Loading [MathJax]/extensions/MathZoom.js
Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model | IEEE Journals & Magazine | IEEE Xplore

Early Prediction of the 2019 Novel Coronavirus Outbreak in the Mainland China Based on Simple Mathematical Model


The flow diagram of early prediction of the 2019-nCoV. The early-stage epidemiological data is firstly analyzed to rule out unreasonable part with considering historical ...

Abstract:

The 2019 novel coronavirus (2019-nCoV) outbreak has been treated as a Public Health Emergency of International Concern by the World Health Organization. This work made an...Show More

Abstract:

The 2019 novel coronavirus (2019-nCoV) outbreak has been treated as a Public Health Emergency of International Concern by the World Health Organization. This work made an early prediction of the 2019-nCoV outbreak in China based on a simple mathematical model and limited epidemiological data. Combing characteristics of the historical epidemic, we found part of the released data is unreasonable. Through ruling out the unreasonable data, the model predictions exhibit that the number of the cumulative 2019-nCoV cases may reach 76,000 to 230,000, with a peak of the unrecovered infectives (22,000-74,000) occurring in late February to early March. After that, the infected cases will rapidly monotonically decrease until early May to late June, when the 2019-nCoV outbreak will fade out. Strong anti-epidemic may reduce the cumulative infected cases by 40%-49%. The improvement of medical care can also lead to about one-half transmission decrease and effectively shorten the duration of the 2019-nCoV.
The flow diagram of early prediction of the 2019-nCoV. The early-stage epidemiological data is firstly analyzed to rule out unreasonable part with considering historical ...
Published in: IEEE Access ( Volume: 8)
Page(s): 51761 - 51769
Date of Publication: 09 March 2020
Electronic ISSN: 2169-3536
PubMed ID: 32391240

Funding Agency:


References

References is not available for this document.