Revealing the influence of national public health policies for the outbreak of the SARS-CoV-2 epidemic in Wuhan, China through status dynamic modeling

tianyi qiu; Han Xiao

Here, we proposed a status dynamic Susceptible-Exposed-Infectious-Out of the system (with Medical care/maximum beds in Hospital) SEIO (MH) model, to reveal the influence of the national public health response for the SARS-CoV-2 epidemics outbreak in Wuhan, China. Different from the traditional Susceptible-Exposed-Infectious-Recovered (SEIR) continuous model 13 . SEIO(MH) model is a real-time discrete model with two more essential parameters: 1) the number of people with medical care (M), and 2) the currently available beds in hospitals. The local status dynamic SEIO (MH) model could simulate the population in each status at any date during the epidemic. Also, this model could simulate multiple national public health responses including: 1) lockdown of the traffic in one city, 2) the hospital bed shortage as well as the amelioration in the medical system when multiple converted hospitals are available, and 3) the temporary public gathering events.