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Large-scale and diffuse population flow amplifies the localized COVID-19 outbreak into a widespread pandemic. Network analysis provides a new methodology to uncover the topology and evolution of the population flow and understand its influence on the early dynamics of COVID-19 transmission. In this paper, we simulated 42 transmission scenarios to show the distribution of the COVID-19 outbreak across China. We predicted some original (Guangzhou, Shanghai, Shenzhen) had higher total aggregate population outflows than Wuhan, indicating larger spread scopes and faster growth rates of COVID-19 outbreak. We built an importation risk model to identify some major cities (Dongguan and Foshan) with the highest total importation risk values and the highest standard deviations, indicating the core transmission chains (Dongguan-Shenzhen, Foshan-Guangzhou). We built the population flow networks to analyze their Spatio-temporal characteristics and identify the influential sub-groups and spreaders. By removing different influential spreaders, we identified Guangzhou can most influence the network's topological characteristics, and some major cities' degree centrality was significantly decreased. Our findings quantified the effectiveness of travel restrictions on delaying the epidemic growth and limiting the spread scope of COVID-19 in China, which helped better derive the geographical COVID-19 transmission related to population flow networks' structural features. • 42 transmission scenarios were simulated to test contribution of different original epicenters to seeding COVID-19 in China. • An importation risk model was built to test contribution of population flow among multiple epicenters to spreading COVID-19. • A population flow network was built to capture evolution of COVID-19 transmission and identify influential spreaders. • This paper quantified the effectiveness of travel restrictions on reducing the numbers of confirmed COVID-19 cases in China. [ABSTRACT FROM AUTHOR]

Strict lockdowns were implemented in China to fight Coronavirus Disease 2019 (COVID‐19). We explored the nighttime light (NTL) of China's four cities in five stages of COVID‐19 including case free period, newly appeared period, rising period, outbreak period, and stationary period. Using six categories of points of interest data ("company," "recreation," "healthcare," "residence," "shopping," and "traffic facility") and random forest models, we found that dimming light of four cities is associated with the epidemic development and human activity changes. When confirmed cases appeared, healthcare associated NTL radiance increased rapidly in Wuhan and Guangzhou, but decreased in the fourth and fifth stages. Companies in all cities were resuscitated in the fifth stage, while companies in Guangzhou was resuscitated in the fourth stage. Shopping related NTL radiance in Wuhan increased quickly in the fifth stage which indicated some resuscitation. In addition, compared to gross domestic product, the trend in electric power consumption was consistent with the trend in NTL radiance. The above findings contribute to the making of control policies for COVID‐19 as well as other infectious diseases. Plain Language Summary: Impacted by the sweeping of Coronavirus disease 2019 (COVID‐19) across China in early 2020, lockdown measures were implemented leading to dramatic changes in human activities. Here, we use nighttime light (NTL) to quantify the impact of COVID‐19 on five phases of human activities during five stages. We find that dimming light in China's four cities is associated with the stage of epidemic development and human activity changes. When confirmed cases appeared, healthcare related NTL radiance increased, and companies related NTL radiance of four cities decreased. Residential related NTL radiance in Shanghai increased during outbreak period possibly from working at home. When the outbreak stabilized, shopping related NTL radiance in Wuhan increased quickly with economic resuscitation. In addition, electric power consumption has a better relationship with NTL radiance than gross domestic product. These results provide detailed information on the impact of the lockdown on different human activities and provide information for further control and openness policies. Key Points: Dimming light during Coronavirus disease 2019 lockdown observed by satellite coincides with the stage of epidemic developmentChanges in six categories of human activity can be considerably explained by nighttime light (NTL) changes (around 52%)GDP (or electric power consumption) has a consistent trend with the NTL radiance [ABSTRACT FROM AUTHOR]