Changes of Spatiotemporal Pattern and Network Characteristic in Population Flow under COVID-19 Epidemic

The COVID-19 pandemic is a major problem facing humanity throughout the world. rapid and accurate tracking of population flows may therefore be epidemiologically informative. This paper adopts massive amount daily flow data (from January 10 to March 15, 2020) for China obtained from Baidu Migration platform analyze changes spatiotemporal patterns network characteristics in during pre-outbreak period, outbreak post-peak period. results show that (1) temporal flow, total varies greatly between three periods, with an overall trend period > flow. Impacted by lockdown measures, various provinces plunged drastically remained low until at which time it gradually increased. (2) For spatial pattern, pattern divided geographic demarcation line known as Hu (Heihe-Tengchong) Line, high-density interconnected southeast half low-density serial-connection northwest half. During Wuhan city appeared hollow region network; increased gradually, but was mainly focused on intra-provincial (3) characteristic changes, gap status cities different administrative levels narrowed significantly. Thus, feasibility migration data, comparison non-epidemic optimal implications are discussed. described difference specific information under non-normal situation compared existing normal situation, analyzed impact mechanism, can provide reference local governments make policy recommendations economic recovery future epidemic