The effect of human mobility and control measures on the COVID-19 epidemic in China

TLDR

The COVID‑19 outbreak spread rapidly across China, prompting extensive behavioral, clinical, and state interventions, yet it remains unclear how travel restrictions and other measures affected transmission. The study aimed to use real‑time mobility and detailed case data to clarify how case importation influenced transmission across Chinese cities and to evaluate the effect of control measures. The authors analyzed real‑time mobility data from Wuhan combined with detailed case and travel history records to assess transmission dynamics and control measure impacts across cities. The analysis revealed that early spatial patterns of cases were strongly linked to human mobility, but after control measures were enacted, this link weakened and growth rates turned negative in most areas, demonstrating that stringent interventions substantially curtailed COVID‑19 spread.

Abstract

The ongoing coronavirus disease 2019 (COVID-19) outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions were undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We used real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation in transmission in cities across China and to ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. After the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside of Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.