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

The spread speed of SARS-CoV-2 has been emergently challenging many cities in China, especially those cities in Hubei province (Wuhan, Huanggang, Xiaogan, etc.) [1] . During the currently still happening disaster, people and governments have gradually enhanced the strength of responses. Three Chinese cities (Wuhan, Huanggang and Ezhou) were shut down on Jan 23, 2020 to contain the rapidly-spreading virus; In most of Chinese cities, The first-level public health emergency response was activated on Jan 24, 2020; Huoshenshan and Leishenshan hospitals were built in less than two weeks to admit and treat patients at the epicenter of the virus; After Feb 2, 2020, Wuhan start to convert gymnasiums and exhibition centers into temporary shelter(fangcang) hospitals to accept and quarantine patients with mild symptoms. Tens of thousands of doctors and nurses from all over China have been sent to Wuhan. It seams we have always been pushed into a defensive position, that the responses were always later than the developing epidemic status. As a spontaneously summoned team, we have continuously followed the progress of this epidemic, and believe that we have found a novel forecast model to solve this problem. Base on this model, corresponding responses could be activated before the uncontrollable risks really happen.