• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

PLoS One . Prediction of the COVID-19 epidemic trends based on SEIR and AI models

tetano

Editor, Senior Moderator
PLoS One


. 2021 Jan 8;16(1):e0245101.
doi: 10.1371/journal.pone.0245101. eCollection 2021.
Prediction of the COVID-19 epidemic trends based on SEIR and AI models


Shuo Feng[SUP] 1 [/SUP], Zebang Feng[SUP] 1 [/SUP], Chen Ling[SUP] 2 [/SUP], Chen Chang[SUP] 3 [/SUP], Zhongke Feng[SUP] 3 [/SUP]



Affiliations

Abstract

In December 2019, the outbreak of a new coronavirus-caused pneumonia (COVID-19) in Wuhan attracted close attention in China and the world. The Chinese government took strong national intervention measures on January 23 to control the spread of the epidemic. We are trying to show the impact of these controls on the spread of the epidemic. We proposed an SEIR(Susceptible-Exposed-Infectious-Removed) model to analyze the epidemic trend in Wuhan and use the AI model to analyze the epidemic trend in non-Wuhan areas. We found that if the closure was lifted, the outbreak in non-Wuhan areas of mainland China would double in size. Our SEIR and AI model was effective in predicting the COVID-19 epidemic peaks and sizes. The epidemic control measures taken by the Chinese government, especially the city closure measures, reduced the scale of the COVID-19 epidemic.



Conflict of interest statement

The authors have declared that no competing interests exist.
 
Back
Top Bottom