Fig. 2: Factors correlated with confirmed COVID-19 cases.

a, b, The relationship between the log-transformed aggregate population outflow from Wuhan (up to 24 January 2020) and the log-transformed number of confirmed cases by prefecture on 26 January 2020 (a) and 19 February 2020 (b). Red circles are prefectures in Hubei; light blue circles are four quarantined prefectures in Zhejiang (including Wenzhou); and the six largest prefectures in China are indicated with unique colours. c, Relationship over time between the number of confirmed cases (cumulative until 19 February 2020) and the cumulative population inflow (up to 24 January 2020) from Wuhan, the cumulative inflow from Hubei province excluding Wuhan, the frequency of Baidu search terms related to the virus, the GDP, population and distance from Wuhan of the prefectures. Over time, the correlation between population outflow from Wuhan and the number of infected cases increases from Pearson’s r = 0.522 on 24 January 2020 to r = 0.952 on 19 February (n = 296 prefectures). The decrease in the predictive strength of online search behaviour might reflect information saturation, while the decrease in the predictive strength of GDP, population size and distance suggests that late-stage Chunyun migration from Wuhan was to a more diverse set of prefectures (and not merely to the closet, largest and most-developed prefectures) and/or that community transmissions began to predominate. d, The correlation with daily infections is consistent throughout the period with Pearson’s r ranging from 0.496 on 24 January 2020 to a peak of 0.926 on 4 February 2020 (n = 296 prefectures). Fluctuations probably indicate lags in the reporting of cases (that are smoothed in c); weaker correlations on the last few days reflect that more than 90% of prefectures outside of Hubei reported no new cases.