Author: Yuan Zhang; Chong You; Zhenghao Cai; Jiarui Sun; Wenjie Hu; Xiao-Hua Zhou
Title: Prediction of the COVID-19 outbreak based on a realistic stochastic model Document date: 2020_3_13
ID: 0xzsa21a_4
Snippet: Besides the ODE models, an even older approach is to discretize the time and consider a difference equation (DE) model, which can be seen as a self-propelled sequence of numbers (or vectors). In such models, the increment or decrement of different compartment at each step is a function of the configuration in the previous step (s) . Earliest examples of a DE include the well-known geometric and Fibonacci sequence, which can both be used to descri.....
Document: Besides the ODE models, an even older approach is to discretize the time and consider a difference equation (DE) model, which can be seen as a self-propelled sequence of numbers (or vectors). In such models, the increment or decrement of different compartment at each step is a function of the configuration in the previous step (s) . Earliest examples of a DE include the well-known geometric and Fibonacci sequence, which can both be used to describe the growth of a biological population. Recently, a discrete time DE model was introduced in Yang et al. (2020) to predict the epidemic trend of COVID-19. The proposed model correctly took the infectious incubation into account. However, this model did not consider the time lag between symptoms onset and diagnosis or the medical tracking. Besides, the rationale behind the assumption of the equal transmission probability between symptomatic and asymptomatic patients is questionable.
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