scholarly journals Estimating the time-varying reproduction number of COVID-19 with a state-space method

2021 ◽  
Vol 17 (1) ◽  
pp. e1008679
Author(s):  
Shinsuke Koyama ◽  
Taiki Horie ◽  
Shigeru Shinomoto
Keyword(s):  
State Space ◽  
Reproduction Number ◽  
Spreading Rate ◽  
State Space Method ◽  
Infected Case ◽  
Social Events ◽  
Trace Back ◽  
Novel Coronavirus ◽  
The Impact ◽  
Space Method

After slowing down the spread of the novel coronavirus COVID-19, many countries have started to relax their confinement measures in the face of critical damage to socioeconomic structures. At this stage, it is desirable to monitor the degree to which political measures or social affairs have exerted influence on the spread of disease. Though it is difficult to trace back individual transmission of infections whose incubation periods are long and highly variable, estimating the average spreading rate is possible if a proper mathematical model can be devised to analyze daily event-occurrences. To render an accurate assessment, we have devised a state-space method for fitting a discrete-time variant of the Hawkes process to a given dataset of daily confirmed cases. The proposed method detects changes occurring in each country and assesses the impact of social events in terms of the temporally varying reproduction number, which corresponds to the average number of cases directly caused by a single infected case. Moreover, the proposed method can be used to predict the possible consequences of alternative political measures. This information can serve as a reference for behavioral guidelines that should be adopted according to the varying risk of infection.

scholarly journals Estimating the time-varying reproduction number of COVID-19 with a state-space method

2020 ◽  
Author(s):  
Shinsuke Koyama ◽  
Taiki Horie ◽  
Shigeru Shinomoto
Keyword(s):  
State Space ◽  
Reproduction Number ◽  
Spreading Rate ◽  
State Space Method ◽  
Infected Case ◽  
Social Events ◽  
Trace Back ◽  
Novel Coronavirus ◽  
The Impact ◽  
Space Method

After slowing down the spread of the novel coronavirus COVID-19, many countries have started to relax their confinement measures in the face of critical damage to socioeconomic structures. At this stage, it is desirable to monitor the degree to which political measures or social affairs have exerted influence on the spread of disease. Though it is difficult to trace back individual transmission of infections whose incubation periods are long and highly variable, estimating the average spreading rate is possible if a proper mathematical model can be devised to analyze daily event-occurrences. To render an accurate assessment, we have devised a state-space method for fitting the Hawkes process to a given dataset of daily confirmed cases. The proposed method detects changes occurring in each country and assesses the impact of social events in terms of the temporally varying reproduction number, which corresponds to the average number of cases directly caused by a single infected case. Moreover, the proposed method can be used to predict the possible consequences of alternative political measures. This information can serve as a reference for behavioral guidelines that should be adopted according to the varying risk of infection.

Study on Dynamic Characteristics of the Bridge Crane Hoisting Mechanism Based on State-Space Method

2014 ◽  
Vol 1061-1062 ◽  
pp. 739-742
Author(s):  
An Liu ◽  
Wei He ◽  
Zhe Kun Li ◽  
Li Cheng
Keyword(s):  
State Space ◽  
Dynamic Characteristics ◽  
Bridge Crane ◽  
Bridge Structure ◽  
State Space Method ◽  
Vibration Model ◽  
Simulation Based ◽  
The Impact ◽  
Input Torque ◽  
Space Method

The dynamic characteristics researches of the bridge crane hoisting mechanism were summarized. Four-freedom-degree elasticity vibration model was established according to actual working condition of bridge crane hoisting mechanism. It considered the impact of the input torque, the stiffness of wire rope and so on. The paper applied to the state-space method to solve the numerical value and simulation based on the Matlab/Simulink software. It contained the hoisting displacement and speed curve, and the bridge structure volatility curve. The simulation results show that the correctness of the model, which lay the theoretical basis for all kinds of hoisting mechanism dynamic characteristics research in dynamic problems

A new state-space method for exponentially damped linear systems

2019 ◽  
Vol 212 ◽  
pp. 137-144 ◽  
Author(s):  
Xinhai Wu ◽  
Huan He ◽  
Guoping Chen
Keyword(s):  
State Space ◽  
Linear Systems ◽  
State Space Method ◽  
Space Method

Study on Small Fluctuation Stability in Air Cushion Surge Chamber Based on State Space Method

2017 ◽  
Author(s):  
Jiachun Liu ◽  
Jian Zhang ◽  
Xiaodong Yu ◽  
Hui Xie
Keyword(s):  
State Space ◽  
Great Influence ◽  
State Space Method ◽  
Actual System ◽  
Small Fluctuation ◽  
Chamber Height ◽  
Air Chamber ◽  
Water Conveyance ◽  
Air Cushion ◽  
Space Method

In this paper, on the basis of the state space method and actual system arrangement, the small fluctuation mathematical model of the water conveyance system with air cushion surge chamber (ACSC) was established. According to the basic equations of ACSC, the ideal gas state equation and the units constant output equation, the formula describing the stable cross-section area (SCSA) of ACSC was deduced, and the small fluctuation stability (SFS) of water conveyance system was analyzed. The corresponding results showed that the air chamber constant had a great influence on the SCSA of ACSC. When the air chamber constant became larger, the quality of the system small fluctuation went worse. The higher upstream water level and the lower initial air chamber height will lead to a smaller initial air chamber constant of ACSC, which is destructive for the stability of the system small fluctuation; As long as the equivalent air quality and air chamber volume are constant, good quality system small fluctuations could be obtained when the initial air chamber height is small and the area of ACSC is large.

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