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Forecasting the Cumulative Number of COVID-19 Deaths in China: a Boltzmann Function-based Modeling Study | |
Cheng Long Qi Ying Zhongyan Li Yuanyuan Gao Xinmiao Fu | |
Novel Coronavirus | |
Acceso Abierto | |
Atribución-NoComercial-SinDerivadas | |
10.1101/2020.03.02.20030064 | |
The COVID-19 outbreak is on-going in China. Here we estimated the potential total numbers of COVID-19 deaths in China, outside Hubei (in China), Hubei Province, Wuhan City and outside Wuhan (in Hubei) by Boltzmann function-based analyses, which are 3342 (95% CI, 3214, 3527), 111 (109, 114), 3245 (3100, 3423), 2613 (2498, 2767) and 627 (603, 654), respectively. The results may help to evaluate the severity of COVID-19 outbreaks and facilitate timely mental service for the families of passed patients. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work is support by the National Natural Science Foundation of China (No. 31972918 and 31770830 to XF). ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes all data are included in the manuscript and supplementary data file. | |
Cold Spring Harbor Laboratory Press | |
2020 | |
Preimpreso | |
https://www.medrxiv.org/content/10.1101/2020.03.02.20030064v3 | |
Inglés | |
VIRUS RESPIRATORIOS | |
Aparece en las colecciones: | Artículos científicos |
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