Author: Wenlei Xiao; Qiang Liu; J Huan; Pengpeng Sun; Liuquan Wang; Chenxin Zang; Sanying Zhu; Liansheng Gao
Title: A Cybernetics-based Dynamic Infection Model for Analyzing SARS-COV-2 Infection Stability and Predicting Uncontrollable Risks Document date: 2020_3_17
ID: 2v5wkjrq_20
Snippet: In views of those differences, we improved the SARS model to CDIM, as shown in Fig. 4 . The infection from immigration or the origin source (i.e. the Huanan Seafood Wholesale Market in Wuhan) is taken as the system input. The infection main loop generates the rapid reproduced infection. The equivalent infection rate C 0 indicates the infected cases per virus carrier per day. The contact tracing rate 1 − C 1 represents the effect of contact trac.....
Document: In views of those differences, we improved the SARS model to CDIM, as shown in Fig. 4 . The infection from immigration or the origin source (i.e. the Huanan Seafood Wholesale Market in Wuhan) is taken as the system input. The infection main loop generates the rapid reproduced infection. The equivalent infection rate C 0 indicates the infected cases per virus carrier per day. The contact tracing rate 1 − C 1 represents the effect of contact tracing of patients. The incubation bypass emulates the process of symptom onset. Since the incubation period T 1 follows a Poisson distribution, the factor λ should be identified (see Eq. 1).
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