Policy and Law Assessment of COVID-19 Based on Smooth Transition Autoregressive Model

As of the end October 2020, cumulative number confirmed cases COVID-19 has exceeded 45 million and deaths 1.1 all over world. Faced with fatal pandemic, countries around world have taken various prevention control measures. One important issues in epidemic is assessment effectiveness. Changes time series daily new can reflect impact policies certain regions. In this paper, a smooth transition autoregressive (STAR) model applied to investigate intrinsic changes during order quantitatively evaluate influence measures, sequence fitted STAR model; then, comparisons between dates points those releasing are applied. Our well fits data. Moreover, nonlinear function within reveals that implementation effective some regions different speeds. However, ineffectiveness also revealed threat second wave had already emerged.