V. ¿Cuánto tardan los resultados de los test? Gobierno admite demora de al menos 48 horas y hospitales, de hasta cinco días. La Tercera. 2020. [On line]. | Link |