Spatial temporal modelling of air traffic network evolution and resilience enhancement in response to the dynamic coupling of propagation outbreaks

COVID-19 has a great impact on the volume and frequency of air transportation. To minimise the transmission risk, civil aviation authorities imposed travel restrictions and led to changes of the global and regional air traffic network (ATN). Considering the potential for future similar propagable events that may challenge the operation of the ATN again, it is crucial to develop more efficient air route adjustment schemes (ARAS) to better respond to propagable outbreaks. This study first examines the development patterns of propagable events and constructs a spatial temporal evolution model under the coupling of event development and traffic flow. Based on the dynamic process of the spatial temporal evolution model, the study explores the resilience assessment method of the ATN throughout the entire cycle of events. This study proposes a methodological framework to intervene in the air route reduction and recovery of any two connected airport pairs based on the prioritised network centrality (PNC) during all rising and descending phases of propagatable outbreaks to achieve overall ATN network resilience enhancement, and the model is validated by the case under COVID-19 background. The numerical study shows that the adjustment of air route capacity has a significant impact on the control of the introduction of cases in the initial phase. However, there is no significant impact on controlling the risk of propagation if the destined regions face widespread local propagation. This explains that travel restriction and quarantine of the ATN do not contribute to controlling the local propagation of regions but can ameliorate the severity of the overall outbreak at the network level by affecting the spreading sequence across the network. To improve the network resilience in response to propagable outbreaks, The air route adjustment scheme considering prioritised network centrality (ARAS-PNC) approach can capitalise on the impact of network performance and outbreak progression and respond better at the network level with greater network efficiency and lower network-wide effective case rate.