Modeling COVID-19 epidemic in Heilongjiang province, China

被引:79
|
作者
Sun, Tingzhe [1 ]
Wang, Yan [1 ]
机构
[1] Anqing Normal Univ, Sch Life Sci, 1318 North Jixian Rd, Anqing 246011, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
COVID-19; Epidemic; Asymptomatic patient; Imported patient;
D O I
10.1016/j.chaos.2020.109949
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The Coronavirus Disease 2019 (COVID-19) surges worldwide. However, massive imported patients especially into Heilongjiang Province in China recently have been an alert for local COVID-19 outbreak. We collected data from January 23 to March 25 from Heilongjiang province and trained an ordinary differential equation model to fit the epidemic data. We extended the simulation using this trained model to characterize the effect of an imported 'escaper'. We showed that an imported 'escaper' was responsible for the newly confirmed COVID-19 infections from Apr 9 to Apr 19 in Heilongjiang province. Stochastic simulations further showed that significantly increased local contacts among imported 'escaper', its epidemiologically associated cases and susceptible populations greatly contributed to the local outbreak of COVID-19. Meanwhile, we further found that the reported number of asymptomatic patients was markedly lower than model predictions implying a large asymptomatic pool which was not identified. We further forecasted the effect of implementing strong interventions immediately to impede COVID-19 outbreak for Heilongjiang province. Implementation of stronger interventions to lower mutual contacts could accelerate the complete recovery from coronavirus infections in Heilongjiang province. Collectively, our model has characterized the epidemic of COVID-19 in Heilongjiang province and implied that strongly controlled measured should be taken for infected and asymptomatic patients to minimize total infections. (c) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:5
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