Simulating the Infected Population and Spread Trend of 2019-nCov Under Different Policy by EIR Model
11 Pages Posted: 13 Feb 2020
Hao Xiong
Hainan University - Department of Management Sciences
Huili Yan
Hainan University - Department of Tourism Management
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.
