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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

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Abstract

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。

方法:根据2019-nCov的传播特征,构建一个新颖的暴露-感染(EI)系统动力学模型。该模型整合了流行病传播的两个阶段:干预之前和干预之后。我们认为,2019-nCov首先在没有干预的情况下传播,然后政府开始采取强有力的隔离措施。使用中华人民共和国国家卫生委员会的最新报告数据,我们估计了该模型的基本参数以及2019-nCov的感染基数。然后,基于此模型,我们模拟了流行病的未来传播。估计了不同预防政策情景下的感染人口和2019-nCov的传播时间。并分析比较了隔离率和干预时间点的影响。

调查结果:在我们的基准情景中,政府采取了严格的预防措施,估计数字与官方数字非常吻合。毫无疑问,官方数字是准确的。我们估计,2019-nCoV的感染基数为2.985,到2020年2月16日的最高感染人数将是49093。然后,疫情传播将在2020年3月底逐渐消失。检疫率和开始时间干预措施的开展对流行病的传播有很大影响。此外,如果将隔离率从100%降至63%以下(这是控制疫情蔓延的隔离率的阈值),则疫情蔓延将永远不会消失。最后,根据严格预防措施下不同行动开始日期的模拟,如果将干预开始日期比当前日期推迟2020年1月23日1天,则高峰感染人口将增加大约6351。如果延迟3或7天的高峰期将是70714和115022,这意味着将增加21621和65929。

解释:鉴于中国采取的强有力的预防措施,可以控制2019-nCoV,这大约需要三个月。在控制的开始时间点之后,确诊的受感染个体仍将保持快速增长14天(大约等于暴露期和感染期的总和)。在流行冠状病毒之前应坚持强有力的预防措施。国内其他地方和海外已确认感染者应立即采取强有力的干预措施。早期有力的预防措施可以有效地阻止全球其他城市的疫情自我爆发。

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: https://ssrn.com/abstract=3537083 or http://dx.doi.org/10.2139/ssrn.3537083

Hao Xiong

Hainan University - Department of Management Sciences

China

Huili Yan (Contact Author)

Hainan University - Department of Tourism Management ( email )

United States

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