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Simulating the Infected Population and Spread Trend of 2019-nCov Under Different Policy by EIR Model (EIR模型模拟不同政策下2019-nCov的感染人口和传播趋势)

11 Pages Posted: 13 Feb 2020

See all articles by Hao Xiong

Hao Xiong

Hainan University - Department of Management Sciences

Huili Yan

Hainan University - Department of Tourism Management



English Abstract: Background: Chinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. However, the common forecasting models, such as SI, SIS, SIR, SIRS and SEIR, are only suit for scenarios without non-pharmaceutical prevention interventions. And the estimating infected populations from existing literature are too far more than the official reported data. Here, we provide a two-phase EI model integrated the epidemic spreading before and after control measures. Then, we estimate of the size of the epidemic and simulate the future development of the epidemics under strong prevention interventions.

Methods: According to the spread characters of 2019-nCov, we construct a novel exposed-infected (EI) compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported data from National Health Commission of the People’s Republic of China, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the development time of 2019-nCov under different prevention policy scenarios are estimated. And, the influences of the quarantine rate and the intervention time point of prevention intervention policy are analyzed and compared.

Findings: In our baseline scenario, the government takes the strict prevention actions, the estimate numbers fit the official numbers very well. There can be no doubt that the official numbers are accurate. We estimated that the basic reproductive number for 2019-nCoV was 2.985 and that the peak infected individuals will be 49093 at Feb.16, 2020. And then the epidemic spreading will fade out at the end of March 2020. The quarantine rate and the starting date point of intervention have great effect on the epidemic spreading. Furthermore, if the quarantine rate is reduced from 100% to less than 63%, which is the threshold of the quarantine rate to control the epidemic spreading, the epidemic spreading would not never be fade out. Finally, from the simulation of different action starting date under the strict prevention measures, if the starting date of intervention is delayed for 1 day than the current date Jan. 23, 2020, the peak infected population will increase about 6351. If the delay 3 days or 7 days the peak number would be 70714 and 115022 individuals, which means increasing 21621 and 65929 individuals.

Interpretation: Given that 2019-nCoV could be controlled under the strong prevention measures of what China has taken and it will take about three months. The confirmed infected individuals will still keep quick increasing for 14 days (approximately equal to the sum of exposed period and infection period) after the start time point of control. The strong prevention measures should be insisted until the epidemic Coronavirus. Other domestic places and overseas have confirmed infected individuals should take strong interventions immediately. Earlier strong prevention measures could efficiently stop the independent self-sustaining outbreaks in other cities globally.

Funding: This work was supported by National Natural Science Foundation of China (Grant No. 71761009, No. 71461007 and No. 71461006) and Hainan Province Planning Program of Philosophy and Social Science (HNSK(YB)19-06, HNSK(YB)19-11).

Declaration of Interest: We declare no competing interests.

Mandarin Abstract: 背景:从2020年1月23日起,中国政府已采取有力措施应对新型冠状病毒(2019-nCoV)的流行。确诊感染人数仍在迅速增加。在控制措施下估计准确的感染人群和流行趋势的未来趋势是重要且紧迫的。但是,常见的预测模型(例如SI,SIS,SIR,SIRS和SEIR)仅适用于没有预防干预措施的情况。而且从现有文献中估计受感染的人口远远超过官方报告的数据。在这里,我们提供了一个两阶段的EI模型,该模型综合了控制措施前后的流行病传播情况。然后,我们估计了流行病的规模,并在强有力的预防干预措施下模拟了流行病的未来发展。




Keywords: simulation; forecasting; 2019-nCoV; epidemic spreading; transmission model

Suggested Citation

Xiong, Hao and Yan, Huili, Simulating the Infected Population and Spread Trend of 2019-nCov Under Different Policy by EIR Model (EIR模型模拟不同政策下2019-nCov的感染人口和传播趋势) (2/8/2020). Available at SSRN: or

Hao Xiong

Hainan University - Department of Management Sciences


Huili Yan (Contact Author)

Hainan University - Department of Tourism Management ( email )

United States

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