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

Linhao Zhong,Darong Liu,Jiaying Wang,Jing Li,Zhe Yin,Lin Mu

doi:10.1109/access.2020.2979599

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 measures 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.

Highlights

Since December 31 2019, the 27 cases of unknown pneumonia were reported in Wuhan City of Hubei Province in South China [1]
On 7 January 2020, Chinese government and the World Health Organization (WHO) identified a novel coronavirus (2019-nCoV) as the causative virus, which belongs to the same virus family of the Severe Acute Respiratory Syndrome (SARS) that outbroke in South China in 2002-2003 [2]
RESULTS the 2019-nCoV is a member of the coronavirus, the 2019-nCoV still shows some different characteristics from SARS

Summary

INTRODUCTION

Since December 31 2019, the 27 cases of unknown pneumonia were reported in Wuhan City of Hubei Province in South China [1]. On 7 January 2020, Chinese government and the World Health Organization (WHO) identified a novel coronavirus (2019-nCoV) as the causative virus, which belongs to the same virus family of the Severe Acute Respiratory Syndrome (SARS) that outbroke in South China in 2002-2003 [2]. Mathematical modelling has gained more attention and awareness in epidemiology and the medical sciences [8]–[10] One family of these models is the dynamical epidemic model called Susceptible-Infected-Removed (SIR) model [11]. We tried to present an early prediction of the epidemic of the 2019-nCoV based a simplified SIR model. Focusing on the infection rate and removal rate, several experiments were designed to simulate the spreading of 2019-nCoV under different levels of anti-epidemic measure and medical care. Our results are supposed to provide important information for the crisis management against the novel coronavirus

DATA AND METHODS

SIMPLIFIED SIR MODEL

METHOD OF PARAMETER ESTIMATION

RESULTS

DISCUSSION