Author: Peiliang SUN; Kang Li
Title: An SEIR Model for Assessment of Current COVID-19 Pandemic Situation in the UK Document date: 2020_4_17
ID: 9mdxid0u_1
Snippet: Authors in [9] analysed the probability distribution of onset to death and onset to recover time, and the proportion of all infections that would lead to hospitalisation according the data in China. These statistic data are used in this paper to formulate the time delay of COVID-19 status transition with the probability distribution over time. Figure 2 illustrates the basic structure of the SEIR model, a SIR derivative, where S(t) represents the .....
Document: Authors in [9] analysed the probability distribution of onset to death and onset to recover time, and the proportion of all infections that would lead to hospitalisation according the data in China. These statistic data are used in this paper to formulate the time delay of COVID-19 status transition with the probability distribution over time. Figure 2 illustrates the basic structure of the SEIR model, a SIR derivative, where S(t) represents the susceptible cases at day t, E(t) is for the exposed cases at day t, I(t) stands for the infectious cases at day t and I Σ (t) denotes the total infected population at day t. R(t) and D(t) represent the cumulative recovered cases and cumulative deaths till day t respectively. The total of cases that may need hospital treatment at day t is denoted as H(t), while Q(t) represents the quarantined cases at day t. The time variable is t = 1, 2, · · · , K and K is the prediction horizon.
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