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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/2274
Modelling death rates due to COVID-19: A Bayesian approach | |
Cristian Bayes. Victor Sal y Rosas. Luis Valdivieso. | |
Acceso Abierto | |
Atribución-NoComercial-SinDerivadas | |
https://arxiv.org/pdf/2004.02386v2.pdf | |
Objective: To estimate the number of deaths in Peru due to COVID-19. Design: With a priori information obtained from the daily number of deaths due to CODIV-19 in China and data from the Peruvian authorities, we constructed a predictive Bayesian non-linear model for the number of deaths in Peru. Exposure: COVID-19. Outcome: Number of deaths. Results: Assuming an intervention level similar to the one implemented in China, the total number of deaths in Peru is expected to be 612 (95%CI: 604.3 - 833.7) persons. Sixty four days after the first reported death, the 99% of expected deaths will be observed. The inflexion point in the number of deaths is estimated to be around day 26 (95%CI: 25.1 - 26.8) after the first reported death. Conclusion: These estimates can help authorities to monitor the epidemic and implement strategies in order to manage the COVID-19 pandemic. | |
arxiv.org | |
2020 | |
Artículo | |
https://arxiv.org/pdf/2004.02386v2.pdf | |
Inglés | |
VIRUS RESPIRATORIOS | |
Aparece en las colecciones: | Artículos científicos |
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