The outbreak of coronavirus disease 2019(COVID-19)has aroused a global alert.To release social panic and guide future schedules,this article proposes a novel mathematical model,the Delay Differential Epidemic Analyzer...The outbreak of coronavirus disease 2019(COVID-19)has aroused a global alert.To release social panic and guide future schedules,this article proposes a novel mathematical model,the Delay Differential Epidemic Analyzer(D2EA),to analyze the dynamics of epidemic and forecast its future trends.Based on the traditional Susceptible-Exposed-Infectious-Recovered(SEIR)model,the D2EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states.Potential variations of practical factors are further considered to reveal the true epidemic picture.In the experiment part,we use the D^2EA model to simulate the epidemic in Hubei Province.Fitting to the collected real data as non-linear optimization,the D^2EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down.We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.展开更多
The outbreak of coronavirus disease 2019(COVID-19)has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic.Therefore,it will be helpful to predict the tendency o...The outbreak of coronavirus disease 2019(COVID-19)has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic.Therefore,it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies.Existing models for prediction,such as cabin models and individual-based models,are either oversimplified or too meticulous,and the influence of the epidemic was studied much more than that of official policies.To predict the epidemic tendency,we consider four groups of people,and establish a propagation dynamics model.We also create a negative feedback to quantify the public vigilance to the epidemic.We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country.Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78191(prediction interval,74872 to 82474).By changing the parameters of the model accordingly,we demonstrate the control effect of the policies of the government on the epidemic situation,which can reduce about 68%possible infections.At the same time,we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.展开更多
基金the National Key Research and Development Program of China(No.2018YFB1004700)the National Natural Science Foundation of China(Nos.61872238 and 61972254)+1 种基金the Shanghai Science and Technology Fund(No.17510740200)the CCF-Huawei Database System Innovation Research Plan(No.CCF-Huawei DBIR2019002A)。
文摘The outbreak of coronavirus disease 2019(COVID-19)has aroused a global alert.To release social panic and guide future schedules,this article proposes a novel mathematical model,the Delay Differential Epidemic Analyzer(D2EA),to analyze the dynamics of epidemic and forecast its future trends.Based on the traditional Susceptible-Exposed-Infectious-Recovered(SEIR)model,the D2EA model innovatively introduces a set of quarantine states and applies both ordinary differential equations and delay differential equations to describe the transition between two states.Potential variations of practical factors are further considered to reveal the true epidemic picture.In the experiment part,we use the D^2EA model to simulate the epidemic in Hubei Province.Fitting to the collected real data as non-linear optimization,the D^2EA model forecasts that the accumulated confirmed infected cases in Hubei Province will reach the peak at the end of February and then steady down.We also evaluate the effectiveness of the quarantine measures and schedule the date to reopen Hubei Province.
基金the National Key Research and Development Program of China(No.2018YFB1004700)the National Natural Science Foundation of China(Nos.61872238 and 61972254)+1 种基金the Shanghai Science and Technology Fund(No.17510740200)the CCFHuawei Database System Innovation Research Plan(No.CCF-Huawei DBIR2019002A)。
文摘The outbreak of coronavirus disease 2019(COVID-19)has been spreading rapidly in China and the Chinese government took a series of policies to control the epidemic.Therefore,it will be helpful to predict the tendency of the epidemic and analyze the influence of official policies.Existing models for prediction,such as cabin models and individual-based models,are either oversimplified or too meticulous,and the influence of the epidemic was studied much more than that of official policies.To predict the epidemic tendency,we consider four groups of people,and establish a propagation dynamics model.We also create a negative feedback to quantify the public vigilance to the epidemic.We evaluate the tendency of epidemic in Hubei and China except Hubei separately to predict the situation of the whole country.Experiments show that the epidemic will terminate around 17 March 2020 and the final number of cumulative infections will be about 78191(prediction interval,74872 to 82474).By changing the parameters of the model accordingly,we demonstrate the control effect of the policies of the government on the epidemic situation,which can reduce about 68%possible infections.At the same time,we use the capital asset pricing model with dummy variable to evaluate the effects of the epidemic and official policies on the revenue of multiple industries.
