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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/202| Novel Coronavirus 2019 (Covid-19) epidemic scale estimation: topological network-based infection dynamic model | |
| Keke Tang Yining Huang Meilian Chen | |
| Novel Coronavirus | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2020.02.20.20023572 | |
| Backgrounds: An ongoing outbreak of novel coronavirus pneumonia (Covid-19) hit Wuhan and hundreds of cities, 29 territories globally. We present a method for scale estimation in dynamic while most of the researchers used static parameters. Methods: We use historical data and the SEIR model for important parameters assumption. And according to the timeline, we use dynamic parameters for infection topology network building. Also, the migration data is used for the Non-Wuhan area estimation which can be cross-validated for the Wuhan model. All data are from the public. Results: The estimated number of infections is 61,596 (95%CI: 58,344.02-64,847.98) by 25 Jan in Wuhan. And the estimation number of the imported cases from Wuhan of Guangzhou was 170 (95%CI: 161.27-179.26), infection scale in Guangzhou is 315 (95%CI: 109.20-520.79), while the imported cases are 168 and the scale of the infection is 339 published by the authority. Conclusions: Using dynamic network models and dynamic parameters for different time periods is an effective way of infection scale modeling. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement No external funding was received in this study. ### 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 Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.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 were from the public. | |
| Cold Spring Harbor Laboratory Press | |
| 2020 | |
| Preimpreso | |
| https://www.medrxiv.org/content/10.1101/2020.02.20.20023572v2 | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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| Novel coronavirus 2019.pdf | 258.67 kB | Adobe PDF | Visualizar/Abrir |