Análisis
Medwave 2020;20(4):e7898 doi: 10.5867/medwave.2020.04.7898
Proyección epidemiológica de COVID-19 en Chile basado en el modelo SEIR generalizado y el concepto de recuperado
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
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Palabras clave: 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.


 

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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.

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

Filiación:
[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

Correspondencia a:
[1] Angamos 655
Viña del Mar, Chile
Código postal: 2540064

Citación: 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

Fecha de envío: 14/4/2020

Fecha de aceptación: 30/4/2020

Fecha de publicación: 15/5/2020

Origen: No solicitado

Tipo de revisión: Con revisión por pares externa, por tres árbitros a doble ciego

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  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 |