Academic Journal
Un Modelo Matemático SIR-D Segmentado para la Dinámica de Propagación del Coronavirus (COVID-19) en el Perú
| العنوان: | Un Modelo Matemático SIR-D Segmentado para la Dinámica de Propagación del Coronavirus (COVID-19) en el Perú |
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| المؤلفون: | Neisser Pino Romero, Percy Soto-Becerra, Ricardo Angelo Quispe Mendizábal |
| المصدر: | Selecciones Matemáticas, Vol 7, Iss 01, Pp 162-171 (2020) |
| بيانات النشر: | Universidad Nacional de Trujillo, 2020. |
| سنة النشر: | 2020 |
| المجموعة: | LCC:Applied mathematics. Quantitative methods LCC:Mathematics |
| مصطلحات موضوعية: | coronavirus (covid-19), epidemiology, ordinary differential equations, computational simulation, regression methods, Applied mathematics. Quantitative methods, T57-57.97, Mathematics, QA1-939 |
| الوصف: | The present study proposes the use of a segmented SIR-D mathematical model to predict the evolution of epidemiological populations of interest in the COVID-19 pandemic (Susceptible [S], Infected [I], Recovered [R] and dead [D]), information that is often key to guiding decision-making in the fight against epidemics. In order to obtain a better model calibration and a lower prediction error in the short term, we performed the model segmentation in 6 stages of periods of 14 days each. At each stage, the epidemiological that define the system of equations are empirically estimated by linear regression of the epidemiological surveillance data that the Peruvian Ministry of Health collects and reports daily. This strategy showed better model calibration compared to an unsegmented SIR-D model. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | Spanish; Castilian |
| تدمد: | 2411-1783 |
| Relation: | https://revistas.unitru.edu.pe/index.php/SSMM/article/view/2970; https://doaj.org/toc/2411-1783 |
| DOI: | 10.17268/sel.mat.2020.01.15 |
| URL الوصول: | https://doaj.org/article/89635fbf2d0f46fcafc052b52a643c79 |
| رقم الانضمام: | edsdoj.89635fbf2d0f46fcafc052b52a643c79 |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 24111783 |
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| DOI: | 10.17268/sel.mat.2020.01.15 |