Quantifying COVID-19-induced disruptions and recovery benchmarks in China’s aviation passenger mobility (2020–2025)

Abstract

The COVID-19 pandemic exerted profound impacts on various facets of global society. The lockdown measures implemented to curb the spread of the virus significantly disrupted the upward trend of civil aviation transportation. This study assesses the pandemic’s impact on China’s air passenger traffic (APT) using three forecasting models to construct counterfactual scenarios. By comparing predicted and actual APT (ΔAPT), we quantify the pandemic—induced losses and analyze their temporal patterns. The initial outbreak caused a sharp drop in APT, with the largest annual loss occurring in 2022. Following the relaxation of control measures in December 2022, APT began to rebound and resumed seasonal patterns. However, full recovery is projected for mid-2025 monthly and early 2026 on a quarterly basis. The integration of three forecasting models improved prediction accuracy and revealed a 12-day lag effect between COVID-19 case trends and changes in APT. This research contributes to understanding the dynamic relationship between public health events and transportation systems. Based on the findings, two policy recommendations are proposed: developing a flexible system that connects real-time epidemic data with aviation responses; improving decision-making by using detailed passenger and regional demand data. These measures can improve the resilience and adaptability of the aviation sector in response to future crises.