A Cybernetics-based Dynamic Infection Model for Analyzing SARS-COV-2 Infection Stability and Predicting Uncontrollable Risks

Wenlei Xiao; Qiang Liu; J Huan; Pengpeng Sun; Liuquan Wang; Chenxin Zang; Sanying Zhu; Liansheng Gao

Wenzhou is another featured city that was found particular with a relatively high R 0 , up to 4.5 (as shown in Fig. 10 ). Deeper investigations were taken, and it was found that the imported infectious cases from Wuhan to Wenzhou were mostly from Huanan Seafood Wholesale Market. So we may consider Wenzhou as a sub-sample of Wuhan. This phenomenon can be thus explained, and alerts should have been announced to eliminate the instable risk and slow down the spread speed in Wenzhou. In contrast, the inter link between Wuhan and Wenzhou helps to observe the current status of Wuhan, whose parameters could be reused in spite of the differences in their model types. After the first-level response on Jan 23, 2020, R 0 decreases significantly down to 0.5 (95% CI, 0.435 to 0.556), which means both social and administrative manipulations start to work correspondingly. Provided the latest R 0 is stabilized, the final number of infected cases in Wenzhou is estimated to be 527 (95% CI, 475 to 582). From the fitted curve, we could have deduced the stability of Wenzhou even early at Feb 01, 2020.