Understanding the role of international flight networks in disease spread: spatial epidemic prevention zones and hierarchical disease control policies.

This study analyzed the January 2020 international flight network, i.e., during the early global spread of COVID-19, to examine how global air connectivity shaped the timing of first imported cases and to derive policy-relevant spatial risk groupings. Infomap was used to delineate spatial epidemic prevention zones (SEPZs), and network indicators, including PageRank, betweenness centrality, the clustering coefficient, and hyperlink-induced topic search (HITS), were used to characterize the international passenger arrival probability, transfer-related connectivity, connection density, and spatial potential transmission. Passenger arrival probability and connection density were associated with a shorter time to arrival (T2A) of the first imported COVID-19 case, whereas a greater geographical distance was associated with a longer T2A. In contrast, macroscale socioeconomic indicators showed limited explanatory power in the early disease transmission. Building on the SEPZs and spatial transmission potential, we propose a hierarchical disease control framework as a decision-support tool for early-stage cross-border risk assessment and scenario planning.