Yuan Yun, a master candidate of the School of Economics and Management, published a paper on line in Nature as the third author following his participation in the research of predicting the pandemic geographical distribution and transmission trend based on the actual population flow.

Yuan Yun, under the guidance of his supervisor and in collaboration with several professors at home and abroad, published online the paper “Population Flow Drives Spatio-Temporal Distribution of COVID-19 in China” in Nature on April 29, 2020 (London time).

The paper introduces a “population flow - risk source model” that can accurately predict the timing and geographic distribution of the COVID-19 with the aid of the anonymized aggregated data on population flow, facilitating effective risk assessment and resource allocation by decision makers.

Professor Nicholas Christakis from Yale University (U.S.), one of the authors of this paper, said, “The results of this study reveal the accuracy of China’s reports on COVID-19 cases. The totally different information from different sources (population flow shown by mobile communications) can help predict the number of cases well, which is in line with epidemiological expectations (at least before Feb. 19).”