Por favor, use este identificador para citar o enlazar este ítem: http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/540
Short-term Forecasts of the COVID-19 Epidemic in Guangdong and Zhejiang, China: February 13–23, 2020
Kimberlyn Roosa
Yiseul Lee
Ruiyan Luo
Alexander Kirpich
Richard Rothenberg
James Hyman
Ping Yan
Gerardo Chowell
Acceso Abierto
Atribución
https://doi.org/10.3390/jcm9020596
COVID-19
Phenomenological models
Sub-epidemic model
The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic’s epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65–81 cases (upper bounds: 169–507) in Guangdong and an additional 44–354 (upper bounds: 141–875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down.
Journal of Clinical Medicine
22-02-2020
Artículo
https://www.mdpi.com/2077-0383/9/2/596
Inglés
Epidemia COVID-19
Investigadores
VIRUS RESPIRATORIOS
Versión publicada
publishedVersion - Versión publicada
Aparece en las colecciones: Artículos científicos

Cargar archivos: